fix: preserve literal 'NULL' strings for primary key columns

fix: convert NaN/NULL to None and restore record properties structure in tap.py
feat: ingest independent schools in Ofsted tap and dbt staging
2026-07-16 08:54:14 +01:00 · 2026-07-16 08:29:59 +01:00 · 2026-07-15 23:21:40 +01:00 · 2026-07-15 17:38:02 +01:00 · 2026-07-15 17:23:40 +01:00 · 2026-07-15 12:32:36 +01:00
110 changed files with 11990 additions and 1225 deletions
@@ -1,4 +1,4 @@
-name: Deploy (staging -> E2E gate -> production)
+name: Stage (build -> staging -> E2E gate)

 on:
  push:
@@ -193,48 +193,5 @@ jobs:
        env:
          BASE_URL: ${{ secrets.STAGING_BASE_URL }}

-  promote-prod:
-    name: Promote to Production
-    runs-on: ubuntu-latest
-    needs: [e2e-staging]
-    steps:
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
-
-      - name: Log in to Gitea Container Registry
-        uses: docker/login-action@v3
-        with:
-          registry: ${{ env.REGISTRY }}
-          username: ${{ gitea.actor }}
-          password: ${{ secrets.REGISTRY_TOKEN }}
-
-      - name: Retag verified images as prod
-        run: |
-          SHORT_SHA="sha-$(echo "${{ gitea.sha }}" | cut -c1-7)"
-          for IMAGE in \
-            "${REGISTRY}/${BACKEND_IMAGE_NAME}" \
-            "${REGISTRY}/${FRONTEND_IMAGE_NAME}" \
-            "${REGISTRY}/${PIPELINE_IMAGE_NAME}"; do
-            # Keep a rollback pointer before moving :prod
-            docker buildx imagetools create -t "${IMAGE}:prod-previous" "${IMAGE}:prod" || true
-            docker buildx imagetools create -t "${IMAGE}:prod" "${IMAGE}:${SHORT_SHA}"
-            echo "Promoted ${IMAGE}:${SHORT_SHA} -> :prod"
-          done
-
-      - name: Trigger production stack update
-        run: curl -fsSk -X POST "${{ secrets.PORTAINER_PROD_WEBHOOK }}"
-
-      - name: Wait for production to become healthy
-        run: |
-          echo "Polling ${PROD_BASE_URL} for up to 5 minutes..."
-          for i in $(seq 1 60); do
-            if curl -fsS -o /dev/null --max-time 10 "${PROD_BASE_URL}/"; then
-              echo "Production is up (attempt $i)"
-              exit 0
-            fi
-            sleep 5
-          done
-          echo "Production did not become healthy in time" >&2
-          exit 1
-        env:
-          PROD_BASE_URL: ${{ secrets.PROD_BASE_URL }}
+# Production deployment is a second, manual approval: see promote.yml
+# ("Promote to Production (manual)") and docs/DEPLOY.md.
@@ -5,6 +5,13 @@ on:
    branches:
      - main

+# Cancel superseded runs: pushing a new commit to a PR (or an empty
+# re-trigger) aborts the previous still-running checks instead of running
+# a second full matrix alongside them.
+concurrency:
+  group: pr-checks-${{ gitea.event.pull_request.number }}
+  cancel-in-progress: true
+
 env:
  REGISTRY: privaterepo.sitaru.org
  BACKEND_IMAGE_NAME: ${{ gitea.repository }}-backend
@@ -23,12 +30,22 @@ jobs:
        uses: actions/setup-node@v4
        with:
          node-version: 22
-          cache: npm
-          cache-dependency-path: nextjs-app/package-lock.json
+
+      # Cache the resolved node_modules (452 MB / 460 packages) keyed on the
+      # lockfile. On a hit — the common case, since deps change rarely — the
+      # whole `npm ci` step is skipped, not just its download phase. The key
+      # pins OS + node major so we never restore incompatible native binaries.
+      - name: Cache node_modules
+        id: node-modules-cache
+        uses: actions/cache@v4
+        with:
+          path: nextjs-app/node_modules
+          key: nextjs-node-modules-${{ runner.os }}-node22-${{ hashFiles('nextjs-app/package-lock.json') }}

      - name: Install dependencies
+        if: steps.node-modules-cache.outputs.cache-hit != 'true'
        working-directory: nextjs-app
-        run: npm ci
+        run: npm ci --prefer-offline --no-audit --no-fund

      - name: Typecheck
        working-directory: nextjs-app
@@ -51,11 +68,14 @@ jobs:
          python-version: "3.12"

      - name: Install dependencies
-        run: pip install -r requirements.txt
+        run: pip install -r requirements.txt pytest "httpx<0.28"

      - name: Import smoke test
        run: python -c "from backend.app import app; print('backend imports OK')"

+      - name: Backend unit tests
+        run: python -m pytest backend/tests -q
+
  build-backend:
    name: Build Backend (no push)
    runs-on: ubuntu-latest
@@ -0,0 +1,126 @@
+name: Promote to Production (manual)
+
+# Second approval gate of the deploy model: run this workflow from the
+# Actions UI after testing the feature on staging. It refuses commits
+# whose staging E2E gate is not green. See docs/DEPLOY.md.
+
+on:
+  workflow_dispatch:
+    inputs:
+      sha:
+        description: >-
+          Commit SHA on main to promote (full or >=7 chars).
+          Leave empty to promote the latest main commit.
+        required: false
+        default: ""
+
+# Only one promotion at a time; never cancel an in-flight promotion.
+concurrency:
+  group: prod-promotion
+  cancel-in-progress: false
+
+env:
+  REGISTRY: privaterepo.sitaru.org
+  BACKEND_IMAGE_NAME: ${{ gitea.repository }}-backend
+  FRONTEND_IMAGE_NAME: ${{ gitea.repository }}-frontend
+  PIPELINE_IMAGE_NAME: ${{ gitea.repository }}-pipeline
+
+jobs:
+  promote-prod:
+    name: Promote approved commit to Production
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository (full history for ancestry check)
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Resolve and validate target SHA
+        id: resolve
+        # SECURITY: the dispatch input is untrusted — it reaches the shell
+        # only via env (never spliced into `run:` with ${{ }}) and is only
+        # used as a quoted argument. The resolved value is validated as a
+        # 40-hex sha and required to be an ancestor of main before any
+        # later step interpolates it.
+        env:
+          SHA_INPUT: ${{ gitea.event.inputs.sha }}
+        run: |
+          set -euo pipefail
+          case "$SHA_INPUT" in
+            -*) echo "REFUSED: SHA input may not start with '-'." >&2; exit 1 ;;
+          esac
+          if [ -z "$SHA_INPUT" ]; then
+            SHA_INPUT="$(git rev-parse origin/main)"
+          fi
+          FULL_SHA=$(git rev-parse --verify --quiet "${SHA_INPUT}^{commit}") || {
+            echo "REFUSED: not a commit in this repository." >&2
+            exit 1
+          }
+          echo "$FULL_SHA" | grep -Eq '^[0-9a-f]{40}$'
+          if ! git merge-base --is-ancestor "$FULL_SHA" origin/main; then
+            echo "REFUSED: $FULL_SHA is not on main — only main commits are promotable." >&2
+            exit 1
+          fi
+          SHORT_SHA="sha-$(echo "$FULL_SHA" | cut -c1-7)"
+          echo "full=$FULL_SHA" >> "$GITHUB_OUTPUT"
+          echo "short=$SHORT_SHA" >> "$GITHUB_OUTPUT"
+          echo "Promoting $FULL_SHA (images tagged $SHORT_SHA)"
+
+      - name: Verify the staging E2E gate passed for this commit
+        run: |
+          STATUS_JSON=$(curl -fsS \
+            -H "Authorization: token ${{ secrets.REGISTRY_TOKEN }}" \
+            "https://${REGISTRY}/api/v1/repos/${{ gitea.repository }}/commits/${{ steps.resolve.outputs.full }}/status")
+          echo "$STATUS_JSON" | python3 -c "
+          import json, sys
+          d = json.load(sys.stdin)
+          ok = [s for s in d.get('statuses', [])
+                if 'E2E Journeys against Staging' in s.get('context', '')
+                and s.get('status') == 'success']
+          if not ok:
+              print('REFUSED: no successful \"E2E Journeys against Staging\" status on this commit.')
+              print('Contexts found:', [s.get('context') for s in d.get('statuses', [])])
+              sys.exit(1)
+          print('E2E gate verified green for this commit.')
+          "
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Log in to Gitea Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ gitea.actor }}
+          password: ${{ secrets.REGISTRY_TOKEN }}
+
+      - name: Retag approved images as prod (keeping rollback pointer)
+        run: |
+          SHORT_SHA="${{ steps.resolve.outputs.short }}"
+          for IMAGE in \
+            "${REGISTRY}/${BACKEND_IMAGE_NAME}" \
+            "${REGISTRY}/${FRONTEND_IMAGE_NAME}" \
+            "${REGISTRY}/${PIPELINE_IMAGE_NAME}"; do
+            # Keep a rollback pointer before moving :prod
+            docker buildx imagetools create -t "${IMAGE}:prod-previous" "${IMAGE}:prod" || true
+            docker buildx imagetools create -t "${IMAGE}:prod" "${IMAGE}:${SHORT_SHA}"
+            echo "Promoted ${IMAGE}:${SHORT_SHA} -> :prod"
+          done
+
+      - name: Trigger production stack update
+        run: curl -fsSk -X POST "${{ secrets.PORTAINER_PROD_WEBHOOK }}"
+
+      - name: Wait for production to become healthy
+        run: |
+          echo "Polling ${PROD_BASE_URL} for up to 5 minutes..."
+          for i in $(seq 1 60); do
+            if curl -fsS -o /dev/null --max-time 10 "${PROD_BASE_URL}/"; then
+              echo "Production is up (attempt $i)"
+              exit 0
+            fi
+            sleep 5
+          done
+          echo "Production did not become healthy in time" >&2
+          exit 1
+        env:
+          PROD_BASE_URL: ${{ secrets.PROD_BASE_URL }}
@@ -1,2 +1,2 @@
 venv
-backend/__pycache__
+__pycache__/
@@ -25,15 +25,17 @@ import asyncio
 from .config import settings
 from .data_loader import (
    clear_cache,
+    compute_benchmarks,
    load_school_data,
    load_latest_school_data,
    geocode_single_postcode,
    get_supplementary_data,
+    get_supplementary_data_batch,
    search_schools_typesense,
 )
 from .data_loader import get_data_info as get_db_info
 from .schemas import METRIC_DEFINITIONS, RANKING_COLUMNS, SCHOOL_COLUMNS
-from .utils import clean_for_json
+from .utils import clean_for_json, convert_to_native

 # Values to exclude from filter dropdowns (empty strings, non-applicable labels)
 EXCLUDED_FILTER_VALUES = {"", "Not applicable", "Does not apply"}
@@ -416,10 +418,17 @@ async def get_schools(
        df_latest = df_latest[df_latest["gender"].str.lower() == gender.lower()]
    if admissions_policy:
        df_latest = df_latest[df_latest["admissions_policy"].str.lower() == admissions_policy.lower()]
-    if has_sixth_form == "yes":
-        df_latest = df_latest[df_latest["age_range"].str.contains("18", na=False)]
-    elif has_sixth_form == "no":
-        df_latest = df_latest[~df_latest["age_range"].str.contains("18", na=False)]
+    # GIAS OfficialSixthForm flag (dim_school.has_sixth_form). NULL (flag not
+    # yet populated by the pipeline) is treated as "no sixth form".
+    if has_sixth_form in ("yes", "no"):
+        if "has_sixth_form" in df_latest.columns:
+            flag = df_latest["has_sixth_form"].eq(True)
+        else:  # Defensive fallback only — data_loader now always synthesizes
+            # has_sixth_form as NULL when the DB predates the pipeline re-run,
+            # so this branch shouldn't normally trigger. Falls back to age
+            # range if the column is somehow absent anyway.
+            flag = df_latest["age_range"].str.contains("18", na=False)
+        df_latest = df_latest[flag if has_sixth_form == "yes" else ~flag]

    # Include key result metrics for display on cards
    location_cols = ["latitude", "longitude"]
@@ -582,8 +591,13 @@ async def get_school_details(request: Request, urn: int):
    except Exception:
        pass

-    return {
-        "school_info": {
+    # Schools with no performance rows (post-16 institutions, PRUs, new
+    # schools) carry NaN in every LEFT-JOINed numeric column; NaN reaching
+    # JSONResponse raises ValueError, so school_info needs the same
+    # conversion yearly_data gets from clean_for_json.
+    school_info = {
+        k: convert_to_native(v)
+        for k, v in {
            "urn": urn,
            "school_name": latest.get("school_name", ""),
            "local_authority": latest.get("local_authority", ""),
@@ -591,6 +605,8 @@ async def get_school_details(request: Request, urn: int):
            "address": latest.get("address", ""),
            "religious_denomination": latest.get("religious_denomination", ""),
            "age_range": latest.get("age_range", ""),
+            "has_sixth_form": latest.get("has_sixth_form"),
+            "status": latest.get("status"),
            "latitude": latest.get("latitude"),
            "longitude": latest.get("longitude"),
            "phase": latest.get("phase"),
@@ -601,7 +617,11 @@ async def get_school_details(request: Request, urn: int):
            "total_pupils": latest.get("gias_total_pupils"),
            "trust_name": latest.get("trust_name"),
            "gender": latest.get("gender"),
-        },
+        }.items()
+    }
+
+    return {
+        "school_info": school_info,
        "yearly_data": clean_for_json(school_data),
        # Supplementary data (null if not yet populated by Kestra)
        "ofsted": supplementary.get("ofsted"),
@@ -644,6 +664,36 @@ async def compare_schools(
    if comparison_data.empty:
        raise HTTPException(status_code=404, detail="No schools found")

+    # One session for all schools' supplementary blocks; failures degrade
+    # to empty blocks rather than failing a working comparison (mirrors
+    # the detail endpoint's defensive pattern).
+    from . import database
+
+    _EMPTY_SUPPLEMENTARY = {
+        "ofsted": None,
+        "census": None,
+        "admissions": None,
+        "admissions_history": [],
+        "deprivation": None,
+    }
+    supplementary_by_urn: dict = {}
+    db = None
+    try:
+        db = database.SessionLocal()
+        # One query per table for all schools, not ~5 queries per school.
+        batch = get_supplementary_data_batch(db, urn_list)
+        for urn in urn_list:
+            supp = batch.get(urn, {})
+            supplementary_by_urn[urn] = {
+                key: supp.get(key, default)
+                for key, default in _EMPTY_SUPPLEMENTARY.items()
+            }
+    except Exception:
+        supplementary_by_urn = {}
+    finally:
+        if db is not None:
+            db.close()
+
    result = {}
    for urn in urn_list:
        school_data = comparison_data[comparison_data["urn"] == urn].sort_values("year")
@@ -659,11 +709,27 @@ async def compare_schools(
                    "phase": latest.get("phase", ""),
                    "attainment_8_score": float(latest["attainment_8_score"]) if pd.notna(latest.get("attainment_8_score")) else None,
                    "rwm_expected_pct": float(latest["rwm_expected_pct"]) if pd.notna(latest.get("rwm_expected_pct")) else None,
+                    # GIAS facts the compare "Who goes there" section needs
+                    # (same fields the detail endpoint exposes)
+                    "religious_denomination": convert_to_native(latest.get("religious_denomination")),
+                    "age_range": convert_to_native(latest.get("age_range")),
+                    "gender": convert_to_native(latest.get("gender")),
+                    "has_sixth_form": convert_to_native(latest.get("has_sixth_form")),
+                    "capacity": convert_to_native(latest.get("capacity")),
+                    "gias_total_pupils": convert_to_native(latest.get("gias_total_pupils")),
+                    "trust_name": convert_to_native(latest.get("trust_name")),
                },
                "yearly_data": clean_for_json(school_data),
+                **supplementary_by_urn.get(urn, dict(_EMPTY_SUPPLEMENTARY)),
            }

-    return {"comparison": result}
+    return {
+        "comparison": result,
+        # Official DfE anchors + computed state-school benchmarks so the
+        # compare UI can label provenance correctly (spec §8.6).
+        "national_averages": _national_averages_payload(df),
+        "benchmarks": compute_benchmarks(df),
+    }


@app.get("/api/filters")
@@ -709,96 +775,101 @@ async def get_la_averages(request: Request):
    return {"year": latest_year, "secondary": {"attainment_8_by_la": la_avg}}


-@app.get("/api/national-averages")
-@limiter.limit(f"{settings.rate_limit_per_minute}/minute")
-async def get_national_averages(request: Request):
-    """
-    Compute national average for each metric from the latest data year.
-    Returns separate averages for primary (KS2) and secondary (KS4) schools.
-    Values are derived from the loaded DataFrame so they automatically
-    stay current when new data is loaded.
-    """
-    df = load_school_data()
-    if df.empty:
-        return {"primary": {}, "secondary": {}}
-
-    ks2_metrics = [
+_KS2_NATIONAL_METRICS = [
    "rwm_expected_pct", "rwm_high_pct",
    "reading_expected_pct", "writing_expected_pct", "maths_expected_pct",
+    "gps_expected_pct", "gps_high_pct", "science_expected_pct",
    "reading_avg_score", "maths_avg_score", "gps_avg_score",
    "reading_progress", "writing_progress", "maths_progress",
    "overall_absence_pct", "persistent_absence_pct",
    "disadvantaged_gap", "disadvantaged_pct", "sen_support_pct", "eal_pct",
-    ]
-    ks4_metrics = [
+]
+_KS4_NATIONAL_METRICS = [
    "attainment_8_score", "progress_8_score",
    "english_maths_standard_pass_pct", "english_maths_strong_pass_pct",
    "ebacc_entry_pct", "ebacc_standard_pass_pct", "ebacc_strong_pass_pct",
    "ebacc_avg_score", "gcse_grade_91_pct",
-    ]
+]

-    def _means(sub_df, metric_list):
-        out = {}
-        for col in metric_list:
-            if col in sub_df.columns:
-                val = sub_df[col].dropna()
-                if len(val) > 0:
-                    out[col] = round(float(val.mean()), 2)
-        return out
+
+def _national_averages_payload(df: pd.DataFrame) -> dict:
+    """National-averages payload shared by /api/national-averages and
+    /api/compare.
+
+    Both series are persisted marts computed at import time: official DfE
+    KS2 figures (fact_ks2_national_averages) and dataset-computed KS4
+    averages (fact_ks4_national_averages) — the API never aggregates the
+    performance dataframe per request. If the KS4 mart hasn't been built
+    yet (deploy lands before the next DAG run), fall back to computing the
+    latest year only — a single-year scan, never the historical loop.
+    """
+    if df.empty:
+        return {"primary": {}, "secondary": {}}

    latest_year = int(df["year"].max())
-    df_latest = df[df["year"] == latest_year]

-    # Primary: schools where KS2 data is non-null
-    primary_df = df_latest[df_latest["rwm_expected_pct"].notna()]
-    # Secondary: schools where KS4 data is non-null
-    secondary_df = df_latest[df_latest["attainment_8_score"].notna()]
+    from . import database
+    from .models import Ks2NationalAverage, Ks4NationalAverage

-    latest_primary = _means(primary_df, ks2_metrics)
-    latest_secondary = _means(secondary_df, ks4_metrics)
-
-    # Per-year KS2 primary averages: use official DfE figures from the mart table.
-    # Per-year KS4 secondary averages: computed from our dataset (no DfE dataset yet).
-    from .database import SessionLocal
-    from .models import Ks2NationalAverage
-
-    by_year = []
-    try:
-        db = SessionLocal()
-        nat_rows = db.query(Ks2NationalAverage).order_by(Ks2NationalAverage.year).all()
-        # Build a lookup of computed secondary averages per year as fallback
-        secondary_by_year = {}
-        for yr in sorted(df["year"].dropna().unique()):
-            yr = int(yr)
-            df_yr = df[df["year"] == yr]
-            secondary_by_year[yr] = _means(
-                df_yr[df_yr["attainment_8_score"].notna()], ks4_metrics
-            )
-        # Merge: official KS2 figures + computed KS4 figures per year
-        ks2_years = {r.year for r in nat_rows}
-        all_years = sorted(ks2_years | set(secondary_by_year.keys()))
-        nat_lookup = {r.year: r for r in nat_rows}
-        for yr in all_years:
-            primary_yr: dict = {}
-            if yr in nat_lookup:
-                r = nat_lookup[yr]
-                for col in ks2_metrics:
-                    val = getattr(r, col, None)
+    def _row_metrics(row, metric_list):
+        out = {}
+        for col in metric_list:
+            val = getattr(row, col, None)
            if val is not None:
-                        primary_yr[col] = val
-            by_year.append({
-                "year": yr,
-                "primary": primary_yr,
-                "secondary": secondary_by_year.get(yr, {}),
-            })
+                out[col] = val
+        return out
+
+    ks2_rows: list = []
+    ks4_rows: list = []
+    db = None
+    try:
+        db = database.SessionLocal()
+        try:
+            ks2_rows = db.query(Ks2NationalAverage).order_by(Ks2NationalAverage.year).all()
+        except Exception:
+            db.rollback()
+        try:
+            ks4_rows = db.query(Ks4NationalAverage).order_by(Ks4NationalAverage.year).all()
+        except Exception:
+            db.rollback()
+    except Exception:
+        pass
    finally:
+        if db is not None:
            db.close()

-    # Update latest_primary with official DfE figure for the latest year if available
-    if by_year:
-        latest_official = next((e["primary"] for e in reversed(by_year) if e["primary"]), None)
-        if latest_official:
-            latest_primary = latest_official
+    primary_by_year = {r.year: _row_metrics(r, _KS2_NATIONAL_METRICS) for r in ks2_rows}
+    secondary_by_year = {r.year: _row_metrics(r, _KS4_NATIONAL_METRICS) for r in ks4_rows}
+
+    if not any(secondary_by_year.values()):
+        # KS4 mart missing/empty: compute the latest year only.
+        df_latest = df[df["year"] == latest_year]
+        sec = (
+            df_latest[df_latest["attainment_8_score"].notna()]
+            if "attainment_8_score" in df_latest.columns
+            else df_latest.iloc[0:0]
+        )
+        vals = {}
+        for col in _KS4_NATIONAL_METRICS:
+            if col in sec.columns:
+                v = sec[col].dropna()
+                if len(v) > 0:
+                    vals[col] = round(float(v.mean()), 2)
+        if vals:
+            secondary_by_year[latest_year] = vals
+
+    all_years = sorted(set(primary_by_year) | set(secondary_by_year))
+    by_year = [
+        {
+            "year": yr,
+            "primary": primary_by_year.get(yr, {}),
+            "secondary": secondary_by_year.get(yr, {}),
+        }
+        for yr in all_years
+    ]
+
+    latest_primary = next((e["primary"] for e in reversed(by_year) if e["primary"]), {})
+    latest_secondary = next((e["secondary"] for e in reversed(by_year) if e["secondary"]), {})

    return {
        "year": latest_year,
@@ -808,6 +879,17 @@ async def get_national_averages(request: Request):
    }


+@app.get("/api/national-averages")
+@limiter.limit(f"{settings.rate_limit_per_minute}/minute")
+async def get_national_averages(request: Request):
+    """
+    National averages: official DfE KS2 figures per year plus computed
+    KS4 averages, derived from the loaded DataFrame and the
+    fact_ks2_national_averages mart.
+    """
+    return _national_averages_payload(load_school_data())
+
+
@app.get("/api/metrics")
@limiter.limit(f"{settings.rate_limit_per_minute}/minute")
 async def get_available_metrics(request: Request):
@@ -3,11 +3,15 @@ Data loading module — reads from marts.* tables built by dbt.
 Provides efficient queries with caching.
 """

+import logging
+import re
+
 import pandas as pd
 import numpy as np
 from typing import Optional, Dict, Tuple, List
 import requests
 from sqlalchemy import text
+import sqlalchemy.exc
 from sqlalchemy.orm import Session

 from .config import settings
@@ -17,7 +21,40 @@ from .models import (
    FactOfstedInspection, FactAdmissions,
    FactDeprivation, FactFinance, FactPupilCharacteristics,
 )
+from .ofsted_codes import ofsted_page_url, report_card_labels
 from .schemas import SCHOOL_TYPE_MAP
+from .gias_codes import (
+    ADMISSIONS_POLICY,
+    ESTABLISHMENT_STATUS,
+    PHASE_OF_EDUCATION,
+    RELIGIOUS_CHARACTER,
+    SCHOOL_TYPE,
+    translate,
+)
+
+# mart code column -> (API name column, dictionary)
+_GIAS_CODE_COLUMNS = {
+    "phase_code": ("phase", PHASE_OF_EDUCATION),
+    "school_type_code": ("school_type", SCHOOL_TYPE),
+    "status_code": ("status", ESTABLISHMENT_STATUS),
+    "religious_character_code": ("religious_denomination", RELIGIOUS_CHARACTER),
+    "admissions_policy_code": ("admissions_policy", ADMISSIONS_POLICY),
+}
+
+
+def translate_gias_code_columns(df: pd.DataFrame) -> pd.DataFrame:
+    """Map GIAS code columns to today's name columns (API contract).
+
+    Runs immediately after pd.read_sql so every downstream consumer —
+    filters, PHASE_GROUPS, payloads, /api/filters — keeps seeing names.
+    DataFrames without the code columns (old schema, test fixtures) pass
+    through unchanged.
+    """
+    for code_col, (name_col, mapping) in _GIAS_CODE_COLUMNS.items():
+        if code_col in df.columns:
+            df[name_col] = df[code_col].map(lambda c: translate(c, mapping))
+    return df
+

 _postcode_cache: Dict[str, Tuple[float, float]] = {}
 _typesense_client = None
@@ -118,14 +155,16 @@ _MAIN_QUERY = text("""
    SELECT
        s.urn,
        s.school_name,
-        s.phase,
-        s.school_type,
+        s.phase_code,
+        s.school_type_code,
        s.academy_trust_name   AS trust_name,
        s.academy_trust_uid    AS trust_uid,
-        s.religious_character  AS religious_denomination,
+        s.religious_character_code,
        s.gender,
        s.age_range,
-        s.admissions_policy,
+        s.has_sixth_form,
+        s.status_code,
+        s.admissions_policy_code,
        s.capacity,
        s.total_pupils         AS gias_total_pupils,
        s.headteacher_name,
@@ -152,13 +191,20 @@ _MAIN_QUERY = text("""
        p.reading_high_pct,
        p.reading_avg_score,
        p.reading_progress,
+        p.reading_progress_lower_ci,
+        p.reading_progress_upper_ci,
        p.writing_expected_pct,
        p.writing_high_pct,
        p.writing_progress,
+        p.writing_progress_lower_ci,
+        p.writing_progress_upper_ci,
+        p.writing_working_towards_pct,
        p.maths_expected_pct,
        p.maths_high_pct,
        p.maths_avg_score,
        p.maths_progress,
+        p.maths_progress_lower_ci,
+        p.maths_progress_upper_ci,
        p.gps_expected_pct,
        p.gps_high_pct,
        p.gps_avg_score,
@@ -187,6 +233,9 @@ _MAIN_QUERY = text("""
        p.progress_8_maths,
        p.progress_8_ebacc,
        p.progress_8_open,
+        p.progress_8_banding,
+        p.attainment_8_disadvantage_gap,
+        p.progress_8_disadvantage_gap,
        p.english_maths_strong_pass_pct,
        p.english_maths_standard_pass_pct,
        p.ebacc_entry_pct,
@@ -214,11 +263,92 @@ _MAIN_QUERY = text("""
    ORDER BY s.school_name, p.year
 """)

+# Fallback used when marts.dim_school predates the has_sixth_form column
+# (i.e. the nightly dbt pipeline hasn't rebuilt the mart yet on this DB).
+# Keeps the column present as NULL so downstream code — including the
+# app.py fallback branch — behaves as designed instead of KeyError-ing.
+_MAIN_QUERY_NO_SIXTH_FORM = text(
+    str(_MAIN_QUERY).replace("s.has_sixth_form,", "NULL AS has_sixth_form,")
+)
+assert "NULL AS has_sixth_form" in str(_MAIN_QUERY_NO_SIXTH_FORM), (
+    "expected replacement of 's.has_sixth_form,' to have taken effect"
+)
+
+# Fallback used when marts.dim_school predates the GIAS code-dictionary
+# migration (i.e. the nightly dbt pipeline hasn't rebuilt the mart yet on
+# this DB, so it still has the old name columns instead of *_code columns).
+_MAIN_QUERY_LEGACY_NAMES = str(_MAIN_QUERY)
+_LEGACY_NAME_REPLACEMENTS = [
+    ("s.phase_code,", "s.phase,"),
+    ("s.school_type_code,", "s.school_type,"),
+    (
+        "s.religious_character_code,",
+        "s.religious_character AS religious_denomination,",
+    ),
+    ("s.status_code,", "s.status,"),
+    ("s.admissions_policy_code,", "s.admissions_policy,"),
+]
+for _old, _new in _LEGACY_NAME_REPLACEMENTS:
+    assert _old in _MAIN_QUERY_LEGACY_NAMES, (
+        f"expected {_old!r} to be present in _MAIN_QUERY before replacement"
+    )
+    _MAIN_QUERY_LEGACY_NAMES = _MAIN_QUERY_LEGACY_NAMES.replace(_old, _new)
+_MAIN_QUERY_LEGACY_NAMES = text(_MAIN_QUERY_LEGACY_NAMES)
+
+_GIAS_CODE_COLUMN_NAMES = (
+    "phase_code",
+    "school_type_code",
+    "religious_character_code",
+    "status_code",
+    "admissions_policy_code",
+)
+
+_MISSING_COLUMN_RE = re.compile(r'column "?(?:s\.)?(\w+)"? does not exist')
+
+
+def _missing_column_name(exc: Exception) -> Optional[str]:
+    """Name of the missing column from a psycopg2 UndefinedColumn error.
+
+    Inspects exc.orig (the DBAPI error), whose message names only the
+    offending column — str(exc) also embeds the full SQL statement, which
+    contains every column name and therefore must not be matched against.
+    """
+    orig = getattr(exc, "orig", None)
+    match = _MISSING_COLUMN_RE.search(str(orig) if orig is not None else str(exc))
+    return match.group(1) if match else None
+

 def load_school_data_as_dataframe() -> pd.DataFrame:
    """Load all school + KS2 data as a pandas DataFrame."""
    try:
        df = pd.read_sql(_MAIN_QUERY, engine)
+    except sqlalchemy.exc.ProgrammingError as exc:
+        missing = _missing_column_name(exc)
+        if missing in _GIAS_CODE_COLUMN_NAMES:
+            logging.getLogger(__name__).warning(
+                "marts predate the GIAS code migration — falling back to "
+                "legacy name-column query: %s",
+                exc,
+            )
+            try:
+                df = pd.read_sql(_MAIN_QUERY_LEGACY_NAMES, engine)
+            except Exception as exc2:
+                print(f"Warning: Could not load school data from marts: {exc2}")
+                return pd.DataFrame()
+        elif missing == "has_sixth_form":
+            logging.getLogger(__name__).warning(
+                "marts.dim_school is missing has_sixth_form (pipeline hasn't "
+                "rebuilt the mart yet on this DB) — retrying without it: %s",
+                exc,
+            )
+            try:
+                df = pd.read_sql(_MAIN_QUERY_NO_SIXTH_FORM, engine)
+            except Exception as exc2:
+                print(f"Warning: Could not load school data from marts: {exc2}")
+                return pd.DataFrame()
+        else:
+            print(f"Warning: Could not load school data from marts: {exc}")
+            return pd.DataFrame()
    except Exception as exc:
        print(f"Warning: Could not load school data from marts: {exc}")
        return pd.DataFrame()
@@ -226,6 +356,8 @@ def load_school_data_as_dataframe() -> pd.DataFrame:
    if df.empty:
        return df

+    df = translate_gias_code_columns(df)
+
    # Build address string
    df["address"] = df.apply(
        lambda r: ", ".join(
@@ -393,37 +525,101 @@ def get_data_info(db: Session = None) -> dict:
 # SUPPLEMENTARY DATA — per-school detail page
 # =============================================================================

-def get_supplementary_data(db: Session, urn: int) -> dict:
-    """Fetch all supplementary data for a single school URN."""
-    result = {}
+def compute_benchmarks(df: pd.DataFrame) -> dict:
+    """State-school benchmarks computed from our dataset (spec §5/§8.6).

-    def safe_query(model, pk_field, latest_field=None):
-        try:
-            q = db.query(model).filter(getattr(model, pk_field) == urn)
-            if latest_field:
-                q = q.order_by(getattr(model, latest_field).desc())
-            return q.first()
-        except Exception as e:
-            import logging
-            logging.getLogger(__name__).error("safe_query failed for %s: %s", model.__name__, e)
-            db.rollback()
+    NOT official DfE figures — consumers must label them
+    "state-school average (computed from our dataset)". The disadvantaged
+    attainment average is weighted by cohort size (eligible_pupils) so
+    small schools don't dominate; context measures are medians.
+    """
+    if df.empty or "year" not in df.columns:
+        return {}
+    latest_year = df["year"].max()
+    if pd.isna(latest_year):
+        return {}
+    d = df[df["year"] == latest_year]
+    if d.empty:
+        return {}
+    is_secondary = (
+        d["attainment_8_score"].notna()
+        if "attainment_8_score" in d.columns
+        else pd.Series(False, index=d.index)
+    )
+    prim, sec = d[~is_secondary], d[is_secondary]
+
+    def _median(sub, col):
+        if col not in sub.columns:
            return None
+        v = sub[col].median()
+        return round(float(v), 1) if pd.notna(v) else None

-    # Latest Ofsted inspection
-    o = safe_query(FactOfstedInspection, "urn", "inspection_date")
-    result["ofsted"] = (
-        {
+    def _weighted_disadvantaged(sub):
+        needed = {"rwm_expected_disadvantaged_pct", "eligible_pupils"}
+        if not needed <= set(sub.columns):
+            return None
+        s = sub.dropna(subset=list(needed))
+        if s.empty or s["eligible_pupils"].sum() == 0:
+            return None
+        w = (
+            (s["rwm_expected_disadvantaged_pct"] * s["eligible_pupils"]).sum()
+            / s["eligible_pupils"].sum()
+        )
+        return round(float(w), 1)
+
+    def _block(sub, with_disadvantaged):
+        median_pupils = None
+        if "total_pupils" in sub.columns:
+            mp = sub["total_pupils"].median()
+            if pd.notna(mp):
+                median_pupils = int(mp)
+        block = {
+            "eal_pct": _median(sub, "eal_pct"),
+            "sen_support_pct": _median(sub, "sen_support_pct"),
+            "disadvantaged_pct": _median(sub, "disadvantaged_pct"),
+            "fsm_pct": _median(sub, "fsm_pct"),
+            "median_pupils": median_pupils,
+        }
+        if with_disadvantaged:
+            block["disadvantaged_rwm_expected_pct"] = _weighted_disadvantaged(sub)
+        return block
+
+    return {
+        "source": "state-school average (computed from our dataset)",
+        "year": int(latest_year),
+        "primary": _block(prim, with_disadvantaged=True),
+        "secondary": _block(sec, with_disadvantaged=False),
+    }
+
+
+def _ofsted_block(o, urn: int) -> dict:
+    """Serialize the latest Ofsted inspection row for API responses.
+
+    `grade_source` records where the effective overall grade came from:
+    a graded (Section 5) inspection, or carried forward from an ungraded
+    (Section 8) outcome — materially different claims a UI must be able
+    to distinguish. `report_card` holds coded+labelled renewed-framework
+    (Nov 2025) area judgements; safeguarding is a separate boolean and
+    never appears among the graded areas.
+    """
+    if o.overall_effectiveness is not None:
+        grade_source = "graded"
+        overall = o.overall_effectiveness
+    elif o.ungraded_grade is not None:
+        # Fall back to the grade parsed from an ungraded (Section 8) outcome
+        # (e.g. "School remains Good") so the detail page matches the list badge.
+        grade_source = "ungraded_carried_forward"
+        overall = o.ungraded_grade
+    else:
+        grade_source = None
+        overall = None
+
+    block = {
        "framework": o.framework,
        "inspection_date": o.inspection_date.isoformat() if o.inspection_date else None,
        "inspection_type": o.inspection_type,
-            # Fall back to the grade parsed from an ungraded (Section 8) outcome
-            # (e.g. "School remains Good") when there's no graded grade, so the
-            # detail page matches the list badge.
-            "overall_effectiveness": (
-                o.overall_effectiveness
-                if o.overall_effectiveness is not None
-                else o.ungraded_grade
-            ),
+        "overall_effectiveness": overall,
+        "grade_source": grade_source,
        "quality_of_education": o.quality_of_education,
        "behaviour_attitudes": o.behaviour_attitudes,
        "personal_development": o.personal_development,
@@ -441,28 +637,14 @@ def get_supplementary_data(db: Session, urn: int) -> dict:
        "rc_early_years": o.rc_early_years,
        "rc_sixth_form": o.rc_sixth_form,
        "report_url": o.report_url,
+        "ofsted_page_url": ofsted_page_url(urn),
    }
-        if o
-        else None
-    )
+    block["report_card"] = report_card_labels(block)
+    return block

-    # Census (latest year of fact_pupil_characteristics)
-    pc = safe_query(FactPupilCharacteristics, "urn", "year")
-    result["census"] = (
-        {
-            "year": pc.year,
-            "total_pupils": pc.total_pupils,
-            "female_pupils": pc.female_pupils,
-            "male_pupils": pc.male_pupils,
-            "fsm_pct": pc.fsm_pct,
-            "eal_pct": pc.eal_pct,
-        }
-        if pc
-        else None
-    )

-    # Admissions — all years, oldest first (for the multi-year trend view).
-    def _admissions_row(a):
+def _admissions_row_dict(a) -> dict:
+    """Serialize one fact_admissions row for API responses."""
    return {
        "year": a.year,
        "school_phase": a.school_phase,
@@ -473,49 +655,35 @@ def get_supplementary_data(db: Session, urn: int) -> dict:
        "first_preference_offer_pct": a.first_preference_offer_pct,
        "oversubscription_ratio": a.oversubscription_ratio,
        "oversubscribed": a.oversubscribed,
+        "total_offers": a.total_offers,
+        "second_preference_offers": a.second_preference_offers,
+        "third_preference_offers": a.third_preference_offers,
+        "cross_la_applications": a.cross_la_applications,
+        "cross_la_offers": a.cross_la_offers,
    }

-    try:
-        admissions_rows = (
-            db.query(FactAdmissions)
-            .filter(FactAdmissions.urn == urn)
-            .order_by(FactAdmissions.year.asc())
-            .all()
-        )
-    except Exception as e:
-        import logging
-        logging.getLogger(__name__).error("admissions history query failed: %s", e)
-        db.rollback()
-        admissions_rows = []

-    history = [_admissions_row(a) for a in admissions_rows]
-    result["admissions_history"] = history
-    # Keep the single latest-year object for backwards-compatible consumers
-    # (hero chips, etc.).
-    result["admissions"] = history[-1] if history else None
+def _census_dict(pc) -> dict:
+    return {
+        "year": pc.year,
+        "total_pupils": pc.total_pupils,
+        "female_pupils": pc.female_pupils,
+        "male_pupils": pc.male_pupils,
+        "fsm_pct": pc.fsm_pct,
+        "eal_pct": pc.eal_pct,
+    }

-    # SEN detail — not available in current marts
-    result["sen_detail"] = None

-    # Phonics — no school-level data on EES
-    result["phonics"] = None
-
-    # Deprivation
-    d = safe_query(FactDeprivation, "urn")
-    result["deprivation"] = (
-        {
+def _deprivation_dict(d) -> dict:
+    return {
        "lsoa_code": d.lsoa_code,
        "idaci_score": d.idaci_score,
        "idaci_decile": d.idaci_decile,
    }
-        if d
-        else None
-    )

-    # Finance (latest year)
-    f = safe_query(FactFinance, "urn", "year")
-    result["finance"] = (
-        {
+
+def _finance_dict(f) -> dict:
+    return {
        "year": f.year,
        "per_pupil_spend": f.per_pupil_spend,
        "staff_cost_pct": f.staff_cost_pct,
@@ -523,8 +691,122 @@ def get_supplementary_data(db: Session, urn: int) -> dict:
        "support_staff_cost_pct": f.support_staff_cost_pct,
        "premises_cost_pct": f.premises_cost_pct,
    }
-        if f
-        else None
+
+
+def _empty_supplementary() -> dict:
+    return {
+        "ofsted": None,
+        "census": None,
+        "admissions": None,
+        "admissions_history": [],
+        "sen_detail": None,
+        "phonics": None,
+        "deprivation": None,
+        "finance": None,
+    }
+
+
+def get_supplementary_data_batch(db: Session, urns: list[int]) -> dict:
+    """Fetch supplementary data for many URNs with one query per table
+    (WHERE urn IN (...)) instead of ~5 queries per school, collapsing the
+    per-request round-trips from 5*N to a constant 5. Returns {urn: block}
+    with the same shape get_supplementary_data produces per URN.
+
+    Each table is queried independently and failures degrade that table to
+    empty for every URN — a missing mart never blanks the others.
+    """
+    urns = [int(u) for u in urns]
+    result = {urn: _empty_supplementary() for urn in urns}
+    if not urns:
+        return result
+
+    def _safe(fn):
+        try:
+            fn()
+        except Exception as e:
+            import logging
+            logging.getLogger(__name__).error("batch supplementary query failed: %s", e)
+            db.rollback()
+
+    # Ofsted — latest inspection per URN. Ordered so the first row seen per
+    # URN is the most recent.
+    def _ofsted():
+        rows = (
+            db.query(FactOfstedInspection)
+            .filter(FactOfstedInspection.urn.in_(urns))
+            .order_by(FactOfstedInspection.urn, FactOfstedInspection.inspection_date.desc())
+            .all()
        )
+        seen = set()
+        for o in rows:
+            if o.urn in seen:
+                continue
+            seen.add(o.urn)
+            result[o.urn]["ofsted"] = _ofsted_block(o, o.urn)
+    _safe(_ofsted)
+
+    # Census — latest year per URN.
+    def _census():
+        rows = (
+            db.query(FactPupilCharacteristics)
+            .filter(FactPupilCharacteristics.urn.in_(urns))
+            .order_by(FactPupilCharacteristics.urn, FactPupilCharacteristics.year.desc())
+            .all()
+        )
+        seen = set()
+        for pc in rows:
+            if pc.urn in seen:
+                continue
+            seen.add(pc.urn)
+            result[pc.urn]["census"] = _census_dict(pc)
+    _safe(_census)
+
+    # Admissions — all years per URN, oldest first (multi-year trend view).
+    def _admissions():
+        rows = (
+            db.query(FactAdmissions)
+            .filter(FactAdmissions.urn.in_(urns))
+            .order_by(FactAdmissions.urn, FactAdmissions.year.asc())
+            .all()
+        )
+        history: dict = {urn: [] for urn in urns}
+        for a in rows:
+            history[a.urn].append(_admissions_row_dict(a))
+        for urn, rows_for_urn in history.items():
+            result[urn]["admissions_history"] = rows_for_urn
+            result[urn]["admissions"] = rows_for_urn[-1] if rows_for_urn else None
+    _safe(_admissions)
+
+    # Deprivation — one row per URN.
+    def _deprivation():
+        rows = (
+            db.query(FactDeprivation)
+            .filter(FactDeprivation.urn.in_(urns))
+            .all()
+        )
+        for d in rows:
+            result[d.urn]["deprivation"] = _deprivation_dict(d)
+    _safe(_deprivation)
+
+    # Finance — latest year per URN.
+    def _finance():
+        rows = (
+            db.query(FactFinance)
+            .filter(FactFinance.urn.in_(urns))
+            .order_by(FactFinance.urn, FactFinance.year.desc())
+            .all()
+        )
+        seen = set()
+        for f in rows:
+            if f.urn in seen:
+                continue
+            seen.add(f.urn)
+            result[f.urn]["finance"] = _finance_dict(f)
+    _safe(_finance)

    return result
+
+
+def get_supplementary_data(db: Session, urn: int) -> dict:
+    """Supplementary data for a single URN (thin wrapper over the batch)."""
+    return get_supplementary_data_batch(db, [urn])[int(urn)]
@@ -0,0 +1,155 @@
+"""GIAS code -> name dictionaries.
+
+GENERATED by pipeline/scripts/generate_gias_codes.py from the GIAS bulk CSV
+— do not edit by hand; rerun the script when the dbt drift test warns.
+The canonical file is backend/gias_codes.py; pipeline/scripts/gias_codes.py
+must be byte-identical (enforced by backend/tests/test_gias_codes.py).
+"""
+
+from __future__ import annotations
+
+import logging
+import math
+
+logger = logging.getLogger(__name__)
+
+
+SCHOOL_TYPE: dict[int, str] = {
+    1: "Community school",
+    2: "Voluntary aided school",
+    3: "Voluntary controlled school",
+    5: "Foundation school",
+    6: "City technology college",
+    7: "Community special school",
+    8: "Non-maintained special school",
+    10: "Other independent special school",
+    11: "Other independent school",
+    12: "Foundation special school",
+    14: "Pupil referral unit",
+    15: "Local authority nursery school",
+    18: "Further education",
+    24: "Secure units",
+    25: "Offshore schools",
+    26: "Service children's education",
+    27: "Miscellaneous",
+    28: "Academy sponsor led",
+    29: "Higher education institutions",
+    30: "Welsh establishment",
+    31: "Sixth form centres",
+    32: "Special post 16 institution",
+    33: "Academy special sponsor led",
+    34: "Academy converter",
+    35: "Free schools",
+    36: "Free schools special",
+    37: "British schools overseas",
+    38: "Free schools alternative provision",
+    39: "Free schools 16 to 19",
+    40: "University technical college",
+    41: "Studio schools",
+    42: "Academy alternative provision converter",
+    43: "Academy alternative provision sponsor led",
+    44: "Academy special converter",
+    45: "Academy 16-19 converter",
+    46: "Academy 16 to 19 sponsor led",
+    49: "Online provider",
+    56: "Institution funded by other government department",
+    57: "Academy secure 16 to 19",
+}
+
+ESTABLISHMENT_STATUS: dict[int, str] = {
+    1: "Open",
+    2: "Closed",
+    3: "Open, but proposed to close",
+    4: "Proposed to open",
+}
+
+PHASE_OF_EDUCATION: dict[int, str] = {
+    0: "Not applicable",
+    1: "Nursery",
+    2: "Primary",
+    3: "Middle deemed primary",
+    4: "Secondary",
+    5: "Middle deemed secondary",
+    6: "16 plus",
+    7: "All-through",
+}
+
+OFFICIAL_SIXTH_FORM: dict[int, str] = {
+    0: "Not applicable",
+    1: "Has a sixth form",
+    2: "Does not have a sixth form",
+    9: "",
+}
+
+RELIGIOUS_CHARACTER: dict[int, str] = {
+    0: "Does not apply",
+    2: "Church of England",
+    3: "Roman Catholic",
+    4: "Methodist",
+    5: "Jewish",
+    6: "None",
+    7: "Muslim",
+    8: "Seventh Day Adventist",
+    9: "Church of England/Methodist",
+    10: "Methodist/Church of England",
+    11: "Church of England/Roman Catholic",
+    12: "Church of England/United Reformed Church",
+    13: "Roman Catholic/Church of England",
+    14: "Quaker",
+    15: "Christian",
+    16: "United Reformed Church",
+    17: "Congregational Church",
+    18: "Free Church",
+    19: "Church of England/Free Church",
+    20: "Church of England/Christian",
+    21: "Sikh",
+    22: "Greek Orthodox",
+    24: "Buddhist",
+    25: "Hindu",
+    26: "Moravian",
+    28: "Inter- / non- denominational",
+    29: "Multi-faith",
+    30: "Church of England/Methodist/United Reform Church/Baptist",
+    31: "Anglican",
+    32: "Anglican/Christian",
+    33: "Anglican/Evangelical",
+    34: "Anglican/Church of England",
+    35: "Catholic",
+    36: "Charadi Jewish",
+    37: "Christian/Evangelical",
+    38: "Christian Science",
+    39: "Christian/Methodist",
+    40: "Christian/non-denominational",
+    41: "Church of England/Evangelical",
+    42: "Islam",
+    43: "Orthodox Jewish",
+    44: "Plymouth Brethren Christian Church",
+    45: "Protestant",
+    46: "Protestant/Evangelical",
+    47: "Reformed Baptist",
+    48: "Roman Catholic/Anglican",
+    49: "Sunni Deobandi",
+    99: "",
+}
+
+ADMISSIONS_POLICY: dict[int, str] = {
+    0: "Not applicable",
+    2: "Selective",
+    4: "Non-selective",
+    9: "",
+}
+
+
+def translate(code, mapping: dict[int, str]) -> str | None:
+    """Translate a GIAS code to its display name.
+
+    None/NaN -> None (column absent or suppressed). Unknown codes degrade to
+    "Unknown (<code>)" with a warning so a new DfE value never blanks the UI.
+    """
+    if code is None or (isinstance(code, float) and math.isnan(code)):
+        return None
+    code = int(code)
+    if code not in mapping:
+        logger.warning("Unknown GIAS code %s (not in dictionary)", code)
+        return f"Unknown ({code})"
+    return mapping[code]
@@ -17,21 +17,22 @@ class DimSchool(Base):

    urn = Column(Integer, primary_key=True)
    school_name = Column(String(255), nullable=False)
-    phase = Column(String(100))
-    school_type = Column(String(100))
+    phase_code = Column(Integer)
+    school_type_code = Column(Integer)
    academy_trust_name = Column(String(255))
    academy_trust_uid = Column(String(20))
-    religious_character = Column(String(100))
+    religious_character_code = Column(Integer)
    gender = Column(String(20))
    age_range = Column(String(20))
+    has_sixth_form = Column(Boolean)
    capacity = Column(Integer)
    total_pupils = Column(Integer)
    headteacher_name = Column(String(200))
    website = Column(String(255))
    telephone = Column(String(30))
-    status = Column(String(50))
+    status_code = Column(Integer)
    nursery_provision = Column(Boolean)
-    admissions_policy = Column(String(50))
+    admissions_policy_code = Column(Integer)
    # Denormalised Ofsted summary (updated by monthly pipeline)
    ofsted_grade = Column(Integer)
    ofsted_date = Column(Date)
@@ -87,6 +88,15 @@ class KS2Performance(Base):
    maths_high_pct = Column(Float)
    maths_avg_score = Column(Float)
    maths_progress = Column(Float)
+    # Progress confidence intervals + writing working-towards (published
+    # for years with progress measures, i.e. up to 2022/23)
+    reading_progress_lower_ci = Column(Float)
+    reading_progress_upper_ci = Column(Float)
+    writing_progress_lower_ci = Column(Float)
+    writing_progress_upper_ci = Column(Float)
+    writing_working_towards_pct = Column(Float)
+    maths_progress_lower_ci = Column(Float)
+    maths_progress_upper_ci = Column(Float)
    gps_expected_pct = Column(Float)
    gps_high_pct = Column(Float)
    gps_avg_score = Column(Float)
@@ -164,6 +174,11 @@ class FactAdmissions(Base):
    total_applications = Column(Integer)
    first_preference_applications = Column(Integer)
    first_preference_offers = Column(Integer)
+    total_offers = Column(Integer)
+    second_preference_offers = Column(Integer)
+    third_preference_offers = Column(Integer)
+    cross_la_applications = Column(Integer)
+    cross_la_offers = Column(Integer)
    first_preference_offer_pct = Column(Float)
    oversubscription_ratio = Column(Float)
    oversubscribed = Column(Boolean)
@@ -216,6 +231,23 @@ class FactFinance(Base):
    premises_cost_pct = Column(Float)


+class Ks4NationalAverage(Base):
+    """Computed national KS4 averages (from our dataset) — one row per year."""
+    __tablename__ = "fact_ks4_national_averages"
+    __table_args__ = MARTS
+
+    year = Column(Integer, primary_key=True)
+    attainment_8_score = Column(Float)
+    progress_8_score = Column(Float)
+    english_maths_standard_pass_pct = Column(Float)
+    english_maths_strong_pass_pct = Column(Float)
+    ebacc_entry_pct = Column(Float)
+    ebacc_standard_pass_pct = Column(Float)
+    ebacc_strong_pass_pct = Column(Float)
+    ebacc_avg_score = Column(Float)
+    gcse_grade_91_pct = Column(Float)
+
+
 class Ks2NationalAverage(Base):
    """Official DfE KS2 national headline averages — one row per academic year."""
    __tablename__ = "fact_ks2_national_averages"
@@ -0,0 +1,44 @@
+"""Ofsted renewed-framework (Nov 2025) report-card code translation.
+
+Scale labels are the live-sampled vocabulary from the Ofsted MI file
+(see pipeline/scripts/diagnose_compare_gaps.py, TASK 7 VALUE SAMPLE) —
+verified against real data, not the consultation draft.
+"""
+
+REPORT_CARD_GRADE_NAMES = {
+    1: "Exceptional",
+    2: "Strong standard",
+    3: "Expected standard",
+    4: "Needs attention",
+    5: "Urgent improvement",
+}
+
+# Graded evaluation areas only — safeguarding is a separate boolean
+# judgement and must never appear in grade counts or label maps.
+_RC_AREA_KEYS = (
+    "rc_inclusion",
+    "rc_curriculum_teaching",
+    "rc_achievement",
+    "rc_attendance_behaviour",
+    "rc_personal_development",
+    "rc_leadership_governance",
+    "rc_early_years",
+    "rc_sixth_form",
+)
+
+
+def report_card_labels(ofsted: dict) -> dict:
+    """{area_key: {code, label}} for populated, known-valued rc_* areas."""
+    out = {}
+    for key in _RC_AREA_KEYS:
+        code = ofsted.get(key)
+        label = REPORT_CARD_GRADE_NAMES.get(code)
+        if code is not None and label is not None:
+            out[key] = {"code": code, "label": label}
+    return out
+
+
+def ofsted_page_url(urn: int) -> str:
+    """The school's page on ofsted.gov.uk (all its reports live there —
+    we never deep-link an individual report)."""
+    return f"https://reports.ofsted.gov.uk/provider/21/{urn}"
@@ -543,6 +543,8 @@ SCHOOL_COLUMNS = [
    "postcode",
    "religious_denomination",
    "age_range",
+    "has_sixth_form",
+    "status",
    "gender",
    "admissions_policy",
    "ofsted_grade",
@@ -0,0 +1,81 @@
+"""compute_benchmarks: state-school benchmarks computed from our dataset
+(spec §5/§8.6). The disadvantaged average must be weighted by cohort size,
+medians must ignore NaN, and only the latest year counts."""
+
+import numpy as np
+import pandas as pd
+
+from backend.data_loader import compute_benchmarks
+
+LATEST = 202425
+
+
+def _df():
+    rows = [
+        # Six primary schools, latest year. Disadvantaged RWM chosen so the
+        # weighted average differs clearly from the unweighted mean:
+        # weighted = (40*100 + 60*300) / 400 = 55.0 ; unweighted mean = 50.0
+        dict(year=LATEST, attainment_8_score=np.nan, eligible_pupils=100,
+             rwm_expected_disadvantaged_pct=40.0, eal_pct=10.0,
+             sen_support_pct=10.0, disadvantaged_pct=20.0, fsm_pct=15.0, total_pupils=200),
+        dict(year=LATEST, attainment_8_score=np.nan, eligible_pupils=300,
+             rwm_expected_disadvantaged_pct=60.0, eal_pct=20.0,
+             sen_support_pct=14.0, disadvantaged_pct=24.0, fsm_pct=17.0, total_pupils=280),
+        dict(year=LATEST, attainment_8_score=np.nan, eligible_pupils=np.nan,
+             rwm_expected_disadvantaged_pct=99.0, eal_pct=30.0,
+             sen_support_pct=18.0, disadvantaged_pct=30.0, fsm_pct=19.0, total_pupils=300),
+        dict(year=LATEST, attainment_8_score=np.nan, eligible_pupils=50,
+             rwm_expected_disadvantaged_pct=np.nan, eal_pct=np.nan,
+             sen_support_pct=np.nan, disadvantaged_pct=np.nan, fsm_pct=np.nan, total_pupils=np.nan),
+        dict(year=LATEST, attainment_8_score=np.nan, eligible_pupils=40,
+             rwm_expected_disadvantaged_pct=np.nan, eal_pct=40.0,
+             sen_support_pct=20.0, disadvantaged_pct=40.0, fsm_pct=21.0, total_pupils=350),
+        dict(year=LATEST, attainment_8_score=np.nan, eligible_pupils=60,
+             rwm_expected_disadvantaged_pct=np.nan, eal_pct=50.0,
+             sen_support_pct=22.0, disadvantaged_pct=44.0, fsm_pct=23.0, total_pupils=400),
+        # Two secondary schools (attainment_8 non-null)
+        dict(year=LATEST, attainment_8_score=45.0, eligible_pupils=180,
+             rwm_expected_disadvantaged_pct=np.nan, eal_pct=15.0,
+             sen_support_pct=12.0, disadvantaged_pct=22.0, fsm_pct=12.0, total_pupils=1000),
+        dict(year=LATEST, attainment_8_score=50.0, eligible_pupils=200,
+             rwm_expected_disadvantaged_pct=np.nan, eal_pct=25.0,
+             sen_support_pct=16.0, disadvantaged_pct=26.0, fsm_pct=14.0, total_pupils=1200),
+        # An older-year primary row that must NOT influence anything
+        dict(year=202324, attainment_8_score=np.nan, eligible_pupils=500,
+             rwm_expected_disadvantaged_pct=1.0, eal_pct=99.0,
+             sen_support_pct=99.0, disadvantaged_pct=99.0, fsm_pct=99.0, total_pupils=9999),
+    ]
+    return pd.DataFrame(rows)
+
+
+def test_weighted_disadvantaged_average():
+    b = compute_benchmarks(_df())
+    # Row 3 has NaN eligible_pupils and must be excluded from the weighting.
+    assert b["primary"]["disadvantaged_rwm_expected_pct"] == 55.0
+
+
+def test_medians_ignore_nan_and_older_years():
+    b = compute_benchmarks(_df())
+    assert b["year"] == LATEST
+    # eal medians over [10,20,30,40,50] = 30
+    assert b["primary"]["eal_pct"] == 30.0
+    # fsm medians over [15,17,19,21,23] = 19
+    assert b["primary"]["fsm_pct"] == 19.0
+    # median pupils over [200,280,300,350,400] = 300
+    assert b["primary"]["median_pupils"] == 300
+
+
+def test_secondary_block_has_no_disadvantaged_rwm():
+    b = compute_benchmarks(_df())
+    assert "disadvantaged_rwm_expected_pct" not in b["secondary"]
+    assert b["secondary"]["fsm_pct"] == 13.0
+    assert b["secondary"]["median_pupils"] == 1100
+
+
+def test_provenance_string():
+    b = compute_benchmarks(_df())
+    assert b["source"] == "state-school average (computed from our dataset)"
+
+
+def test_empty_df():
+    assert compute_benchmarks(pd.DataFrame()) == {}
@@ -0,0 +1,123 @@
+"""/api/compare enrichment for the compare redesign: per-school
+supplementary blocks, top-level national_averages (shared with the
+/api/national-averages endpoint) and computed benchmarks — all additive."""
+
+import types
+
+import numpy as np
+import pandas as pd
+import pytest
+from fastapi.testclient import TestClient
+
+LATEST = 202425
+
+CANNED_SUPPLEMENTARY = {
+    "ofsted": {"overall_effectiveness": 2, "grade_source": "graded",
+               "report_card": {}, "ofsted_page_url": "https://reports.ofsted.gov.uk/provider/21/100140"},
+    "census": {"year": 202526, "fsm_pct": 29.8},
+    "admissions": {"year": 202627, "second_preference_offers": 4},
+    "admissions_history": [{"year": 202627, "second_preference_offers": 4}],
+    "sen_detail": None,
+    "phonics": None,
+    "deprivation": {"idaci_decile": 4},
+    "finance": None,
+}
+
+
+def _two_primary_schools_df() -> pd.DataFrame:
+    rows = []
+    for urn, name, rwm, dis in ((100140, "Plumcroft Primary School", 79.0, 72.0),
+                                (138690, "Barclay Primary School", 87.0, 86.0)):
+        rows.append(dict(
+            urn=urn, school_name=name, local_authority="Greenwich",
+            school_type="Community school", address="1 Road", phase="Primary",
+            year=LATEST, rwm_expected_pct=rwm, attainment_8_score=np.nan,
+            eligible_pupils=60, rwm_expected_disadvantaged_pct=dis,
+            eal_pct=20.0, sen_support_pct=14.0, disadvantaged_pct=25.0,
+            total_pupils=1000.0,
+        ))
+    return pd.DataFrame(rows)
+
+
+class _StubNatRow:
+    year = 202425
+    rwm_expected_pct = 62.1
+    gps_expected_pct = 72.0
+    science_expected_pct = 81.0
+
+
+class _StubSession:
+    def query(self, *a, **k):
+        return self
+
+    def order_by(self, *a, **k):
+        return self
+
+    def all(self):
+        return [_StubNatRow()]
+
+    def close(self):
+        pass
+
+
+@pytest.fixture()
+def client(monkeypatch):
+    from backend import app as app_module
+    from backend import database as database_module
+
+    monkeypatch.setattr(app_module, "load_school_data", _two_primary_schools_df)
+    monkeypatch.setattr(
+        app_module,
+        "get_supplementary_data_batch",
+        lambda db, urns: {int(u): dict(CANNED_SUPPLEMENTARY) for u in urns},
+    )
+    monkeypatch.setattr(database_module, "SessionLocal", _StubSession)
+    return TestClient(app_module.app, raise_server_exceptions=False)
+
+
+def test_existing_shape_is_preserved(client):
+    body = client.get("/api/compare?urns=100140,138690").json()
+    school = body["comparison"]["100140"]
+    assert school["school_info"]["rwm_expected_pct"] == 79.0
+    assert school["yearly_data"][0]["year"] == LATEST
+
+
+def test_each_school_gains_supplementary_blocks(client):
+    body = client.get("/api/compare?urns=100140,138690").json()
+    for urn in ("100140", "138690"):
+        school = body["comparison"][urn]
+        assert school["ofsted"]["grade_source"] == "graded"
+        assert school["census"]["fsm_pct"] == 29.8
+        assert school["admissions"]["second_preference_offers"] == 4
+        assert school["admissions_history"][0]["year"] == 202627
+        assert school["deprivation"]["idaci_decile"] == 4
+
+
+def test_top_level_national_averages_and_benchmarks(client):
+    body = client.get("/api/compare?urns=100140,138690").json()
+    assert body["national_averages"]["year"] == LATEST
+    assert body["benchmarks"]["source"] == "state-school average (computed from our dataset)"
+    # weighted over equal cohorts of 72 and 86 = 79.0
+    assert body["benchmarks"]["primary"]["disadvantaged_rwm_expected_pct"] == 79.0
+
+
+def test_supplementary_failure_degrades_not_500(client, monkeypatch):
+    from backend import app as app_module
+
+    def _boom(db, urns):
+        raise RuntimeError("marts unavailable")
+
+    monkeypatch.setattr(app_module, "get_supplementary_data_batch", _boom)
+    resp = client.get("/api/compare?urns=100140")
+    assert resp.status_code == 200
+    school = resp.json()["comparison"]["100140"]
+    assert school["ofsted"] is None
+    assert school["admissions_history"] == []
+
+
+def test_national_averages_endpoint_exposes_gps_science(client):
+    body = client.get("/api/national-averages").json()
+    latest_primary_by_year = [e["primary"] for e in body["by_year"] if e["primary"]]
+    assert latest_primary_by_year, "expected official by_year rows from the stub"
+    assert latest_primary_by_year[-1]["gps_expected_pct"] == 72.0
+    assert latest_primary_by_year[-1]["science_expected_pct"] == 81.0
@@ -0,0 +1,95 @@
+"""Tests for the GIAS code->name dictionaries (spec 2026-07-09).
+
+The dictionaries are generated from the live GIAS bulk CSV by
+pipeline/scripts/generate_gias_codes.py — these tests assert the module's
+contract, key sentinel values the marts/UI depend on, and that the pipeline
+copy has not drifted from the canonical backend module.
+"""
+
+import math
+from pathlib import Path
+
+from backend.gias_codes import (
+    ADMISSIONS_POLICY,
+    ESTABLISHMENT_STATUS,
+    OFFICIAL_SIXTH_FORM,
+    PHASE_OF_EDUCATION,
+    RELIGIOUS_CHARACTER,
+    SCHOOL_TYPE,
+    translate,
+)
+
+REPO = Path(__file__).resolve().parents[2]
+
+
+def test_translate_known_code():
+    open_code = next(c for c, n in ESTABLISHMENT_STATUS.items() if n == "Open")
+    assert translate(open_code, ESTABLISHMENT_STATUS) == "Open"
+
+
+def test_translate_unknown_code_degrades_gracefully():
+    assert translate(9999, ESTABLISHMENT_STATUS) == "Unknown (9999)"
+
+
+def test_translate_none_and_nan_return_none():
+    assert translate(None, ESTABLISHMENT_STATUS) is None
+    assert translate(float("nan"), ESTABLISHMENT_STATUS) is None
+
+
+def test_translate_accepts_float_codes():
+    # pd.read_sql yields float columns when NULLs are present
+    open_code = next(c for c, n in ESTABLISHMENT_STATUS.items() if n == "Open")
+    assert translate(float(open_code), ESTABLISHMENT_STATUS) == "Open"
+
+
+def test_sentinel_names_present():
+    """Names the marts/UI compare against must exist verbatim."""
+    assert "Open" in ESTABLISHMENT_STATUS.values()
+    assert "Open, but proposed to close" in ESTABLISHMENT_STATUS.values()
+    assert "Has a sixth form" in OFFICIAL_SIXTH_FORM.values()
+    assert "Primary" in PHASE_OF_EDUCATION.values()
+    assert "Secondary" in PHASE_OF_EDUCATION.values()
+    assert "Does not apply" in RELIGIOUS_CHARACTER.values()
+    assert all(len(d) > 0 for d in (
+        SCHOOL_TYPE, ESTABLISHMENT_STATUS, PHASE_OF_EDUCATION,
+        OFFICIAL_SIXTH_FORM, RELIGIOUS_CHARACTER, ADMISSIONS_POLICY,
+    ))
+
+
+def test_pipeline_copy_is_identical():
+    canonical = (REPO / "backend" / "gias_codes.py").read_text()
+    copy = (REPO / "pipeline" / "scripts" / "gias_codes.py").read_text()
+    assert canonical == copy, (
+        "pipeline/scripts/gias_codes.py has drifted from backend/gias_codes.py — "
+        "regenerate with pipeline/scripts/generate_gias_codes.py and copy the file"
+    )
+
+
+def test_seed_matches_dictionaries():
+    import csv
+    fields = {
+        "school_type": SCHOOL_TYPE,
+        "establishment_status": ESTABLISHMENT_STATUS,
+        "phase_of_education": PHASE_OF_EDUCATION,
+        "official_sixth_form": OFFICIAL_SIXTH_FORM,
+        "religious_character": RELIGIOUS_CHARACTER,
+        "admissions_policy": ADMISSIONS_POLICY,
+    }
+    seed_path = REPO / "pipeline" / "transform" / "seeds" / "gias_code_names.csv"
+    seed: dict[str, dict[int, str]] = {k: {} for k in fields}
+    with open(seed_path, newline="") as fh:
+        for row in csv.DictReader(fh):
+            seed[row["field"]][int(row["code"])] = row["name"]
+    assert seed == fields
+
+
+def test_blank_name_sentinel_codes_map_to_empty_string():
+    """GIAS carries codes whose (name) column is blank — e.g. ReligiousCharacter
+    99 (~4k schools) and AdmissionsPolicy 9 (~5.6k schools). The old name
+    pipeline served these as empty strings; the dictionaries must reproduce
+    that ("" is falsy, so UI tag heuristics stay silent) rather than letting
+    them hit the "Unknown (<code>)" path meant for genuinely new codes."""
+    assert RELIGIOUS_CHARACTER[99] == ""
+    assert ADMISSIONS_POLICY[9] == ""
+    assert translate(99, RELIGIOUS_CHARACTER) == ""
+    assert translate(9, ADMISSIONS_POLICY) == ""
@@ -0,0 +1,132 @@
+"""API-boundary translation: marts now carry GIAS codes; the DataFrame the
+rest of the backend sees must carry today's name strings."""
+
+import numpy as np
+import pandas as pd
+
+from backend.data_loader import _missing_column_name, translate_gias_code_columns
+from backend.gias_codes import ESTABLISHMENT_STATUS, PHASE_OF_EDUCATION
+
+
+def _code_for(mapping, name):
+    return next(c for c, n in mapping.items() if n == name)
+
+
+def test_codes_become_todays_names():
+    df = pd.DataFrame([{
+        "urn": 1,
+        "phase_code": float(_code_for(PHASE_OF_EDUCATION, "Primary")),
+        "school_type_code": np.nan,
+        "status_code": float(_code_for(ESTABLISHMENT_STATUS, "Open, but proposed to close")),
+        "religious_character_code": np.nan,
+        "admissions_policy_code": np.nan,
+    }])
+    out = translate_gias_code_columns(df)
+    row = out.iloc[0]
+    assert row["phase"] == "Primary"
+    assert row["status"] == "Open, but proposed to close"
+    assert row["school_type"] is None
+    assert row["religious_denomination"] is None
+    assert row["admissions_policy"] is None
+
+
+def test_unknown_code_degrades_not_blanks():
+    df = pd.DataFrame([{"urn": 1, "phase_code": 9999.0}])
+    out = translate_gias_code_columns(df)
+    assert out.iloc[0]["phase"] == "Unknown (9999)"
+
+
+def test_missing_code_columns_are_a_noop():
+    """Old-schema DataFrames (tests, pre-pipeline DBs) pass through untouched."""
+    df = pd.DataFrame([{"urn": 1, "phase": "Primary", "status": "Open"}])
+    out = translate_gias_code_columns(df)
+    assert out.iloc[0]["phase"] == "Primary"
+    assert out.iloc[0]["status"] == "Open"
+
+
+def _fake_exc(orig_message):
+    """A stand-in for sqlalchemy.exc.ProgrammingError: str(exc) embeds the
+    full SQL statement (deliberately containing every column name below, to
+    prove the matcher doesn't fall back to it), while .orig carries the real
+    DBAPI error message naming only the offending column."""
+    exc = Exception(
+        "SELECT s.phase_code, s.school_type_code, s.religious_character_code, "
+        "s.status_code, s.admissions_policy_code, s.has_sixth_form FROM ... "
+        f"[SQL: ...] (Background on this error at: https://...)"
+    )
+    exc.orig = Exception(orig_message) if orig_message is not None else None
+    return exc
+
+
+def test_missing_column_name_quoted():
+    assert _missing_column_name(_fake_exc('column "phase_code" does not exist')) == "phase_code"
+
+
+def test_missing_column_name_unquoted():
+    assert _missing_column_name(_fake_exc("column phase_code does not exist")) == "phase_code"
+
+
+def test_missing_column_name_table_prefixed():
+    assert (
+        _missing_column_name(_fake_exc("column s.has_sixth_form does not exist"))
+        == "has_sixth_form"
+    )
+
+
+def test_missing_column_name_no_match_returns_none():
+    assert _missing_column_name(_fake_exc("relation \"marts.dim_school\" does not exist")) is None
+
+
+def test_load_school_data_survives_premigration_marts(monkeypatch):
+    """Real prod state until the nightly pipeline first rebuilds the mart with
+    the GIAS code columns: marts.dim_school still has the old name columns
+    (phase, school_type, religious_character, status, admissions_policy)
+    instead of the new *_code columns. The first query raises UndefinedColumn
+    on s.phase_code; load_school_data_as_dataframe must retry with the
+    legacy name-column query rather than swallow the error and return (and
+    then have load_school_data cache) an empty DataFrame."""
+    import sqlalchemy.exc
+    from backend import data_loader
+
+    data_loader._df_cache = None
+    data_loader._df_latest_cache = None
+
+    good_df = pd.DataFrame(
+        [
+            {
+                "urn": 1,
+                "school_name": "Legacy School",
+                "phase": "Primary",
+                "school_type": "Academy",
+                "status": "Open",
+            }
+        ]
+    )
+    calls = []
+
+    def fake_read_sql(query, con):
+        calls.append(query)
+        if len(calls) == 1:
+            raise sqlalchemy.exc.ProgrammingError(
+                statement=str(data_loader._MAIN_QUERY),
+                params=None,
+                orig=Exception(
+                    "(psycopg2.errors.UndefinedColumn) column s.phase_code "
+                    "does not exist\nLINE 5:         s.phase_code,"
+                ),
+            )
+        return good_df.copy()
+
+    monkeypatch.setattr(data_loader.pd, "read_sql", fake_read_sql)
+
+    try:
+        df = data_loader.load_school_data_as_dataframe()
+    finally:
+        data_loader._df_cache = None
+        data_loader._df_latest_cache = None
+
+    assert len(calls) == 2, "must retry with the legacy name-column query variant"
+    assert calls[1] is data_loader._MAIN_QUERY_LEGACY_NAMES
+    assert not df.empty
+    assert df["phase"].iloc[0] == "Primary"
+    assert df["status"].iloc[0] == "Open"
@@ -0,0 +1,93 @@
+"""_national_averages_payload reads persisted marts (computed at import
+time) — it must never loop the dataframe per year. The only dataframe work
+allowed is the single-latest-year KS4 fallback for the window between a
+deploy and the next DAG run."""
+
+import numpy as np
+import pandas as pd
+import pytest
+
+LATEST = 202425
+
+
+def _df():
+    return pd.DataFrame(
+        [
+            dict(year=202324, attainment_8_score=40.0, rwm_expected_pct=np.nan),
+            dict(year=LATEST, attainment_8_score=50.0, rwm_expected_pct=np.nan),
+            dict(year=LATEST, attainment_8_score=30.0, rwm_expected_pct=np.nan),
+            dict(year=LATEST, attainment_8_score=np.nan, rwm_expected_pct=80.0),
+        ]
+    )
+
+
+class _Ks2Row:
+    year = LATEST
+    rwm_expected_pct = 62.1
+    gps_expected_pct = 72.0
+
+
+class _Ks4Row:
+    year = LATEST
+    attainment_8_score = 46.5
+    progress_8_score = -0.02
+
+
+class _StubSession:
+    """Returns KS2 rows for the first query and KS4 rows for the second —
+    mirroring the payload's query order."""
+
+    def __init__(self):
+        self.calls = 0
+
+    def query(self, model):
+        self._model = model.__name__
+        return self
+
+    def order_by(self, *a):
+        return self
+
+    def all(self):
+        return [_Ks2Row()] if self._model == "Ks2NationalAverage" else [_Ks4Row()]
+
+    def close(self):
+        pass
+
+
+class _Ks4MissingSession(_StubSession):
+    def all(self):
+        if self._model == "Ks4NationalAverage":
+            raise RuntimeError("relation does not exist")
+        return [_Ks2Row()]
+
+    def rollback(self):
+        pass
+
+
+@pytest.fixture()
+def payload(monkeypatch):
+    from backend import app as app_module
+    from backend import database as database_module
+
+    def _run(session_cls):
+        monkeypatch.setattr(database_module, "SessionLocal", session_cls)
+        return app_module._national_averages_payload(_df())
+
+    return _run
+
+
+def test_ks4_averages_come_from_the_mart_not_the_dataframe(payload):
+    body = payload(_StubSession)
+    # Mart value (46.5), NOT the dataframe mean of (50+30)/2 = 40.0
+    assert body["secondary"]["attainment_8_score"] == 46.5
+    assert body["primary"]["rwm_expected_pct"] == 62.1
+    assert body["by_year"][-1]["secondary"]["progress_8_score"] == -0.02
+
+
+def test_missing_ks4_mart_falls_back_to_latest_year_only(payload):
+    body = payload(_Ks4MissingSession)
+    # Fallback computes the latest year from the df: mean(50, 30) = 40.0
+    assert body["secondary"]["attainment_8_score"] == 40.0
+    # ...and only the latest year — no historical KS4 loop
+    ks4_years = [e["year"] for e in body["by_year"] if e["secondary"]]
+    assert ks4_years == [LATEST]
@@ -0,0 +1,45 @@
+"""Report-card code translation uses the live-sampled Ofsted vocabulary
+(pipeline/scripts/diagnose_compare_gaps.py, TASK 7 VALUE SAMPLE):
+Exceptional / Strong standard / Expected standard / Needs attention /
+Urgent improvement — never the consultation draft's 'Attention needed'."""
+
+from backend.ofsted_codes import (
+    REPORT_CARD_GRADE_NAMES,
+    ofsted_page_url,
+    report_card_labels,
+)
+
+
+def test_scale_is_sampled_vocabulary():
+    assert REPORT_CARD_GRADE_NAMES == {
+        1: "Exceptional",
+        2: "Strong standard",
+        3: "Expected standard",
+        4: "Needs attention",
+        5: "Urgent improvement",
+    }
+
+
+def test_labels_only_for_populated_areas_and_never_safeguarding():
+    ofsted = {
+        "rc_achievement": 2,
+        "rc_inclusion": 3,
+        "rc_attendance_behaviour": 4,
+        "rc_early_years": None,
+        "rc_safeguarding_met": True,
+        "overall_effectiveness": None,
+    }
+    labels = report_card_labels(ofsted)
+    assert labels == {
+        "rc_achievement": {"code": 2, "label": "Strong standard"},
+        "rc_inclusion": {"code": 3, "label": "Expected standard"},
+        "rc_attendance_behaviour": {"code": 4, "label": "Needs attention"},
+    }
+
+
+def test_unknown_code_is_skipped_not_crashed():
+    assert report_card_labels({"rc_achievement": 9}) == {}
+
+
+def test_provider_url():
+    assert ofsted_page_url(138690) == "https://reports.ofsted.gov.uk/provider/21/138690"
@@ -0,0 +1,71 @@
+"""Regression tests for GET /api/schools/{urn}.
+
+Schools with no performance rows (special post-16 institutions, sixth-form
+centres, PRUs, brand-new schools) come back from the marts LEFT JOIN with
+NaN in every numeric column. The endpoint must still serialize them — a NaN
+that reaches Starlette's JSONResponse raises ValueError (allow_nan=False)
+and the route 500s, which the frontend then renders as a 404.
+"""
+
+import numpy as np
+import pandas as pd
+import pytest
+from fastapi.testclient import TestClient
+
+
+def _no_results_school_df() -> pd.DataFrame:
+    """One school row as produced by the marts query for a school with no
+    performance data: GIAS/location fields partly populated, every
+    results-linked column NaN (including year)."""
+    return pd.DataFrame(
+        [
+            {
+                "urn": 150275,
+                "school_name": "West London Performing Arts Academy",
+                "phase": "Secondary",
+                "school_type": "Special post 16 institution",
+                "trust_name": None,
+                "religious_denomination": "Does not apply",
+                "gender": None,
+                "age_range": "16-25",
+                "admissions_policy": None,
+                "capacity": np.nan,
+                "gias_total_pupils": np.nan,
+                "headteacher_name": None,
+                "website": None,
+                "ofsted_grade": np.nan,
+                "local_authority": "Ealing",
+                "address": "268 Northfield Avenue, London, W5 4UB",
+                "postcode": "W5 4UB",
+                "latitude": 51.4986,
+                "longitude": -0.3148,
+                "year": np.nan,
+                "total_pupils": np.nan,
+                "eligible_pupils": np.nan,
+                "rwm_expected_pct": np.nan,
+            }
+        ]
+    )
+
+
+@pytest.fixture()
+def client(monkeypatch):
+    from backend import app as app_module
+
+    monkeypatch.setattr(app_module, "load_school_data", _no_results_school_df)
+    monkeypatch.setattr(
+        app_module, "get_supplementary_data", lambda db, urn: {}
+    )
+    return TestClient(app_module.app, raise_server_exceptions=False)
+
+
+def test_school_without_performance_rows_returns_200(client):
+    resp = client.get("/api/schools/150275")
+    assert resp.status_code == 200, resp.text
+
+
+def test_nan_gias_fields_serialize_as_null(client):
+    info = client.get("/api/schools/150275").json()["school_info"]
+    assert info["capacity"] is None
+    assert info["total_pupils"] is None
+    assert info["school_name"] == "West London Performing Arts Academy"
@@ -0,0 +1,70 @@
+"""Tests for GIAS establishment status exposure.
+
+"Open, but proposed to close" schools are now kept by the dims; the API must
+surface `status` on list items and school_info so the UI can render the
+proposed-to-close marker (listing tag) and notice strip (detail page).
+"""
+
+import numpy as np
+import pandas as pd
+import pytest
+from fastapi.testclient import TestClient
+
+PROPOSED = "Open, but proposed to close"
+
+
+def _schools_df() -> pd.DataFrame:
+    base = {
+        "local_authority": "Testshire",
+        "school_type": "Academy",
+        "phase": "Secondary",
+        "address": "1 Test Street",
+        "town": "Testtown",
+        "postcode": "TS1 1AA",
+        "religious_denomination": None,
+        "gender": "Mixed",
+        "age_range": "11-16",
+        "admissions_policy": None,
+        "has_sixth_form": False,
+        "ofsted_grade": np.nan,
+        "ofsted_date": None,
+        "ofsted_framework": None,
+        "latitude": 51.5,
+        "longitude": -0.1,
+        "year": 202425,
+        "total_pupils": 800,
+        "rwm_expected_pct": np.nan,
+        "attainment_8_score": 48.0,
+    }
+    return pd.DataFrame(
+        [
+            {**base, "urn": 200001, "school_name": "Alpha Academy",
+             "status": "Open"},
+            {**base, "urn": 200002, "school_name": "Sarson High School",
+             "status": PROPOSED},
+        ]
+    )
+
+
+@pytest.fixture()
+def client(monkeypatch):
+    from backend import app as app_module
+
+    monkeypatch.setattr(app_module, "load_latest_school_data", _schools_df)
+    monkeypatch.setattr(app_module, "load_school_data", _schools_df)
+    monkeypatch.setattr(app_module, "get_supplementary_data", lambda db, urn: {})
+    return TestClient(app_module.app, raise_server_exceptions=False)
+
+
+def test_list_payload_includes_status(client):
+    resp = client.get("/api/schools")
+    assert resp.status_code == 200, resp.text
+    by_urn = {s["urn"]: s for s in resp.json()["schools"]}
+    assert by_urn[200001]["status"] == "Open"
+    assert by_urn[200002]["status"] == PROPOSED
+
+
+def test_detail_payload_includes_status(client):
+    resp = client.get("/api/schools/200002")
+    assert resp.status_code == 200, resp.text
+    assert resp.json()["school_info"]["status"] == PROPOSED
@@ -0,0 +1,177 @@
+"""Tests for the GIAS-driven has_sixth_form flag (spec 2026-07-07 §3).
+
+The filter and payloads must use dim_school.has_sixth_form, not the old
+age_range-contains-"18" substring heuristic. The key regression case is a
+16-19 sixth-form college: flag true, but "16-19" contains no "18".
+"""
+
+import numpy as np
+import pandas as pd
+import pytest
+from fastapi.testclient import TestClient
+
+
+def _schools_df() -> pd.DataFrame:
+    """Latest-year snapshot rows as produced by load_latest_school_data."""
+    base = {
+        "local_authority": "Testshire",
+        "school_type": "Academy",
+        "phase": "Secondary",
+        "address": "1 Test Street",
+        "town": "Testtown",
+        "postcode": "TS1 1AA",
+        "religious_denomination": None,
+        "gender": "Mixed",
+        "admissions_policy": None,
+        "ofsted_grade": np.nan,
+        "ofsted_date": None,
+        "ofsted_framework": None,
+        "latitude": 51.5,
+        "longitude": -0.1,
+        "year": 202425,
+        "total_pupils": 1000,
+        "rwm_expected_pct": np.nan,
+        "attainment_8_score": 50.0,
+    }
+    return pd.DataFrame(
+        [
+            # 11-18 school WITH a registered sixth form
+            {**base, "urn": 100001, "school_name": "Alpha High",
+             "age_range": "11-18", "has_sixth_form": True},
+            # 16-19 college: old heuristic said NO ("16-19" has no "18"),
+            # GIAS flag says YES — must appear in the yes-filter results
+            {**base, "urn": 100002, "school_name": "Beta Sixth Form College",
+             "age_range": "16-19", "has_sixth_form": True},
+            # 11-18 age range on paper but NO registered sixth form:
+            # old heuristic said YES, GIAS flag says NO
+            {**base, "urn": 100003, "school_name": "Gamma Academy",
+             "age_range": "11-18", "has_sixth_form": False},
+            # Missing flag (pipeline not yet re-run) — must not crash,
+            # must not match the yes-filter
+            {**base, "urn": 100004, "school_name": "Delta School",
+             "age_range": "11-16", "has_sixth_form": None},
+        ]
+    )
+
+
+@pytest.fixture()
+def client(monkeypatch):
+    from backend import app as app_module
+
+    monkeypatch.setattr(app_module, "load_latest_school_data", _schools_df)
+    monkeypatch.setattr(app_module, "load_school_data", _schools_df)
+    monkeypatch.setattr(app_module, "get_supplementary_data", lambda db, urn: {})
+    return TestClient(app_module.app, raise_server_exceptions=False)
+
+
+def _urns(resp):
+    return sorted(s["urn"] for s in resp.json()["schools"])
+
+
+def test_filter_yes_uses_flag_not_age_range(client):
+    resp = client.get("/api/schools?has_sixth_form=yes")
+    assert resp.status_code == 200, resp.text
+    # 16-19 college included; 11-18-without-sixth-form excluded
+    assert _urns(resp) == [100001, 100002]
+
+
+def test_filter_no_uses_flag_not_age_range(client):
+    resp = client.get("/api/schools?has_sixth_form=no")
+    assert resp.status_code == 200, resp.text
+    # Gamma (flag false) and Delta (flag missing => not true)
+    assert _urns(resp) == [100003, 100004]
+
+
+def test_list_payload_includes_flag(client):
+    resp = client.get("/api/schools")
+    assert resp.status_code == 200, resp.text
+    by_urn = {s["urn"]: s for s in resp.json()["schools"]}
+    assert by_urn[100002]["has_sixth_form"] is True
+    assert by_urn[100003]["has_sixth_form"] is False
+    assert by_urn[100004]["has_sixth_form"] is None
+
+
+def test_detail_payload_includes_flag(client):
+    resp = client.get("/api/schools/100002")
+    assert resp.status_code == 200, resp.text
+    assert resp.json()["school_info"]["has_sixth_form"] is True
+
+
+def test_detail_payload_serializes_numpy_bool(monkeypatch):
+    """Once the pipeline has run, has_sixth_form is a real bool dtype column
+    (dbt not_null test guarantees no NULLs), so row access yields
+    numpy.bool_ rather than a Python bool. convert_to_native must handle it —
+    otherwise FastAPI's jsonable_encoder raises ValueError and the detail
+    endpoint 500s (C2)."""
+    from backend import app as app_module
+
+    df = _schools_df()
+    # Drop the row with a None flag — this fixture models the post-pipeline
+    # state where the column is a genuine, fully-populated bool dtype.
+    df = df[df["has_sixth_form"].notna()].reset_index(drop=True)
+    df["has_sixth_form"] = df["has_sixth_form"].astype(bool)
+    assert df["has_sixth_form"].dtype == bool
+
+    monkeypatch.setattr(app_module, "load_school_data", lambda: df)
+    monkeypatch.setattr(app_module, "get_supplementary_data", lambda db, urn: {})
+    client = TestClient(app_module.app, raise_server_exceptions=False)
+
+    resp = client.get("/api/schools/100002")
+    assert resp.status_code == 200, resp.text
+    assert resp.json()["school_info"]["has_sixth_form"] is True
+
+
+def test_load_school_data_survives_missing_has_sixth_form_column(monkeypatch):
+    """Real prod state until the nightly pipeline first rebuilds the mart:
+    marts.dim_school lacks has_sixth_form entirely. The first query raises
+    UndefinedColumn; load_school_data_as_dataframe must retry without the
+    column (synthesizing it as None) rather than swallow the error and
+    return (and then have load_school_data cache) an empty DataFrame (C1)."""
+    import sqlalchemy.exc
+    from backend import data_loader
+
+    data_loader._df_cache = None
+    data_loader._df_latest_cache = None
+
+    good_df = pd.DataFrame(
+        [
+            {
+                "urn": 1,
+                "school_name": "Fallback School",
+                "school_type": "Academy",
+                "has_sixth_form": None,
+            }
+        ]
+    )
+    calls = []
+
+    def fake_read_sql(query, con):
+        calls.append(query)
+        if len(calls) == 1:
+            # The statement text still contains phase_code, school_type_code,
+            # etc. (it's the full _MAIN_QUERY SELECT list) — that's exactly
+            # the collision this test guards against: matching must be done
+            # against exc.orig (the DBAPI error), not str(exc)/the statement.
+            raise sqlalchemy.exc.ProgrammingError(
+                statement=str(data_loader._MAIN_QUERY),
+                params=None,
+                orig=Exception(
+                    "(psycopg2.errors.UndefinedColumn) column s.has_sixth_form "
+                    "does not exist"
+                ),
+            )
+        return good_df.copy()
+
+    monkeypatch.setattr(data_loader.pd, "read_sql", fake_read_sql)
+
+    try:
+        df = data_loader.load_school_data_as_dataframe()
+    finally:
+        data_loader._df_cache = None
+        data_loader._df_latest_cache = None
+
+    assert len(calls) == 2, "must retry with the no-sixth-form query variant"
+    assert calls[1] is data_loader._MAIN_QUERY_NO_SIXTH_FORM
+    assert not df.empty
+    assert "has_sixth_form" in df.columns
+    assert df["has_sixth_form"].iloc[0] is None
@@ -0,0 +1,111 @@
+"""get_supplementary_data_batch fetches one query per table for all URNs
+(not ~5 per school) and returns the same per-URN block shape as the
+single-URN function, picking the latest row per URN where relevant."""
+
+import types
+
+from backend import data_loader
+from backend.data_loader import get_supplementary_data_batch
+
+
+class _FakeQuery:
+    """Records that a query ran and serves canned rows filtered by an in-list."""
+
+    def __init__(self, recorder, model_name, rows):
+        self._rec = recorder
+        self._model = model_name
+        self._rows = rows
+
+    def filter(self, *args, **kwargs):
+        return self
+
+    def order_by(self, *args, **kwargs):
+        return self
+
+    def all(self):
+        self._rec.append(self._model)
+        return self._rows
+
+    def first(self):
+        self._rec.append(self._model)
+        return self._rows[0] if self._rows else None
+
+
+class _FakeSession:
+    def __init__(self, rows_by_model):
+        self.rows_by_model = rows_by_model
+        self.queries: list[str] = []
+
+    def query(self, model):
+        name = model.__name__
+        return _FakeQuery(self.queries, name, self.rows_by_model.get(name, []))
+
+    def rollback(self):
+        pass
+
+
+def _ofsted_row(urn, date, oe):
+    base = {f: None for f in (
+        "framework", "inspection_type", "quality_of_education", "behaviour_attitudes",
+        "personal_development", "leadership_management", "early_years_provision",
+        "sixth_form_provision", "ungraded_outcome", "ungraded_grade",
+        "rc_safeguarding_met", "rc_inclusion", "rc_curriculum_teaching", "rc_achievement",
+        "rc_attendance_behaviour", "rc_personal_development", "rc_leadership_governance",
+        "rc_early_years", "rc_sixth_form", "report_url",
+    )}
+    base.update(urn=urn, inspection_date=types.SimpleNamespace(isoformat=lambda: date),
+                overall_effectiveness=oe, grade_source=None)
+    return types.SimpleNamespace(**base)
+
+
+def _adm_row(urn, year):
+    return types.SimpleNamespace(
+        urn=urn, year=year, school_phase="Primary", places_offered=100,
+        total_applications=200, first_preference_applications=150,
+        first_preference_offers=140, first_preference_offer_pct=93.3,
+        oversubscription_ratio=1.5, oversubscribed=True,
+        total_offers=100, second_preference_offers=5, third_preference_offers=2,
+        cross_la_applications=10, cross_la_offers=3,
+    )
+
+
+def test_one_query_per_table_and_latest_row_per_urn():
+    rows = {
+        # URN 1 has two Ofsted rows; the batch must keep the most recent (2023).
+        "FactOfstedInspection": [
+            _ofsted_row(1, "2023-01-01", 2),
+            _ofsted_row(1, "2019-01-01", 3),
+            _ofsted_row(2, "2021-06-01", 1),
+        ],
+        "FactAdmissions": [_adm_row(1, 202526), _adm_row(1, 202627), _adm_row(2, 202627)],
+        "FactPupilCharacteristics": [],
+        "FactDeprivation": [],
+        "FactFinance": [],
+    }
+    session = _FakeSession(rows)
+    out = get_supplementary_data_batch(session, [1, 2])
+
+    # Exactly one query per table — five total, regardless of two URNs.
+    assert sorted(session.queries) == [
+        "FactAdmissions", "FactDeprivation", "FactFinance",
+        "FactOfstedInspection", "FactPupilCharacteristics",
+    ]
+
+    # Latest Ofsted kept per URN
+    assert out[1]["ofsted"]["overall_effectiveness"] == 2
+    assert out[2]["ofsted"]["overall_effectiveness"] == 1
+
+    # Admissions history grouped per URN, latest exposed as `admissions`
+    assert [r["year"] for r in out[1]["admissions_history"]] == [202526, 202627]
+    assert out[1]["admissions"]["year"] == 202627
+    assert out[2]["admissions_history"] == [{**out[2]["admissions_history"][0]}]
+
+    # Empty tables degrade to the null block, not a crash
+    assert out[1]["census"] is None and out[1]["deprivation"] is None
+
+
+def test_single_wrapper_matches_batch(monkeypatch):
+    session = _FakeSession({"FactOfstedInspection": [_ofsted_row(5, "2022-01-01", 2)]})
+    single = data_loader.get_supplementary_data(session, 5)
+    assert single["ofsted"]["overall_effectiveness"] == 2
+    assert single["admissions_history"] == []
@@ -0,0 +1,65 @@
+"""Supplementary-block enrichment for the compare redesign: report-card
+labels, provider-page URL, graded-vs-carried-forward provenance, and the
+admissions preference/cross-LA detail promoted in the data-foundation PR."""
+
+import types
+
+from backend.data_loader import _admissions_row_dict, _ofsted_block
+
+
+def _row(**kw):
+    base = dict(
+        framework="RC", inspection_date=None, inspection_type=None,
+        overall_effectiveness=None, quality_of_education=None,
+        behaviour_attitudes=None, personal_development=None,
+        leadership_management=None, early_years_provision=None,
+        sixth_form_provision=None, ungraded_outcome=None, ungraded_grade=None,
+        rc_safeguarding_met=None, rc_inclusion=None, rc_curriculum_teaching=None,
+        rc_achievement=None, rc_attendance_behaviour=None,
+        rc_personal_development=None, rc_leadership_governance=None,
+        rc_early_years=None, rc_sixth_form=None, report_url=None,
+    )
+    base.update(kw)
+    return types.SimpleNamespace(**base)
+
+
+def test_report_card_block_and_provider_url():
+    o = _row(rc_achievement=2, rc_inclusion=3, rc_safeguarding_met=True)
+    block = _ofsted_block(o, urn=100140)
+    assert block["report_card"]["rc_achievement"]["label"] == "Strong standard"
+    assert "rc_safeguarding_met" not in block["report_card"]
+    assert block["rc_safeguarding_met"] is True
+    assert block["ofsted_page_url"] == "https://reports.ofsted.gov.uk/provider/21/100140"
+
+
+def test_grade_source_graded_vs_carried_forward():
+    assert _ofsted_block(_row(overall_effectiveness=1), urn=1)["grade_source"] == "graded"
+    carried = _ofsted_block(_row(ungraded_grade=2), urn=1)
+    assert carried["grade_source"] == "ungraded_carried_forward"
+    assert carried["overall_effectiveness"] == 2
+    assert _ofsted_block(_row(), urn=1)["grade_source"] is None
+
+
+def test_ofsted_block_keeps_existing_keys():
+    block = _ofsted_block(_row(overall_effectiveness=2, quality_of_education=2), urn=1)
+    for key in ("framework", "inspection_date", "overall_effectiveness",
+                "quality_of_education", "rc_inclusion", "report_url"):
+        assert key in block
+
+
+def test_admissions_row_new_fields():
+    a = types.SimpleNamespace(
+        year=202627, school_phase="Primary", places_offered=80,
+        total_applications=185, first_preference_applications=74,
+        first_preference_offers=74, first_preference_offer_pct=100.0,
+        oversubscription_ratio=0.925, oversubscribed=False,
+        total_offers=80, second_preference_offers=4, third_preference_offers=2,
+        cross_la_applications=12, cross_la_offers=3,
+    )
+    d = _admissions_row_dict(a)
+    for k in ("total_offers", "second_preference_offers", "third_preference_offers",
+              "cross_la_applications", "cross_la_offers"):
+        assert d[k] == getattr(a, k)
+    # Existing keys unchanged
+    assert d["first_preference_offer_pct"] == 100.0
+    assert d["oversubscribed"] is False
@@ -11,6 +11,8 @@ def convert_to_native(value: Any) -> Any:
    """Convert numpy types to native Python types for JSON serialization."""
    if pd.isna(value):
        return None
+    if isinstance(value, np.bool_):
+        return bool(value)
    if isinstance(value, (np.integer,)):
        return int(value)
    if isinstance(value, (np.floating,)):
@@ -112,11 +112,15 @@ Full details in `docs/DEPLOY.md`. The short version:
 - **Never push to `main` directly.** Work on a feature branch and open a PR;
  branch protection requires the PR checks (typecheck, tests, builds, AI review)
  to pass before merge.
- Merging to `main` deploys automatically: images are built once, deployed to
-  the **staging** Portainer stack, verified by the Playwright journeys in
-  `e2e/`, and only then retagged `:prod` and rolled out to production.
+- Merging to `main` deploys automatically **to staging only**: images are
+  built once, deployed to the staging Portainer stack, and verified by the
+  Playwright journeys in `e2e/`. Production is a second, manual approval:
+  the "Promote to Production (manual)" workflow in Gitea Actions, run after
+  testing the feature on staging. It refuses commits whose staging E2E gate
+  isn't green. Never trigger it yourself — promotion is the human's call.
 - If you change user-facing behaviour, update or extend the `e2e/` journey
-  tests in the same PR — they are the promotion gate.
+  tests in the same PR — they gate whether staging is fit for human testing
+  and whether a commit is promotable.

 ## Recent Changes

@@ -1,41 +1,61 @@
 # SDLC & Deployment Pipeline

-SchoolCompare uses a fully automated staging → production pipeline on Gitea
-Actions. AI writes the code on feature branches; the pipeline verifies every
-change on a staging environment before promoting the exact same images to
-production. Human input is directional only: feature requests, PR review if
-desired, and intervention when a gate fails.
+SchoolCompare uses a two-stage deploy model on Gitea Actions with two human
+approvals. AI writes the code on feature branches; the first approval merges
+the PR, which deploys to staging and runs the E2E gate; the second approval —
+after manual testing on staging — promotes the exact same images to
+production via a manual workflow.

 ## The flow

 ```
 feature branch (AI-authored)
-   │  PR to main
+   │  PR to main                                    ← approval #1
   ▼
 PR checks (.gitea/workflows/pr-checks.yml)
   typecheck + unit tests + backend smoke + image builds (no push)
   + Claude code review posted as a PR comment (severe findings fail the check)
   │  merge (branch protection requires green checks)
   ▼
-Deploy pipeline (.gitea/workflows/deploy.yml)
+Stage pipeline (.gitea/workflows/deploy.yml) — automatic
   1. build & push images        → tags sha-<sha>, staging
   2. staging Portainer webhook  → wait for staging health
-   3. Playwright E2E journeys against staging
-   4. retag sha-<sha> → :prod    (same bytes — build once, promote the image)
+   3. Playwright E2E journeys against staging      ← gate before human testing
+   ▼
+Manual testing on staging (stx.schoolcompare.co.uk)
+   │  Actions → "Promote to Production (manual)"   ← approval #2
+   ▼
+Promote pipeline (.gitea/workflows/promote.yml) — manual dispatch
+   1. resolve target sha (input, or latest main if empty)
+   2. REFUSE unless that commit's "E2E Journeys against Staging" status is green
+   3. retag sha-<sha> → :prod    (same bytes — build once, promote the image)
      previous :prod saved as :prod-previous
-   5. prod Portainer webhook     → wait for prod health
+   4. prod Portainer webhook     → wait for prod health
 ```

 Key principle: **build once, promote the exact image**. Production pins `:prod`,
-which only moves after the E2E gate passes on staging. Nothing tags `:latest`
+which only moves when a human runs the promote workflow — and the workflow
+only accepts commits that passed the staging E2E gate. Nothing tags `:latest`
 anymore.

 ## Branch & PR workflow

 - `main` is protected: no direct pushes, PRs require green status checks.
 - All work (human or AI) happens on feature branches → PR to `main`.
- Merging to `main` **is** the release action. If staging or the E2E gate
-  fails, production is untouched.
+- Merging to `main` releases **to staging only**. Production moves only on
+  the second approval. If staging or the E2E gate fails, fix forward —
+  production is untouched either way.
+
+## Promotion granularity
+
+Staging always runs the latest `main`. Promoting approves a *state of main*,
+not a single PR — if two PRs merged since the last promotion, they ship
+together. Test staging accordingly. To promote an older state, pass its
+commit SHA to the promote workflow (its images must still exist in the
+registry).
+
+Staging quirk for manual testing: external `/api` is broken at the staging
+proxy — exercise API endpoints from the host, not via the public staging URL.

 ## Environments

@@ -92,8 +112,9 @@ fail the E2E gate. That's the point: staging absorbs the risk.

 ## Rollback

-Every promotion first re-points `:prod-previous` at the outgoing `:prod`.
-To roll back:
+Re-run "Promote to Production (manual)" with the SHA of the last good commit
+(fastest, fully gated), or manually re-point the tags — every promotion first
+saves the outgoing `:prod` as `:prod-previous`:

 ```bash
 for img in backend frontend pipeline; do
@@ -0,0 +1,560 @@
+# GIAS OfficialSixthForm Flag Implementation Plan
+
+> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
+
+**Goal:** Ingest GIAS's authoritative `OfficialSixthForm` flag into `marts.dim_school.has_sixth_form` and replace every `age_range contains "18"` heuristic in the backend and frontend with it.
+
+**Architecture:** Data flows tap → raw → dbt staging → dbt mart → backend SQL → API payload → Next.js components. The GIAS Singer tap must declare the new CSV column (target-postgres only persists declared columns); the dbt staging model renames it; `dim_school` derives a boolean (with a statutory-age fallback for blank GIAS values); the backend exposes it on list + detail payloads and uses it for the `has_sixth_form=yes|no` filter; the frontend badge/note/filter-labels switch from the age-range substring check to the flag.
+
+**Tech Stack:** Singer SDK (tap), dbt (Postgres), FastAPI + pandas, Next.js + TypeScript, pytest, Jest/RTL.
+
+**Spec:** `docs/superpowers/specs/2026-07-07-exam-phase-taxonomy-design.md` §3.
+
+## Global Constraints
+
+- A school **has a sixth form** iff GIAS `OfficialSixthForm (name)` = `"Has a sixth form"`. `"Does not have a sixth form"` and `"Not applicable"` → false. Blank/NULL (rare) → fall back to `statutory_high_age >= 18`.
+- The public API filter parameter stays `has_sixth_form=yes|no` (unchanged contract).
+- Filter dropdown labels must drop the age-range parentheticals: "With sixth form" / "Without sixth form" (sixth form ≠ age range).
+- Never push to `main`; work stays on branch `feat/gias-sixth-form-flag` (create from `docs/exam-phase-taxonomy` so the spec is included, or from `main` if that branch has merged).
+- The dbt models cannot be run locally (no pipeline DB); dbt changes are verified by review + `python -c` schema asserts + existing CI. Do NOT attempt to start a local server.
+- The backend marts tables are dbt `table` materializations — rebuilt on every pipeline run, so **no ALTER TABLE migration is needed** for `marts.dim_school`.
+- Deployment ordering: the tap must run before dbt on the first pipeline run after deploy (this is already the DAG order: extract → transform). Until that run happens, `has_sixth_form` is absent from the DB; the backend must treat a missing column as "flag false / fallback", never crash.
+
+---
+
+### Task 1: Ingest `OfficialSixthForm (name)` — tap schema + dbt staging
+
+**Files:**
+- Modify: `pipeline/plugins/extractors/tap-uk-gias/tap_uk_gias/tap.py:31-66` (Singer schema)
+- Modify: `pipeline/transform/models/staging/stg_gias_establishments.sql` (add renamed column)
+
+**Interfaces:**
+- Produces: raw column `"OfficialSixthForm (name)"` in `raw.gias_establishments`; staging column `official_sixth_form` (text: `Has a sixth form` / `Does not have a sixth form` / `Not applicable` / NULL) consumed by Task 2.
+
+- [ ] **Step 1: Add the property to the Singer schema**
+
+In `tap.py`, inside `GIASEstablishmentsStream.schema = th.PropertiesList(...)`, add after the `th.Property("PhaseOfEducation (name)", th.StringType),` line:
+
+```python
+        th.Property("OfficialSixthForm (name)", th.StringType),
+```
+
+- [ ] **Step 2: Verify the tap module still imports and declares the column**
+
+Run:
+```bash
+cd /Users/tudor/projects/school_compare/pipeline/plugins/extractors/tap-uk-gias && \
+python3 -c "
+import ast, sys
+src = open('tap_uk_gias/tap.py').read()
+ast.parse(src)
+assert '\"OfficialSixthForm (name)\"' in src.replace(\"'\", '\"')
+print('OK: tap declares OfficialSixthForm (name)')
+"
+```
+Expected: `OK: tap declares OfficialSixthForm (name)`
+(Uses `ast.parse` instead of importing because `singer_sdk` is not installed locally.)
+
+- [ ] **Step 3: Add the column to the staging model**
+
+In `stg_gias_establishments.sql`, in the `renamed` CTE, add after the `"PhaseOfEducation (name)" as phase,` line:
+
+```sql
+        nullif(trim("OfficialSixthForm (name)"), '')    as official_sixth_form,
+```
+
+- [ ] **Step 4: Sanity-check the SQL edit**
+
+Run:
+```bash
+grep -n "official_sixth_form" /Users/tudor/projects/school_compare/pipeline/transform/models/staging/stg_gias_establishments.sql
+```
+Expected: one line showing the new column inside the `renamed` CTE (before `from source`).
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add pipeline/plugins/extractors/tap-uk-gias/tap_uk_gias/tap.py pipeline/transform/models/staging/stg_gias_establishments.sql
+git commit -m "feat(pipeline): ingest GIAS OfficialSixthForm into staging
+
+Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>"
+```
+
+---
+
+### Task 2: Derive `dim_school.has_sixth_form` (dbt mart + schema tests + SQLAlchemy model)
+
+**Files:**
+- Modify: `pipeline/transform/models/marts/dim_school.sql` (add derived column)
+- Modify: `pipeline/transform/models/marts/_marts_schema.yml` (document + test the column)
+- Modify: `backend/models.py:13-38` (`DimSchool` — add column)
+
+**Interfaces:**
+- Consumes: `official_sixth_form` text column from Task 1's staging model.
+- Produces: `marts.dim_school.has_sixth_form boolean not null`, and `DimSchool.has_sixth_form = Column(Boolean)` for the backend. Task 3 selects it as `s.has_sixth_form`.
+
+- [ ] **Step 1: Add the derived column to `dim_school.sql`**
+
+In the `select`, add after the `s.age_range` line (`s.statutory_low_age || '-' || s.statutory_high_age as age_range,`):
+
+```sql
+    -- Authoritative sixth-form flag (spec §3): GIAS OfficialSixthForm.
+    -- "Not applicable" (nurseries, primaries, PRUs) => false. Blank GIAS
+    -- value (rare, new establishments) falls back to the statutory age range.
+    case
+        when s.official_sixth_form = 'Has a sixth form' then true
+        when s.official_sixth_form in ('Does not have a sixth form', 'Not applicable') then false
+        else coalesce(s.statutory_high_age >= 18, false)
+    end as has_sixth_form,
+```
+
+- [ ] **Step 2: Add schema documentation + tests in `_marts_schema.yml`**
+
+Under `- name: dim_school` → `columns:`, add after the `phase` column block:
+
+```yaml
+      - name: has_sixth_form
+        description: >
+          Authoritative sixth-form flag from GIAS OfficialSixthForm.
+          "Has a sixth form" => true; "Does not have a sixth form" and
+          "Not applicable" => false; blank GIAS value falls back to
+          statutory_high_age >= 18. Replaces the age_range-contains-"18"
+          heuristic (spec 2026-07-07 §3).
+        tests:
+          - not_null
+          - accepted_values:
+              values: [true, false]
+```
+
+- [ ] **Step 3: Add the column to the `DimSchool` SQLAlchemy model**
+
+In `backend/models.py`, in `class DimSchool`, add after `age_range = Column(String(20))`:
+
+```python
+    has_sixth_form = Column(Boolean)
+```
+
+- [ ] **Step 4: Verify SQL/YAML/Python all parse**
+
+Run:
+```bash
+cd /Users/tudor/projects/school_compare && \
+python3 -c "
+import yaml
+y = yaml.safe_load(open('pipeline/transform/models/marts/_marts_schema.yml'))
+dim = [m for m in y['models'] if m['name'] == 'dim_school'][0]
+cols = [c['name'] for c in dim['columns']]
+assert 'has_sixth_form' in cols, cols
+print('OK: schema yml documents has_sixth_form')
+" && \
+grep -c "has_sixth_form" pipeline/transform/models/marts/dim_school.sql && \
+python3 -c "import ast; ast.parse(open('backend/models.py').read()); print('OK: models.py parses')"
+```
+Expected: `OK: schema yml documents has_sixth_form`, grep count `>= 1`, `OK: models.py parses`.
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add pipeline/transform/models/marts/dim_school.sql pipeline/transform/models/marts/_marts_schema.yml backend/models.py
+git commit -m "feat(pipeline): derive dim_school.has_sixth_form from GIAS flag
+
+Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>"
+```
+
+---
+
+### Task 3: Backend — expose `has_sixth_form` and replace the filter heuristic
+
+**Files:**
+- Modify: `backend/data_loader.py:117-215` (`_MAIN_QUERY` — select the column)
+- Modify: `backend/schemas.py:536-553` (`SCHOOL_COLUMNS` — include in list payloads)
+- Modify: `backend/app.py:419-422` (filter) and `backend/app.py:589-610` (detail `school_info`)
+- Test: `backend/tests/test_sixth_form_flag.py` (new)
+
+**Interfaces:**
+- Consumes: `marts.dim_school.has_sixth_form` (Task 2).
+- Produces: `has_sixth_form: bool | null` field on `GET /api/schools` items and on `GET /api/schools/{urn}` → `school_info`. Filter `GET /api/schools?has_sixth_form=yes|no` now driven by the flag. Frontend (Task 4) reads `school.has_sixth_form`.
+
+- [ ] **Step 1: Write the failing tests**
+
+Create `backend/tests/test_sixth_form_flag.py`:
+
+```python
+"""Tests for the GIAS-driven has_sixth_form flag (spec 2026-07-07 §3).
+
+The filter and payloads must use dim_school.has_sixth_form, not the old
+age_range-contains-"18" substring heuristic. The key regression case is a
+16-19 sixth-form college: flag true, but "16-19" contains no "18".
+"""
+
+import numpy as np
+import pandas as pd
+import pytest
+from fastapi.testclient import TestClient
+
+
+def _schools_df() -> pd.DataFrame:
+    """Latest-year snapshot rows as produced by load_latest_school_data."""
+    base = {
+        "local_authority": "Testshire",
+        "school_type": "Academy",
+        "phase": "Secondary",
+        "address": "1 Test Street",
+        "town": "Testtown",
+        "postcode": "TS1 1AA",
+        "religious_denomination": None,
+        "gender": "Mixed",
+        "admissions_policy": None,
+        "ofsted_grade": np.nan,
+        "ofsted_date": None,
+        "ofsted_framework": None,
+        "latitude": 51.5,
+        "longitude": -0.1,
+        "year": 202425,
+        "total_pupils": 1000,
+        "rwm_expected_pct": np.nan,
+        "attainment_8_score": 50.0,
+    }
+    return pd.DataFrame(
+        [
+            # 11-18 school WITH a registered sixth form
+            {**base, "urn": 100001, "school_name": "Alpha High",
+             "age_range": "11-18", "has_sixth_form": True},
+            # 16-19 college: old heuristic said NO ("16-19" has no "18"),
+            # GIAS flag says YES — must appear in the yes-filter results
+            {**base, "urn": 100002, "school_name": "Beta Sixth Form College",
+             "age_range": "16-19", "has_sixth_form": True},
+            # 11-18 age range on paper but NO registered sixth form:
+            # old heuristic said YES, GIAS flag says NO
+            {**base, "urn": 100003, "school_name": "Gamma Academy",
+             "age_range": "11-18", "has_sixth_form": False},
+            # Missing flag (pipeline not yet re-run) — must not crash,
+            # must not match the yes-filter
+            {**base, "urn": 100004, "school_name": "Delta School",
+             "age_range": "11-16", "has_sixth_form": None},
+        ]
+    )
+
+
+@pytest.fixture()
+def client(monkeypatch):
+    from backend import app as app_module
+
+    monkeypatch.setattr(app_module, "load_latest_school_data", _schools_df)
+    monkeypatch.setattr(app_module, "load_school_data", _schools_df)
+    monkeypatch.setattr(app_module, "get_supplementary_data", lambda db, urn: {})
+    return TestClient(app_module.app, raise_server_exceptions=False)
+
+
+def _urns(resp):
+    return sorted(s["urn"] for s in resp.json()["schools"])
+
+
+def test_filter_yes_uses_flag_not_age_range(client):
+    resp = client.get("/api/schools?has_sixth_form=yes")
+    assert resp.status_code == 200, resp.text
+    # 16-19 college included; 11-18-without-sixth-form excluded
+    assert _urns(resp) == [100001, 100002]
+
+
+def test_filter_no_uses_flag_not_age_range(client):
+    resp = client.get("/api/schools?has_sixth_form=no")
+    assert resp.status_code == 200, resp.text
+    # Gamma (flag false) and Delta (flag missing => not true)
+    assert _urns(resp) == [100003, 100004]
+
+
+def test_list_payload_includes_flag(client):
+    resp = client.get("/api/schools")
+    assert resp.status_code == 200, resp.text
+    by_urn = {s["urn"]: s for s in resp.json()["schools"]}
+    assert by_urn[100002]["has_sixth_form"] is True
+    assert by_urn[100003]["has_sixth_form"] is False
+    assert by_urn[100004]["has_sixth_form"] is None
+
+
+def test_detail_payload_includes_flag(client):
+    resp = client.get("/api/schools/100002")
+    assert resp.status_code == 200, resp.text
+    assert resp.json()["school_info"]["has_sixth_form"] is True
+```
+
+- [ ] **Step 2: Run tests to verify they fail**
+
+Run: `cd /Users/tudor/projects/school_compare && python3 -m pytest backend/tests/test_sixth_form_flag.py -v`
+Expected: FAIL — `test_filter_yes_uses_flag_not_age_range` asserts `[100001, 100002]` but the age-range heuristic returns `[100001, 100003]`; the payload tests fail with `KeyError: 'has_sixth_form'`.
+
+- [ ] **Step 3: Select the column in `_MAIN_QUERY`**
+
+In `backend/data_loader.py`, in `_MAIN_QUERY`, add after `s.age_range,`:
+
+```sql
+        s.has_sixth_form,
+```
+
+- [ ] **Step 4: Include it in list payloads**
+
+In `backend/schemas.py`, in `SCHOOL_COLUMNS`, add after `"age_range",`:
+
+```python
+    "has_sixth_form",
+```
+
+(`app.py` builds list responses from `SCHOOL_COLUMNS ∩ df.columns`, so a DB that predates the pipeline re-run simply omits the field — no crash.)
+
+- [ ] **Step 5: Replace the filter heuristic in `app.py`**
+
+Replace lines 419-422:
+
+```python
+    if has_sixth_form == "yes":
+        df_latest = df_latest[df_latest["age_range"].str.contains("18", na=False)]
+    elif has_sixth_form == "no":
+        df_latest = df_latest[~df_latest["age_range"].str.contains("18", na=False)]
+```
+
+with:
+
+```python
+    # GIAS OfficialSixthForm flag (dim_school.has_sixth_form). NULL (flag not
+    # yet populated by the pipeline) is treated as "no sixth form".
+    if has_sixth_form in ("yes", "no"):
+        if "has_sixth_form" in df_latest.columns:
+            flag = df_latest["has_sixth_form"].eq(True)
+        else:  # DB predates the pipeline re-run — fall back to age range
+            flag = df_latest["age_range"].str.contains("18", na=False)
+        df_latest = df_latest[flag if has_sixth_form == "yes" else ~flag]
+```
+
+- [ ] **Step 6: Add the flag to the detail payload**
+
+In `backend/app.py` `school_info` dict (line ~598), add after `"age_range": latest.get("age_range", ""),`:
+
+```python
+            "has_sixth_form": latest.get("has_sixth_form"),
+```
+
+(`convert_to_native` already maps NaN/None → null and numpy bools → bool.)
+
+- [ ] **Step 7: Run the new tests**
+
+Run: `cd /Users/tudor/projects/school_compare && python3 -m pytest backend/tests/test_sixth_form_flag.py -v`
+Expected: 4 passed.
+
+- [ ] **Step 8: Run the full backend suite**
+
+Run: `cd /Users/tudor/projects/school_compare && python3 -m pytest backend/tests -v`
+Expected: all pass (the pre-existing `test_school_details.py` df has no `has_sixth_form` column — `latest.get()` returns None, serialized as null).
+
+- [ ] **Step 9: Commit**
+
+```bash
+git add backend/data_loader.py backend/schemas.py backend/app.py backend/tests/test_sixth_form_flag.py
+git commit -m "feat(api): drive has_sixth_form filter and payloads from GIAS flag
+
+Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>"
+```
+
+---
+
+### Task 4: Frontend — badge, note, row tag, and filter labels use the flag
+
+**Files:**
+- Modify: `nextjs-app/lib/types.ts:10-30` (`School` interface)
+- Modify: `nextjs-app/components/SecondarySchoolDetailView.tsx:101` (badge + coming-soon note)
+- Modify: `nextjs-app/components/SecondarySchoolRow.tsx:25-27` (row tag)
+- Modify: `nextjs-app/components/FilterBar.tsx:370-372` (labels only — param name unchanged)
+- Test: `nextjs-app/__tests__/components/SecondarySchoolRow.test.tsx` (new)
+
+**Interfaces:**
+- Consumes: `has_sixth_form: boolean | null` on both list items and `school_info` (Task 3; both are typed as `School`).
+- Produces: no new exports — behavior change only.
+
+- [ ] **Step 1: Write the failing test**
+
+Create `nextjs-app/__tests__/components/SecondarySchoolRow.test.tsx`:
+
+```tsx
+/**
+ * SecondarySchoolRow — sixth-form tag must come from the GIAS
+ * has_sixth_form flag, not the age_range-contains-"18" heuristic.
+ */
+
+import '@testing-library/jest-dom';
+import { render, screen } from '@testing-library/react';
+import { SecondarySchoolRow } from '@/components/SecondarySchoolRow';
+import type { School } from '@/lib/types';
+
+const base = {
+  urn: 100002,
+  school_name: 'Beta Sixth Form College',
+  local_authority: 'Testshire',
+  school_type: 'Academy',
+  phase: 'Secondary',
+  gender: 'Mixed',
+  attainment_8_score: 50.0,
+} as unknown as School;
+
+describe('SecondarySchoolRow sixth-form tag', () => {
+  it('shows the tag for a 16-19 college with the GIAS flag set', () => {
+    render(
+      <SecondarySchoolRow
+        school={{ ...base, age_range: '16-19', has_sixth_form: true }}
+      />,
+    );
+    expect(screen.getByText('Sixth form')).toBeInTheDocument();
+  });
+
+  it('hides the tag for an 11-18 school without a registered sixth form', () => {
+    render(
+      <SecondarySchoolRow
+        school={{ ...base, age_range: '11-18', has_sixth_form: false }}
+      />,
+    );
+    expect(screen.queryByText('Sixth form')).not.toBeInTheDocument();
+  });
+
+  it('hides the tag when the flag is missing (pipeline not yet re-run)', () => {
+    render(
+      <SecondarySchoolRow school={{ ...base, age_range: '11-18' }} />,
+    );
+    expect(screen.queryByText('Sixth form')).not.toBeInTheDocument();
+  });
+});
+```
+
+- [ ] **Step 2: Run it to verify it fails**
+
+Run: `cd /Users/tudor/projects/school_compare/nextjs-app && npx jest __tests__/components/SecondarySchoolRow.test.tsx`
+Expected: FAIL — first test can't find "Sixth form" ("16-19" fails the substring check), second test finds an unexpected "Sixth form" tag. (If TS complains that `has_sixth_form` is not on `School`, that is the same failure — proceed.)
+
+- [ ] **Step 3: Add the field to the `School` type**
+
+In `nextjs-app/lib/types.ts`, in `export interface School`, add after `age_range: string | null;`:
+
+```ts
+  has_sixth_form?: boolean | null;
+```
+
+- [ ] **Step 4: Switch `SecondarySchoolRow` to the flag**
+
+Replace the helper at `SecondarySchoolRow.tsx:25-27`:
+
+```ts
+function hasSixthForm(school: School): boolean {
+  return school.age_range?.includes('18') ?? false;
+}
+```
+
+with:
+
+```ts
+function hasSixthForm(school: School): boolean {
+  // GIAS OfficialSixthForm flag; missing (pipeline not yet re-run) => false.
+  return school.has_sixth_form ?? false;
+}
+```
+
+- [ ] **Step 5: Switch `SecondarySchoolDetailView` to the flag**
+
+Replace line 101:
+
+```ts
+  const hasSixthForm = schoolInfo.age_range?.includes('18') ?? false;
+```
+
+with:
+
+```ts
+  // GIAS OfficialSixthForm flag; missing (pipeline not yet re-run) => false.
+  const hasSixthForm = schoolInfo.has_sixth_form ?? false;
+```
+
+(This drives both the header "Sixth form" badge at line ~230 and the "Post-16 destination data coming soon" note at line ~715 — no changes needed there.)
+
+- [ ] **Step 6: Fix the filter labels in `FilterBar.tsx`**
+
+Replace:
+
+```tsx
+                    <option value="yes">With sixth form (11-18)</option>
+                    <option value="no">Without sixth form (11-16)</option>
+```
+
+with:
+
+```tsx
+                    <option value="yes">With sixth form</option>
+                    <option value="no">Without sixth form</option>
+```
+
+- [ ] **Step 7: Run the new test and verify it passes**
+
+Run: `cd /Users/tudor/projects/school_compare/nextjs-app && npx jest __tests__/components/SecondarySchoolRow.test.tsx`
+Expected: 3 passed.
+
+- [ ] **Step 8: Run the full frontend checks**
+
+Run: `cd /Users/tudor/projects/school_compare/nextjs-app && npx tsc --noEmit && npx jest`
+Expected: typecheck clean, all Jest suites pass.
+
+- [ ] **Step 9: Verify no heuristic remains**
+
+Run:
+```bash
+grep -rn "includes('18')\|contains(\"18\")" /Users/tudor/projects/school_compare/nextjs-app/components /Users/tudor/projects/school_compare/backend --include="*.tsx" --include="*.ts" --include="*.py" | grep -v test
+```
+Expected: only the documented fallback inside `app.py` (DB-predates-pipeline branch); no other hits.
+
+- [ ] **Step 10: Commit**
+
+```bash
+git add nextjs-app/lib/types.ts nextjs-app/components/SecondarySchoolRow.tsx nextjs-app/components/SecondarySchoolDetailView.tsx nextjs-app/components/FilterBar.tsx nextjs-app/__tests__/components/SecondarySchoolRow.test.tsx
+git commit -m "feat(ui): sixth-form badge, note and filter labels use GIAS flag
+
+Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>"
+```
+
+---
+
+### Task 5: Update the spec status + PR
+
+**Files:**
+- Modify: `docs/superpowers/specs/2026-07-07-exam-phase-taxonomy-design.md` (§3 "Pipeline change (future work)" → implemented)
+
+**Interfaces:**
+- Consumes: everything above merged into the branch.
+- Produces: PR ready for review; e2e journeys are the promotion gate (no journey currently exercises the sixth-form filter, and the API contract is unchanged, so no e2e change is required — state this in the PR body).
+
+- [ ] **Step 1: Mark spec §3 pipeline change as implemented**
+
+In the spec, change the §3 heading `### Pipeline change (future work)` to `### Pipeline change (implemented 2026-07-07)` and append one line at the end of that subsection:
+
+```markdown
+Implemented in `feat/gias-sixth-form-flag` — see
+`docs/superpowers/plans/2026-07-07-gias-sixth-form-flag.md`.
+```
+
+- [ ] **Step 2: Commit**
+
+```bash
+git add docs/superpowers/specs/2026-07-07-exam-phase-taxonomy-design.md
+git commit -m "docs: mark sixth-form flag pipeline change implemented
+
+Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>"
+```
+
+- [ ] **Step 3: Push and open the PR (Gitea)**
+
+Push the branch, then create the PR against `main` using the Gitea API via the git credential helper (token-header auth 401s on this Gitea; basic auth from `git credential fill` works):
+
+```bash
+git push -u origin feat/gias-sixth-form-flag
+```
+
+PR title: `feat: drive sixth-form separation from GIAS OfficialSixthForm flag`
+PR body must note: (1) API contract unchanged (`has_sixth_form=yes|no`), (2) flag is NULL until the next pipeline run — backend and frontend degrade to "no sixth form" / age-range fallback, (3) no e2e journey change needed, and end with the standard generation footer.
+
+- [ ] **Step 4: Verify CI passes**
+
+Watch the PR checks (typecheck, tests, builds, AI review). All must pass before merge; merging deploys to staging automatically.
@@ -0,0 +1,799 @@
+# GIAS Code Dictionaries Implementation Plan
+
+> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
+
+**Goal:** Store the six GIAS classification fields as official DfE integer codes in the marts and translate code → name in application code, leaving the API contract (name strings) unchanged.
+
+**Architecture:** A generation script downloads the public GIAS bulk CSV and emits the dictionaries (Python dicts + a dbt seed) from real data. The tap ingests the `(code)` columns, staging casts them, `dim_school`/`dim_location` keep only codes, and translation happens in exactly two places: `backend/data_loader.py` right after `pd.read_sql`, and `pipeline/scripts/sync_typesense.py` before indexing. A dbt seed test warns when DfE adds/renames a value; a parity test keeps the backend and pipeline dictionary copies identical.
+
+**Tech Stack:** Singer SDK tap, dbt (Postgres), FastAPI + pandas, Typesense sync script, pytest.
+
+**Spec:** `docs/superpowers/specs/2026-07-09-gias-code-dictionaries-design.md`
+
+## Global Constraints
+
+- **Numeric code values are never assumed.** Every literal code used in SQL or yml (status filter, sixth-form derivation, phase cascade) must be verified against `pipeline/transform/seeds/gias_code_names.csv` generated in Task 1 from the live CSV. The literals written in this plan are best-current-knowledge and each carries a verification step.
+- **Names served by the API must stay byte-identical** to today's strings (e.g. `Does not apply`, `Open, but proposed to close`) — UI heuristics compare exact strings.
+- The `(name)` columns stay declared in the tap and present in raw; staging stops exposing them.
+- `dim_school` and `dim_location` status filters must stay identical (API inner-joins them).
+- Backend tests run via: `uv run --with-requirements requirements.txt --with pytest --with "httpx==0.27.0" python -m pytest backend/tests -v` (no local pytest exists).
+- dbt cannot run locally — dbt changes are verified statically (grep / yaml parse) + CI.
+- Never push to `main`. Work on branch `feat/gias-code-dictionaries` (branch off `docs/gias-code-dictionaries` so the spec is included, or off `main` if that has merged).
+- Commits end with: `Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>`
+- Deploy runbook (accepted window, spec §7): merge → deploy → trigger `school_data_daily` immediately. No code-level fallback for the old-schema window.
+
+---
+
+### Task 1: Dictionary generation script, canonical module, pipeline copy, seed
+
+**Files:**
+- Create: `pipeline/scripts/generate_gias_codes.py`
+- Create: `backend/gias_codes.py` (content generated by the script)
+- Create: `pipeline/scripts/gias_codes.py` (byte-identical copy)
+- Create: `pipeline/transform/seeds/gias_code_names.csv` (generated)
+- Test: `backend/tests/test_gias_codes.py`
+
+**Interfaces:**
+- Produces: `backend/gias_codes.py` exporting `SCHOOL_TYPE`, `ESTABLISHMENT_STATUS`, `PHASE_OF_EDUCATION`, `OFFICIAL_SIXTH_FORM`, `RELIGIOUS_CHARACTER`, `ADMISSIONS_POLICY` (each `dict[int, str]`) and `translate(code, mapping) -> str | None`. Task 4 imports these; Task 5 imports the pipeline copy; Task 3 reads code literals from the seed CSV.
+
+- [ ] **Step 1: Write the failing tests**
+
+Create `backend/tests/test_gias_codes.py`:
+
+```python
+"""Tests for the GIAS code->name dictionaries (spec 2026-07-09).
+
+The dictionaries are generated from the live GIAS bulk CSV by
+pipeline/scripts/generate_gias_codes.py — these tests assert the module's
+contract, key sentinel values the marts/UI depend on, and that the pipeline
+copy has not drifted from the canonical backend module.
+"""
+
+import math
+from pathlib import Path
+
+from backend.gias_codes import (
+    ADMISSIONS_POLICY,
+    ESTABLISHMENT_STATUS,
+    OFFICIAL_SIXTH_FORM,
+    PHASE_OF_EDUCATION,
+    RELIGIOUS_CHARACTER,
+    SCHOOL_TYPE,
+    translate,
+)
+
+REPO = Path(__file__).resolve().parents[2]
+
+
+def test_translate_known_code():
+    open_code = next(c for c, n in ESTABLISHMENT_STATUS.items() if n == "Open")
+    assert translate(open_code, ESTABLISHMENT_STATUS) == "Open"
+
+
+def test_translate_unknown_code_degrades_gracefully():
+    assert translate(9999, ESTABLISHMENT_STATUS) == "Unknown (9999)"
+
+
+def test_translate_none_and_nan_return_none():
+    assert translate(None, ESTABLISHMENT_STATUS) is None
+    assert translate(float("nan"), ESTABLISHMENT_STATUS) is None
+
+
+def test_translate_accepts_float_codes():
+    # pd.read_sql yields float columns when NULLs are present
+    open_code = next(c for c, n in ESTABLISHMENT_STATUS.items() if n == "Open")
+    assert translate(float(open_code), ESTABLISHMENT_STATUS) == "Open"
+
+
+def test_sentinel_names_present():
+    """Names the marts/UI compare against must exist verbatim."""
+    assert "Open" in ESTABLISHMENT_STATUS.values()
+    assert "Open, but proposed to close" in ESTABLISHMENT_STATUS.values()
+    assert "Has a sixth form" in OFFICIAL_SIXTH_FORM.values()
+    assert "Primary" in PHASE_OF_EDUCATION.values()
+    assert "Secondary" in PHASE_OF_EDUCATION.values()
+    assert "Does not apply" in RELIGIOUS_CHARACTER.values()
+    assert all(len(d) > 0 for d in (
+        SCHOOL_TYPE, ESTABLISHMENT_STATUS, PHASE_OF_EDUCATION,
+        OFFICIAL_SIXTH_FORM, RELIGIOUS_CHARACTER, ADMISSIONS_POLICY,
+    ))
+
+
+def test_pipeline_copy_is_identical():
+    canonical = (REPO / "backend" / "gias_codes.py").read_text()
+    copy = (REPO / "pipeline" / "scripts" / "gias_codes.py").read_text()
+    assert canonical == copy, (
+        "pipeline/scripts/gias_codes.py has drifted from backend/gias_codes.py — "
+        "regenerate with pipeline/scripts/generate_gias_codes.py and copy the file"
+    )
+
+
+def test_seed_matches_dictionaries():
+    import csv
+    fields = {
+        "school_type": SCHOOL_TYPE,
+        "establishment_status": ESTABLISHMENT_STATUS,
+        "phase_of_education": PHASE_OF_EDUCATION,
+        "official_sixth_form": OFFICIAL_SIXTH_FORM,
+        "religious_character": RELIGIOUS_CHARACTER,
+        "admissions_policy": ADMISSIONS_POLICY,
+    }
+    seed_path = REPO / "pipeline" / "transform" / "seeds" / "gias_code_names.csv"
+    seed: dict[str, dict[int, str]] = {k: {} for k in fields}
+    with open(seed_path, newline="") as fh:
+        for row in csv.DictReader(fh):
+            seed[row["field"]][int(row["code"])] = row["name"]
+    assert seed == fields
+```
+
+- [ ] **Step 2: Run tests to verify they fail**
+
+Run: `cd /Users/tudor/projects/school_compare && uv run --with-requirements requirements.txt --with pytest --with "httpx==0.27.0" python -m pytest backend/tests/test_gias_codes.py -v`
+Expected: FAIL at import — `ModuleNotFoundError: No module named 'backend.gias_codes'`.
+
+- [ ] **Step 3: Write the generation script**
+
+Create `pipeline/scripts/generate_gias_codes.py`:
+
+```python
+"""Generate GIAS code->name dictionaries from the live bulk CSV.
+
+Writes:
+  - backend/gias_codes.py                        (canonical Python module)
+  - pipeline/scripts/gias_codes.py               (byte-identical copy)
+  - pipeline/transform/seeds/gias_code_names.csv (dbt seed for drift test)
+
+Run from the repo root whenever the dbt drift test warns that DfE
+added/renamed a value:  python pipeline/scripts/generate_gias_codes.py
+"""
+
+from __future__ import annotations
+
+import io
+import sys
+from datetime import date, timedelta
+from pathlib import Path
+
+import pandas as pd
+import requests
+
+GIAS_URL = (
+    "https://ea-edubase-api-prod.azurewebsites.net"
+    "/edubase/downloads/public/edubasealldata{date}.csv"
+)
+
+# (CSV code column, CSV name column, python dict name, seed field key)
+FIELDS = [
+    ("TypeOfEstablishment (code)", "TypeOfEstablishment (name)", "SCHOOL_TYPE", "school_type"),
+    ("EstablishmentStatus (code)", "EstablishmentStatus (name)", "ESTABLISHMENT_STATUS", "establishment_status"),
+    ("PhaseOfEducation (code)", "PhaseOfEducation (name)", "PHASE_OF_EDUCATION", "phase_of_education"),
+    ("OfficialSixthForm (code)", "OfficialSixthForm (name)", "OFFICIAL_SIXTH_FORM", "official_sixth_form"),
+    ("ReligiousCharacter (code)", "ReligiousCharacter (name)", "RELIGIOUS_CHARACTER", "religious_character"),
+    ("AdmissionsPolicy (code)", "AdmissionsPolicy (name)", "ADMISSIONS_POLICY", "admissions_policy"),
+]
+
+MODULE_HEADER = '''"""GIAS code -> name dictionaries.
+
+GENERATED by pipeline/scripts/generate_gias_codes.py from the GIAS bulk CSV
+— do not edit by hand; rerun the script when the dbt drift test warns.
+The canonical file is backend/gias_codes.py; pipeline/scripts/gias_codes.py
+must be byte-identical (enforced by backend/tests/test_gias_codes.py).
+"""
+
+from __future__ import annotations
+
+import logging
+import math
+
+logger = logging.getLogger(__name__)
+
+'''
+
+MODULE_FOOTER = '''
+
+def translate(code, mapping: dict[int, str]) -> str | None:
+    """Translate a GIAS code to its display name.
+
+    None/NaN -> None (column absent or suppressed). Unknown codes degrade to
+    "Unknown (<code>)" with a warning so a new DfE value never blanks the UI.
+    """
+    if code is None or (isinstance(code, float) and math.isnan(code)):
+        return None
+    code = int(code)
+    if code not in mapping:
+        logger.warning("Unknown GIAS code %s (not in dictionary)", code)
+        return f"Unknown ({code})"
+    return mapping[code]
+'''
+
+
+def download_csv() -> pd.DataFrame:
+    for day in (date.today(), date.today() - timedelta(days=1)):
+        url = GIAS_URL.format(date=day.strftime("%Y%m%d"))
+        print(f"Downloading {url}")
+        resp = requests.get(url, timeout=300)
+        if resp.status_code == 404:
+            continue
+        resp.raise_for_status()
+        return pd.read_csv(
+            io.StringIO(resp.content.decode("latin-1")),
+            dtype=str, keep_default_na=False,
+        )
+    sys.exit("GIAS CSV not available for today or yesterday")
+
+
+def main() -> None:
+    repo = Path(__file__).resolve().parents[2]
+    df = download_csv()
+
+    module_parts = [MODULE_HEADER]
+    seed_rows: list[tuple[str, int, str]] = []
+
+    for code_col, name_col, dict_name, field_key in FIELDS:
+        pairs = (
+            df[[code_col, name_col]]
+            .loc[lambda d: (d[code_col] != "") & (d[name_col] != "")]
+            .drop_duplicates()
+        )
+        mapping = sorted((int(c), n) for c, n in pairs.itertuples(index=False))
+        dupes = len(mapping) - len({c for c, _ in mapping})
+        if dupes:
+            sys.exit(f"{code_col}: {dupes} codes map to multiple names — investigate before generating")
+        lines = [f"{dict_name}: dict[int, str] = {{"]
+        for code, name in mapping:
+            escaped = name.replace('"', '\\"')
+            lines.append(f'    {code}: "{escaped}",')
+        lines.append("}\n")
+        module_parts.append("\n".join(lines))
+        seed_rows += [(field_key, code, name) for code, name in mapping]
+
+    module = "\n".join(module_parts) + MODULE_FOOTER
+
+    (repo / "backend" / "gias_codes.py").write_text(module)
+    (repo / "pipeline" / "scripts" / "gias_codes.py").write_text(module)
+
+    seed_path = repo / "pipeline" / "transform" / "seeds" / "gias_code_names.csv"
+    with open(seed_path, "w", newline="") as fh:
+        import csv
+        w = csv.writer(fh)
+        w.writerow(["field", "code", "name"])
+        w.writerows(seed_rows)
+
+    print(f"Wrote backend/gias_codes.py, pipeline/scripts/gias_codes.py, {seed_path.name}")
+    print("\nKey codes for the dbt work (Task 3):")
+    for field in ("establishment_status", "phase_of_education", "official_sixth_form"):
+        print(f"  {field}:")
+        for f, code, name in seed_rows:
+            if f == field:
+                print(f"    {code} = {name}")
+
+
+if __name__ == "__main__":
+    main()
+```
+
+- [ ] **Step 4: Run the generator**
+
+Run: `cd /Users/tudor/projects/school_compare && uv run --with pandas --with requests python pipeline/scripts/generate_gias_codes.py`
+Expected: downloads the CSV (~100MB, may take a minute), writes the three files, and prints the status/phase/sixth-form code tables. **Record the printed code tables — Task 3 needs them.** If the download fails twice, report BLOCKED (no network or GIAS outage) rather than inventing dictionary content.
+
+- [ ] **Step 5: Run the tests again**
+
+Run: `cd /Users/tudor/projects/school_compare && uv run --with-requirements requirements.txt --with pytest --with "httpx==0.27.0" python -m pytest backend/tests/test_gias_codes.py -v`
+Expected: 7 passed. If `test_sentinel_names_present` fails, the GIAS vocabulary differs from expectations — inspect the generated module and report DONE_WITH_CONCERNS naming the differing value; do not edit the generated names.
+
+- [ ] **Step 6: Commit**
+
+```bash
+git add pipeline/scripts/generate_gias_codes.py backend/gias_codes.py pipeline/scripts/gias_codes.py pipeline/transform/seeds/gias_code_names.csv backend/tests/test_gias_codes.py
+git commit -m "feat: GIAS code->name dictionaries generated from live bulk CSV
+
+Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>"
+```
+
+---
+
+### Task 2: Tap ingests the (code) columns; staging exposes codes, drops names
+
+**Files:**
+- Modify: `pipeline/plugins/extractors/tap-uk-gias/tap_uk_gias/tap.py` (Singer schema)
+- Modify: `pipeline/transform/models/staging/stg_gias_establishments.sql`
+
+**Interfaces:**
+- Produces: staging columns `school_type_code`, `status_code`, `phase_code`, `official_sixth_form_code`, `religious_character_code`, `admissions_policy_code` (all int) consumed by Task 3. Staging **stops exposing** `school_type`, `status`, `phase`, `official_sixth_form`, `religious_character`, `admissions_policy` (names stay in raw only).
+
+- [ ] **Step 1: Add the six (code) properties to the Singer schema**
+
+In `tap.py`, `GIASEstablishmentsStream.schema`, add each `(code)` property directly above its existing `(name)` sibling:
+
+```python
+        th.Property("TypeOfEstablishment (code)", th.StringType),
+        th.Property("PhaseOfEducation (code)", th.StringType),
+        th.Property("EstablishmentStatus (code)", th.StringType),
+        th.Property("Gender (name)", ...)  # existing line — for placement reference only
+        th.Property("ReligiousCharacter (code)", th.StringType),
+        th.Property("AdmissionsPolicy (code)", th.StringType),
+        th.Property("OfficialSixthForm (code)", th.StringType),
+```
+
+(The exact insertion order doesn't matter — the schema is a dict — but keep each `(code)` adjacent to its `(name)` for readability. Do NOT remove any `(name)` property.)
+
+- [ ] **Step 2: Rewrite the six columns in staging**
+
+In `stg_gias_establishments.sql` `renamed` CTE, replace:
+
+```sql
+        "TypeOfEstablishment (name)"                    as school_type,
+        "PhaseOfEducation (name)"                       as phase,
+        nullif(trim("OfficialSixthForm (name)"), '')    as official_sixth_form,
+        "ReligiousCharacter (name)"                     as religious_character,
+        "AdmissionsPolicy (name)"                       as admissions_policy,
+        "EstablishmentStatus (name)"                    as status,
+```
+
+with:
+
+```sql
+        cast(nullif(trim("TypeOfEstablishment (code)"), '') as integer)  as school_type_code,
+        cast(nullif(trim("PhaseOfEducation (code)"), '') as integer)     as phase_code,
+        cast(nullif(trim("OfficialSixthForm (code)"), '') as integer)    as official_sixth_form_code,
+        cast(nullif(trim("ReligiousCharacter (code)"), '') as integer)   as religious_character_code,
+        cast(nullif(trim("AdmissionsPolicy (code)"), '') as integer)     as admissions_policy_code,
+        cast(nullif(trim("EstablishmentStatus (code)"), '') as integer)  as status_code,
+```
+
+(The name lines are scattered through the CTE — replace each in place; the six name aliases must no longer appear in the model.)
+
+- [ ] **Step 3: Verify statically**
+
+Run:
+```bash
+cd /Users/tudor/projects/school_compare && \
+python3 -c "import ast; ast.parse(open('pipeline/plugins/extractors/tap-uk-gias/tap_uk_gias/tap.py').read()); print('tap OK')" && \
+grep -c "(code)" pipeline/plugins/extractors/tap-uk-gias/tap_uk_gias/tap.py && \
+grep -E "as (school_type|status|phase|official_sixth_form|religious_character|admissions_policy)," pipeline/transform/models/staging/stg_gias_establishments.sql; echo "name-alias grep exit=$? (want 1 = none found)"
+```
+Expected: `tap OK`, code-column count `6`, and the final grep finds nothing (exit 1).
+
+- [ ] **Step 4: Commit**
+
+```bash
+git add pipeline/plugins/extractors/tap-uk-gias/tap_uk_gias/tap.py pipeline/transform/models/staging/stg_gias_establishments.sql
+git commit -m "feat(pipeline): ingest GIAS code columns; staging exposes codes not names
+
+Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>"
+```
+
+---
+
+### Task 3: Marts store codes; dbt tests + drift test
+
+**Files:**
+- Modify: `pipeline/transform/models/marts/dim_school.sql`
+- Modify: `pipeline/transform/models/marts/dim_location.sql`
+- Modify: `pipeline/transform/models/marts/_marts_schema.yml`
+- Create: `pipeline/transform/tests/assert_gias_code_names_match_seed.sql`
+
+**Interfaces:**
+- Consumes: staging code columns from Task 2; code literals from `pipeline/transform/seeds/gias_code_names.csv` (Task 1).
+- Produces: `dim_school` columns `school_type_code`, `status_code`, `phase_code`, `religious_character_code`, `admissions_policy_code` (int) replacing their string columns; `has_sixth_form` unchanged (bool). Task 4's `_MAIN_QUERY` selects these.
+
+**Before writing SQL: open `pipeline/transform/seeds/gias_code_names.csv` and confirm the literals below.** Best-current-knowledge values (VERIFY EACH):
+`establishment_status`: 1 = Open, 3 = "Open, but proposed to close" (2 = Closed, 4 = Proposed to open).
+`phase_of_education`: 0 = Not applicable, 2 = Primary, 4 = Secondary, 7 = All-through.
+`official_sixth_form`: 1 = Has a sixth form, 2 = Does not have a sixth form, 0 = Not applicable.
+If any differ, use the seed's values everywhere below and say so in your report.
+
+- [ ] **Step 1: Rewrite dim_school.sql derivations in code space**
+
+Replace the phase cascade block (`case ... end as phase,`) with:
+
+```sql
+    -- Phase in GIAS code space (see seeds/gias_code_names.csv):
+    -- 2 = Primary, 4 = Secondary, 7 = All-through, 0 = Not applicable.
+    case
+        -- 1. Trust GIAS phase when it's a real value (0 = the catch-all "Not Applicable")
+        when s.phase_code is not null and s.phase_code != 0
+            then s.phase_code
+        -- 2. Infer from statutory age range (independent schools still publish these)
+        when s.statutory_high_age is not null and s.statutory_high_age <= 11 then 2
+        when s.statutory_low_age is not null and s.statutory_low_age >= 11 then 4
+        when s.statutory_low_age is not null and s.statutory_high_age is not null
+             and s.statutory_low_age < 11 and s.statutory_high_age > 11 then 7
+        -- 3. Fallback: infer from school name (covers independents with missing ages)
+        when s.school_name ilike '%primary%'
+             or s.school_name ilike '%infant%'
+             or s.school_name ilike '%junior%'
+             or s.school_name ilike '%preparatory%'
+             or s.school_name ilike '% prep school%'
+             or s.school_name ilike '% prep %'
+            then 2
+        when s.school_name ilike '%secondary%'
+             or s.school_name ilike '%high school%'
+             or s.school_name ilike '%grammar%'
+             or s.school_name ilike '%senior school%'
+             or s.school_name ilike '%upper school%'
+            then 4
+        -- 4. Give up — null renders no phase pill
+        else null
+    end as phase_code,
+```
+
+Replace `s.school_type,` with `s.school_type_code,`; `s.religious_character,` with `s.religious_character_code,`; `s.admissions_policy,` with `s.admissions_policy_code,`; `s.status,` with `s.status_code,`.
+
+Replace the has_sixth_form case with:
+
+```sql
+    -- GIAS OfficialSixthForm in code space: 1 = has, 2 = does not, 0 = N/A.
+    -- Null (rare, new establishments) falls back to the statutory age range.
+    case
+        when s.official_sixth_form_code = 1 then true
+        when s.official_sixth_form_code in (0, 2) then false
+        else coalesce(s.statutory_high_age >= 18, false)
+    end as has_sixth_form,
+```
+
+Replace the status filter with:
+
+```sql
+-- 1 = Open; 3 = Open, but proposed to close (still operating; drops out when
+-- GIAS flips to Closed — marts fully rebuild each run).
+where s.status_code in (1, 3)
+```
+
+- [ ] **Step 2: Same filter in dim_location.sql**
+
+Replace its `where s.status in ('Open', 'Open, but proposed to close')` (and the comment above it) with:
+
+```sql
+-- Must match dim_school's status filter exactly (the API inner-joins the two).
+where s.status_code in (1, 3)
+```
+
+- [ ] **Step 3: Update _marts_schema.yml**
+
+Under `dim_school` columns: rename `phase` → `phase_code` (keep the warn-severity not_null, reword description to mention codes); replace the `status` accepted_values block with:
+
+```yaml
+      - name: status_code
+        description: GIAS EstablishmentStatus code (1 = Open, 3 = Open but proposed to close)
+        tests:
+          - accepted_values:
+              values: [1, 3]
+```
+
+Add warn-severity accepted_values for the other codes, values copied from the seed (school_type/religious/admissions lists are long — paste the full code list from `gias_code_names.csv` for each):
+
+```yaml
+      - name: school_type_code
+        tests:
+          - accepted_values:
+              severity: warn
+              values: [<all school_type codes from the seed>]
+      - name: religious_character_code
+        tests:
+          - accepted_values:
+              severity: warn
+              values: [<all religious_character codes from the seed>]
+      - name: admissions_policy_code
+        tests:
+          - accepted_values:
+              severity: warn
+              values: [<all admissions_policy codes from the seed>]
+```
+
+(`<...>` here means: paste the actual comma-separated integers from the seed file — the lists exist by the time this task runs. Leaving a literal `<...>` in the yml is a task failure.)
+
+`has_sixth_form` tests stay unchanged.
+
+- [ ] **Step 4: Write the drift test**
+
+Create `pipeline/transform/tests/assert_gias_code_names_match_seed.sql`:
+
+```sql
+-- Warn when the live GIAS CSV carries a (code, name) pair we don't have in
+-- the dictionary seed — i.e. DfE added or renamed a value. Fix by rerunning
+-- pipeline/scripts/generate_gias_codes.py and committing the regenerated
+-- dictionaries + seed together.
+{{ config(severity='warn') }}
+
+with raw_pairs as (
+    {% for field_key, code_col, name_col in [
+        ('school_type',          'TypeOfEstablishment (code)',  'TypeOfEstablishment (name)'),
+        ('establishment_status', 'EstablishmentStatus (code)',  'EstablishmentStatus (name)'),
+        ('phase_of_education',   'PhaseOfEducation (code)',     'PhaseOfEducation (name)'),
+        ('official_sixth_form',  'OfficialSixthForm (code)',    'OfficialSixthForm (name)'),
+        ('religious_character',  'ReligiousCharacter (code)',   'ReligiousCharacter (name)'),
+        ('admissions_policy',    'AdmissionsPolicy (code)',     'AdmissionsPolicy (name)')
+    ] %}
+    select distinct
+        '{{ field_key }}' as field,
+        cast(nullif(trim("{{ code_col }}"), '') as integer) as code,
+        nullif(trim("{{ name_col }}"), '') as name
+    from {{ source('raw', 'gias_establishments') }}
+    where nullif(trim("{{ code_col }}"), '') is not null
+      and nullif(trim("{{ name_col }}"), '') is not null
+    {% if not loop.last %}union all{% endif %}
+    {% endfor %}
+)
+
+select r.*
+from raw_pairs r
+left join {{ ref('gias_code_names') }} s
+    on s.field = r.field
+   and s.code = r.code
+   and s.name = r.name
+where s.field is null
+```
+
+- [ ] **Step 5: Verify statically**
+
+Run:
+```bash
+cd /Users/tudor/projects/school_compare && \
+uv run --with pyyaml python -c "import yaml; yaml.safe_load(open('pipeline/transform/models/marts/_marts_schema.yml')); print('yml OK')" && \
+grep -c "_code" pipeline/transform/models/marts/dim_school.sql && \
+grep -n "status_code in (1, 3)" pipeline/transform/models/marts/dim_school.sql pipeline/transform/models/marts/dim_location.sql && \
+grep -rn "s\.status\b\|s\.phase\b\|s\.school_type\b\|s\.religious_character\b\|s\.admissions_policy\b\|official_sixth_form\b" pipeline/transform/models/marts/dim_school.sql | grep -v "_code"; echo "stale-name grep exit=$? (want 1)"
+```
+Expected: `yml OK`, both filters matched, and no stale name-column references (final grep exits 1).
+
+- [ ] **Step 6: Commit**
+
+```bash
+git add pipeline/transform/models/marts/dim_school.sql pipeline/transform/models/marts/dim_location.sql pipeline/transform/models/marts/_marts_schema.yml pipeline/transform/tests/assert_gias_code_names_match_seed.sql
+git commit -m "feat(pipeline): dim_school/dim_location store GIAS codes; seed drift test
+
+Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>"
+```
+
+---
+
+### Task 4: Backend translates at the API boundary
+
+**Files:**
+- Modify: `backend/models.py` (DimSchool columns)
+- Modify: `backend/data_loader.py` (`_MAIN_QUERY` + translation)
+- Test: `backend/tests/test_gias_translation.py` (new)
+
+**Interfaces:**
+- Consumes: `backend/gias_codes.py` dictionaries + `translate` (Task 1); mart code columns (Task 3).
+- Produces: `translate_gias_code_columns(df) -> df` in `backend/data_loader.py`; after `load_school_data_as_dataframe()` the DataFrame carries today's name columns (`phase`, `school_type`, `status`, `religious_denomination`, `admissions_policy`) — every downstream consumer unchanged.
+
+- [ ] **Step 1: Write the failing tests**
+
+Create `backend/tests/test_gias_translation.py`:
+
+```python
+"""API-boundary translation: marts now carry GIAS codes; the DataFrame the
+rest of the backend sees must carry today's name strings."""
+
+import numpy as np
+import pandas as pd
+
+from backend.data_loader import translate_gias_code_columns
+from backend.gias_codes import ESTABLISHMENT_STATUS, PHASE_OF_EDUCATION
+
+
+def _code_for(mapping, name):
+    return next(c for c, n in mapping.items() if n == name)
+
+
+def test_codes_become_todays_names():
+    df = pd.DataFrame([{
+        "urn": 1,
+        "phase_code": float(_code_for(PHASE_OF_EDUCATION, "Primary")),
+        "school_type_code": np.nan,
+        "status_code": float(_code_for(ESTABLISHMENT_STATUS, "Open, but proposed to close")),
+        "religious_character_code": np.nan,
+        "admissions_policy_code": np.nan,
+    }])
+    out = translate_gias_code_columns(df)
+    row = out.iloc[0]
+    assert row["phase"] == "Primary"
+    assert row["status"] == "Open, but proposed to close"
+    assert row["school_type"] is None
+    assert row["religious_denomination"] is None
+    assert row["admissions_policy"] is None
+
+
+def test_unknown_code_degrades_not_blanks():
+    df = pd.DataFrame([{"urn": 1, "phase_code": 9999.0}])
+    out = translate_gias_code_columns(df)
+    assert out.iloc[0]["phase"] == "Unknown (9999)"
+
+
+def test_missing_code_columns_are_a_noop():
+    """Old-schema DataFrames (tests, pre-pipeline DBs) pass through untouched."""
+    df = pd.DataFrame([{"urn": 1, "phase": "Primary", "status": "Open"}])
+    out = translate_gias_code_columns(df)
+    assert out.iloc[0]["phase"] == "Primary"
+    assert out.iloc[0]["status"] == "Open"
+```
+
+- [ ] **Step 2: Run to verify failure**
+
+Run: `cd /Users/tudor/projects/school_compare && uv run --with-requirements requirements.txt --with pytest --with "httpx==0.27.0" python -m pytest backend/tests/test_gias_translation.py -v`
+Expected: FAIL — `ImportError: cannot import name 'translate_gias_code_columns'`.
+
+- [ ] **Step 3: Implement translation in data_loader.py**
+
+Add near the top of `backend/data_loader.py` (after existing imports):
+
+```python
+from .gias_codes import (
+    ADMISSIONS_POLICY,
+    ESTABLISHMENT_STATUS,
+    PHASE_OF_EDUCATION,
+    RELIGIOUS_CHARACTER,
+    SCHOOL_TYPE,
+    translate,
+)
+
+# mart code column -> (API name column, dictionary)
+_GIAS_CODE_COLUMNS = {
+    "phase_code": ("phase", PHASE_OF_EDUCATION),
+    "school_type_code": ("school_type", SCHOOL_TYPE),
+    "status_code": ("status", ESTABLISHMENT_STATUS),
+    "religious_character_code": ("religious_denomination", RELIGIOUS_CHARACTER),
+    "admissions_policy_code": ("admissions_policy", ADMISSIONS_POLICY),
+}
+
+
+def translate_gias_code_columns(df: pd.DataFrame) -> pd.DataFrame:
+    """Map GIAS code columns to today's name columns (API contract).
+
+    Runs immediately after pd.read_sql so every downstream consumer —
+    filters, PHASE_GROUPS, payloads, /api/filters — keeps seeing names.
+    DataFrames without the code columns (old schema, test fixtures) pass
+    through unchanged.
+    """
+    for code_col, (name_col, mapping) in _GIAS_CODE_COLUMNS.items():
+        if code_col in df.columns:
+            df[name_col] = df[code_col].map(lambda c: translate(c, mapping))
+    return df
+```
+
+- [ ] **Step 4: Switch `_MAIN_QUERY` to code columns and call the translation**
+
+In `_MAIN_QUERY` replace:
+`s.phase,` → `s.phase_code,` · `s.school_type,` → `s.school_type_code,` · `s.religious_character AS religious_denomination,` → `s.religious_character_code,` · `s.admissions_policy,` → `s.admissions_policy_code,` · `s.status,` → `s.status_code,`
+
+In `load_school_data_as_dataframe()`, insert the call immediately after the empty-check and **before** the existing `normalize_school_type` line:
+
+```python
+    if df.empty:
+        return df
+
+    df = translate_gias_code_columns(df)
+
+    # Build address string
+    ...
+    # Normalize school type  (existing line — now normalises the translated name)
+    df["school_type"] = df["school_type"].apply(normalize_school_type)
+```
+
+- [ ] **Step 5: Update DimSchool in models.py**
+
+Replace `phase = Column(String(100))`, `school_type = Column(String(100))`, `religious_character = Column(String(100))`, `admissions_policy = Column(String(50))`, `status = Column(String(50))` with:
+
+```python
+    phase_code = Column(Integer)
+    school_type_code = Column(Integer)
+    religious_character_code = Column(Integer)
+    admissions_policy_code = Column(Integer)
+    status_code = Column(Integer)
+```
+
+Then check nothing else references the removed attributes:
+```bash
+grep -rn "\.phase\b\|\.school_type\b\|\.religious_character\b\|\.admissions_policy\b\|\.status\b" backend/*.py | grep -i "dimschool\|DimSchool" 
+```
+Expected: no hits (the backend reads via `_MAIN_QUERY`, not ORM attributes). If there are hits, update them to the `_code` columns + translation and note it in your report.
+
+- [ ] **Step 6: Run the new tests and the whole backend suite**
+
+Run: `cd /Users/tudor/projects/school_compare && uv run --with-requirements requirements.txt --with pytest --with "httpx==0.27.0" python -m pytest backend/tests -v`
+Expected: all pass — 3 new + all pre-existing (their fixtures carry name columns; translation is a no-op on them).
+
+- [ ] **Step 7: Commit**
+
+```bash
+git add backend/models.py backend/data_loader.py backend/tests/test_gias_translation.py
+git commit -m "feat(api): translate GIAS codes to names at the query boundary
+
+Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>"
+```
+
+---
+
+### Task 5: Typesense sync translates before indexing
+
+**Files:**
+- Modify: `pipeline/scripts/sync_typesense.py`
+
+**Interfaces:**
+- Consumes: `pipeline/scripts/gias_codes.py` (Task 1), mart code columns (Task 3).
+- Produces: identical Typesense documents to today (facet values are names).
+
+- [ ] **Step 1: Switch the SELECT and translate**
+
+In `sync_typesense.py`: add at the top (the DAG runs `python scripts/sync_typesense.py`, so `scripts/` is `sys.path[0]` and a plain import works):
+
+```python
+from gias_codes import PHASE_OF_EDUCATION, RELIGIOUS_CHARACTER, SCHOOL_TYPE, translate
+```
+
+In the SQL, replace `s.phase,` → `s.phase_code,`, `s.school_type,` → `s.school_type_code,`, `s.religious_character,` → `s.religious_character_code,`.
+
+In the document builder, replace:
+
+```python
+        "phase": row["phase"] or "",
+        "school_type": row["school_type"] or "",
+```
+with:
+```python
+        "phase": translate(row["phase_code"], PHASE_OF_EDUCATION) or "",
+        "school_type": translate(row["school_type_code"], SCHOOL_TYPE) or "",
+```
+and:
+```python
+    if row.get("religious_character"):
+        doc["religious_character"] = row["religious_character"]
+```
+with:
+```python
+    religious_character = translate(row.get("religious_character_code"), RELIGIOUS_CHARACTER)
+    if religious_character:
+        doc["religious_character"] = religious_character
+```
+
+- [ ] **Step 2: Verify statically**
+
+Run:
+```bash
+cd /Users/tudor/projects/school_compare && \
+python3 -c "import ast; ast.parse(open('pipeline/scripts/sync_typesense.py').read()); print('sync OK')" && \
+grep -n "row\[\"phase\"\]\|row\[\"school_type\"\]\|row\[\"religious_character\"\]" pipeline/scripts/sync_typesense.py; echo "stale grep exit=$? (want 1)"
+```
+Expected: `sync OK`, no stale name-column row accesses.
+
+- [ ] **Step 3: Commit**
+
+```bash
+git add pipeline/scripts/sync_typesense.py
+git commit -m "feat(pipeline): typesense sync translates GIAS codes before indexing
+
+Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>"
+```
+
+---
+
+### Task 6: Spec status, PR, deploy runbook
+
+**Files:**
+- Modify: `docs/superpowers/specs/2026-07-09-gias-code-dictionaries-design.md` (status line)
+
+- [ ] **Step 1: Mark the spec implemented**
+
+Change `**Status:** Approved design` to `**Status:** Implemented 2026-07-09 — see docs/superpowers/plans/2026-07-09-gias-code-dictionaries.md`.
+
+- [ ] **Step 2: Commit and push**
+
+```bash
+git add docs/superpowers/specs/2026-07-09-gias-code-dictionaries-design.md
+git commit -m "docs: mark GIAS code dictionaries spec implemented
+
+Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>"
+git push -u origin feat/gias-code-dictionaries
+```
+
+- [ ] **Step 3: Open the PR (Gitea API via git credential fill — token-header auth 401s)**
+
+Title: `feat: GIAS classification fields stored as codes, translated in code`
+Body must include: (1) API contract unchanged — names still served, translation at the query boundary; (2) the **deploy runbook: merge → deploy → trigger `school_data_daily` immediately** (accepted empty-API window until the marts rebuild — spec §7); (3) dictionary maintenance loop (dbt drift test warns → rerun `generate_gias_codes.py` → commit regenerated files); (4) no frontend/e2e changes. End with the standard generation footer.
+
+- [ ] **Step 4: Watch CI**
+
+All PR checks must pass. Do not merge — merging triggers the deploy window; the human runs the runbook.
@@ -0,0 +1,591 @@
+# Compare-Screen Data Foundation (Pipeline PR) Implementation Plan
+
+> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
+
+**Goal:** Land every pipeline/dbt change the compare-screen redesign needs (spec §5 + §8 of `docs/superpowers/specs/2026-07-11-compare-screen-redesign-design.md`): promote raw-but-unstored fields to marts, close the national-averages gaps, and wire the Ofsted report-card columns.
+
+**Architecture:** Meltano Singer taps load `raw.*` tables; dbt builds `staging` → `marts` (read-only for the backend). All changes here are additive columns/rows — no breaking changes to existing marts. The full `dbt build` runs on the server via the Airflow DAGs; locally we gate with `dbt parse` (no DB needed) plus network-only diagnostic scripts.
+
+**Tech Stack:** Python (Singer SDK taps), dbt-postgres ~1.10 (invoked as `python -m dbt.cli.main`), Meltano, PostgreSQL.
+
+## Global Constraints
+
+- **No new external sources** (spec §5): only fields already in the `raw` schema or in files the taps already download. The one sanctioned tap change is the Ofsted MI report-card columns (spec §5, §8.4) and the legacy-KS2 year addition (same DfE performance-tables source).
+- **Additive only:** never rename or drop existing mart columns; the backend maps them 1:1 in `backend/models.py`.
+- **Never push to `main`.** Branch: `feat/compare-data-foundation`; PR checks must pass.
+- Backend `models.py` changes belong to the follow-up backend PR, not this one.
+- dbt invocation is always `python -m dbt.cli.main` (a bare `dbt` resolves to the wrong binary — see `pipeline/dags/school_data_pipeline.py:27`).
+- EES suppression codes `z`/`c`/`x` must go through the `safe_numeric` macro.
+- Computed benchmarks (FSM/EAL/SEN medians, disadvantaged national average) are **backend work** (spec §5) — explicitly out of scope here.
+
+---
+
+### Task 0: Create the branch
+
+**Files:** none
+
+- [ ] **Step 1:** `git checkout main && git pull && git checkout -b feat/compare-data-foundation`
+
+---
+
+### Task 1: Diagnostics — pin the three unknowns
+
+The spec flags three facts we must confirm from the actual files before wiring code: (a) why `gps_expected_pct`/`science_expected_pct` are NULL in `marts.fact_ks2_national_averages` despite being mapped end-to-end; (b) what the KS2 attainment long file calls its subjects/years for 2021/22 and 2022/23 (subject-level 2022/23 is NULL in prod; school-level 2021/22 is absent); (c) the exact report-card column headers in the current Ofsted MI CSV.
+
+**Files:**
+- Create: `pipeline/scripts/diagnose_compare_gaps.py`
+
+**Interfaces:**
+- Produces: a printed findings report; Tasks 5, 6, 7 consume the confirmed column/label names. Precedent: `pipeline/scripts/diagnose_ees_ks4.py`.
+
+- [ ] **Step 1: Write the diagnostic script**
+
+```python
+"""Diagnose the three data gaps blocking the compare-screen redesign.
+
+Run from repo root (network access required, no DB needed):
+    python pipeline/scripts/diagnose_compare_gaps.py
+"""
+import io
+import re
+import sys
+import zipfile
+
+import pandas as pd
+import requests
+
+sys.path.insert(0, "pipeline/plugins/extractors/tap-uk-ees")
+sys.path.insert(0, "pipeline/plugins/extractors/tap-uk-ofsted")
+from tap_uk_ees.tap import (  # noqa: E402
+    _KS2_NATIONAL_COL_MAP,
+    _KS2_NATIONAL_CSV_URL,
+    download_release_zip,
+    get_all_releases,
+)
+from tap_uk_ofsted.tap import discover_csv_url  # noqa: E402
+
+TIMEOUT = 120
+
+
+def check_national_gps_science():
+    print("\n=== (a) National catalogue CSV: GPS/science columns ===")
+    resp = requests.get(_KS2_NATIONAL_CSV_URL, timeout=TIMEOUT)
+    resp.raise_for_status()
+    df = pd.read_csv(io.BytesIO(resp.content), dtype=str, keep_default_na=False)
+    df.columns = [c.strip().lower() for c in df.columns]
+    for csv_col in ("pt_gps_exp", "pt_scita_exp", "avg_readscore", "avg_matscore", "avg_gpsscore"):
+        status = "PRESENT" if csv_col in df.columns else "MISSING"
+        print(f"  {csv_col}: {status}")
+    gps_like = [c for c in df.columns if "gps" in c or "scita" in c or "sci" in c]
+    print(f"  all gps/science-ish columns: {gps_like}")
+    nat = df[df.get("geographic_level", "").str.strip().str.lower() == "national"]
+    print(f"  national rows time_periods: {sorted(nat['time_period'].unique())}")
+    # Sample the values our map would read for the latest year
+    latest = nat[nat["time_period"] == nat["time_period"].max()]
+    for csv_col, field in _KS2_NATIONAL_COL_MAP.items():
+        val = latest.iloc[0].get(csv_col, "<col missing>") if len(latest) else "<no row>"
+        print(f"  {field} <- {csv_col} = {val!r}")
+
+
+def check_ks2_attainment_years_subjects():
+    print("\n=== (b) EES KS2 attainment: years & subject labels ===")
+    releases = get_all_releases("key-stage-2-attainment")
+    print(f"  releases found: {[r['time_period'] for r in releases]}")
+    for release in releases:
+        zf = download_release_zip(release["id"])
+        name = next((n for n in zf.namelist()
+                     if "ks2_school_attainment_data" in n and n.endswith(".csv")), None)
+        if not name:
+            print(f"  {release['time_period']}: NO school attainment CSV in ZIP")
+            continue
+        with zf.open(name) as f:
+            df = pd.read_csv(f, dtype=str, keep_default_na=False, nrows=200000)
+        years = sorted(df["time_period"].unique())
+        subjects = sorted(df["subject"].unique())
+        print(f"  release {release['time_period']}: time_periods={years}")
+        print(f"    subjects={subjects}")
+
+
+def check_ofsted_report_card_columns():
+    print("\n=== (c) Ofsted MI CSV: report-card columns ===")
+    url = discover_csv_url()
+    print(f"  MI file: {url}")
+    resp = requests.get(url, timeout=TIMEOUT)
+    resp.raise_for_status()
+    df = pd.read_csv(io.BytesIO(resp.content), dtype=str, keep_default_na=False, nrows=5)
+    rc_like = [c for c in df.columns
+               if re.search(r"report card|inclusion|curriculum|achievement|safeguard|well.?being|governance", c, re.I)]
+    print(f"  candidate report-card columns ({len(rc_like)}):")
+    for c in rc_like:
+        print(f"    - {c!r}")
+
+
+if __name__ == "__main__":
+    check_national_gps_science()
+    check_ks2_attainment_years_subjects()
+    check_ofsted_report_card_columns()
+```
+
+Note: if `_KS2_NATIONAL_CSV_URL` is named differently in `tap_uk_ees/tap.py` (it is defined near the `_KS2_NATIONAL_COL_MAP` around line ~490), import whatever constant holds the catalogue CSV URL.
+
+- [ ] **Step 2: Run it and record findings**
+
+Run: `python pipeline/scripts/diagnose_compare_gaps.py 2>&1 | tee /tmp/compare-gaps-findings.txt`
+Expected: three sections printed. Paste the findings as a comment block at the bottom of the script (so they're committed evidence), e.g. `# FINDINGS 2026-07-12: pt_gps_exp MISSING (actual col: ...), 202122 present in release X, rc columns: [...]`.
+
+- [ ] **Step 3: Commit**
+
+```bash
+git add pipeline/scripts/diagnose_compare_gaps.py
+git commit -m "chore(pipeline): diagnostic for compare-screen data gaps"
+```
+
+---
+
+### Task 2: Admissions preference detail → mart
+
+Staging already extracts `second_preference_offers`, `third_preference_offers`, `total_offers` (`stg_ees_admissions.sql:26-29`) — the mart drops them. The cross-LA fields are declared in the tap (`all_applications_from_another_LA`, `offers_to_applicants_from_another_LA`) but not selected in staging.
+
+**Files:**
+- Modify: `pipeline/transform/models/staging/stg_ees_admissions.sql` (after line 33, in `renamed`)
+- Modify: `pipeline/transform/models/marts/fact_admissions.sql`
+- Modify: `pipeline/transform/models/marts/_marts_schema.yml` (fact_admissions block, ~line 120)
+
+**Interfaces:**
+- Produces mart columns: `total_offers int`, `second_preference_offers int`, `third_preference_offers int`, `cross_la_applications int`, `cross_la_offers int`. The backend PR will map these in `FactAdmissions`.
+
+- [ ] **Step 1: Add cross-LA columns to staging**
+
+In `stg_ees_admissions.sql`, after the `first_preference_applications` line (line 33):
+
+```sql
+        -- Cross-borough demand: applications naming this school from families
+        -- living in another local authority, and offers made to them.
+        {{ safe_numeric('"all_applications_from_another_LA"') }}::integer as cross_la_applications,
+        {{ safe_numeric('"offers_to_applicants_from_another_LA"') }}::integer as cross_la_offers,
+```
+
+(Quote the identifiers — the tap emits them with mixed case, same trap as `FSM_eligible_percent`, see the header comment in that file. If `dbt parse` or the DAG run later shows the raw columns are lower-cased in Postgres, drop the double quotes.)
+
+- [ ] **Step 2: Pass everything through the mart**
+
+Replace the full select list in `fact_admissions.sql`:
+
+```sql
+-- Mart: School admissions — one row per URN per year
+
+select
+    urn,
+    year,
+    school_phase,
+    places_offered,
+    total_offers,
+    total_applications,
+    first_preference_applications,
+    first_preference_offers,
+    second_preference_offers,
+    third_preference_offers,
+    cross_la_applications,
+    cross_la_offers,
+    first_preference_offer_pct,
+    oversubscription_ratio,
+    oversubscribed,
+    admissions_policy
+from {{ ref('stg_ees_admissions') }}
+```
+
+- [ ] **Step 3: Add schema tests**
+
+In `_marts_schema.yml` under `fact_admissions.columns`, append:
+
+```yaml
+      - name: second_preference_offers
+      - name: third_preference_offers
+      - name: cross_la_applications
+      - name: cross_la_offers
+      - name: total_offers
+```
+
+- [ ] **Step 4: Parse gate**
+
+Run: `cd pipeline/transform && python -m dbt.cli.main parse --profiles-dir .`
+Expected: `Done.` with no compilation errors.
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add pipeline/transform/models/staging/stg_ees_admissions.sql pipeline/transform/models/marts/fact_admissions.sql pipeline/transform/models/marts/_marts_schema.yml
+git commit -m "feat(pipeline): admissions preference breakdown and cross-LA demand in marts"
+```
+
+---
+
+### Task 3: KS2 progress confidence intervals + writing working-towards
+
+The tap already emits `progress_measure_lower_conf_interval`, `progress_measure_upper_conf_interval`, `working_towards_expected_standard_pupil_percent` (tap.py:203-206). The staging pivot drops them. These power the CI-based Above/Average/Below progress chips (spec §8, first-review item on statistical honesty).
+
+**Files:**
+- Modify: `pipeline/transform/models/staging/stg_ees_ks2.sql` (inside the `pivoted` CTE, next to each subject's `progress_measure_score` case, lines ~41/55/72, and in the final select ~lines 145-152)
+- Modify: `pipeline/transform/models/marts/fact_ks2_performance.sql`
+- Modify: `pipeline/transform/models/marts/_marts_schema.yml` (fact_ks2_performance block, ~line 82)
+
+**Interfaces:**
+- Produces mart columns: `reading_progress_lower_ci`, `reading_progress_upper_ci`, `writing_progress_lower_ci`, `writing_progress_upper_ci`, `maths_progress_lower_ci`, `maths_progress_upper_ci` (float), `writing_working_towards_pct` (float).
+
+- [ ] **Step 1: Add pivot cases in staging**
+
+After the `reading_progress` case (line ~41), add:
+
+```sql
+        max(case when subject = 'Reading'
+                  and breakdown_topic = 'All pupils' and breakdown = 'Total'
+            then {{ safe_numeric('progress_measure_lower_conf_interval') }} end) as reading_progress_lower_ci,
+        max(case when subject = 'Reading'
+                  and breakdown_topic = 'All pupils' and breakdown = 'Total'
+            then {{ safe_numeric('progress_measure_upper_conf_interval') }} end) as reading_progress_upper_ci,
+```
+
+After the `writing_progress` case (line ~55), add:
+
+```sql
+        max(case when subject = 'Writing'
+                  and breakdown_topic = 'All pupils' and breakdown = 'Total'
+            then {{ safe_numeric('progress_measure_lower_conf_interval') }} end) as writing_progress_lower_ci,
+        max(case when subject = 'Writing'
+                  and breakdown_topic = 'All pupils' and breakdown = 'Total'
+            then {{ safe_numeric('progress_measure_upper_conf_interval') }} end) as writing_progress_upper_ci,
+        max(case when subject = 'Writing'
+                  and breakdown_topic = 'All pupils' and breakdown = 'Total'
+            then {{ safe_numeric('working_towards_expected_standard_pupil_percent') }} end) as writing_working_towards_pct,
+```
+
+After the `maths_progress` case (line ~72), add:
+
+```sql
+        max(case when subject = 'Maths'
+                  and breakdown_topic = 'All pupils' and breakdown = 'Total'
+            then {{ safe_numeric('progress_measure_lower_conf_interval') }} end) as maths_progress_lower_ci,
+        max(case when subject = 'Maths'
+                  and breakdown_topic = 'All pupils' and breakdown = 'Total'
+            then {{ safe_numeric('progress_measure_upper_conf_interval') }} end) as maths_progress_upper_ci,
+```
+
+Then add the seven new columns to the model's final select (next to the existing `p.reading_progress` / `p.writing_progress` / `p.maths_progress` lines ~145-152):
+
+```sql
+    p.reading_progress_lower_ci,
+    p.reading_progress_upper_ci,
+    p.writing_progress_lower_ci,
+    p.writing_progress_upper_ci,
+    p.writing_working_towards_pct,
+    p.maths_progress_lower_ci,
+    p.maths_progress_upper_ci,
+```
+
+- [ ] **Step 2: Pass through the mart**
+
+In `fact_ks2_performance.sql`, add the same seven column names to the select list immediately after the existing `maths_progress` line (this mart selects staging columns by name; match the file's existing alias style — if columns are selected bare, add them bare).
+
+- [ ] **Step 3: Schema tests**
+
+In `_marts_schema.yml` under `fact_ks2_performance.columns`, append the seven names (no tests beyond presence — values are legitimately NULL for 2023/24+ since progress measures ended with 2022/23, spec §4.3):
+
+```yaml
+      - name: reading_progress_lower_ci
+      - name: reading_progress_upper_ci
+      - name: writing_progress_lower_ci
+      - name: writing_progress_upper_ci
+      - name: writing_working_towards_pct
+      - name: maths_progress_lower_ci
+      - name: maths_progress_upper_ci
+```
+
+- [ ] **Step 4: Parse gate**
+
+Run: `cd pipeline/transform && python -m dbt.cli.main parse --profiles-dir .`
+Expected: `Done.`
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add pipeline/transform/models/staging/stg_ees_ks2.sql pipeline/transform/models/marts/fact_ks2_performance.sql pipeline/transform/models/marts/_marts_schema.yml
+git commit -m "feat(pipeline): KS2 progress confidence intervals and writing working-towards"
+```
+
+---
+
+### Task 4: KS4 — Progress 8 banding and disadvantage gaps
+
+The tap's `ees_ks4_info` stream already declares `progress8_banding` (DfE's own "well above average … well below average" label — the ready-made secondary chip), `attainment8_diffn` and `progress8_diffn` (tap.py:338-340). Wire them through staging into the mart.
+
+**Files:**
+- Modify: `pipeline/transform/models/staging/stg_ees_ks4.sql` (the CTE that reads `ees_ks4_info` — the same one that already surfaces `sen_pct`; add three columns to its select and to the final joined select)
+- Modify: `pipeline/transform/models/marts/fact_ks4_performance.sql` (add after `progress_8_upper_ci`)
+- Modify: `pipeline/transform/models/marts/_marts_schema.yml` (fact_ks4_performance block, ~line 93)
+
+**Interfaces:**
+- Produces mart columns: `progress_8_banding text`, `attainment_8_disadvantage_gap float`, `progress_8_disadvantage_gap float`.
+
+- [ ] **Step 1: Staging — select from the info source**
+
+In the info CTE of `stg_ees_ks4.sql` add:
+
+```sql
+        nullif(trim(progress8_banding), '') as progress_8_banding,
+        {{ safe_numeric('attainment8_diffn') }} as attainment_8_disadvantage_gap,
+        {{ safe_numeric('progress8_diffn') }} as progress_8_disadvantage_gap,
+```
+
+and add the three names to the model's final select (aliased the same way the CTE's other columns are).
+
+- [ ] **Step 2: Mart passthrough**
+
+In `fact_ks4_performance.sql`, after the `progress_8_upper_ci,` line:
+
+```sql
+    progress_8_banding,
+    attainment_8_disadvantage_gap,
+    progress_8_disadvantage_gap,
+```
+
+- [ ] **Step 3: Schema tests** — append the three names under `fact_ks4_performance.columns`, plus an accepted-values guard that tolerates NULL:
+
+```yaml
+      - name: progress_8_banding
+        tests:
+          - accepted_values:
+              values: ['Well above average', 'Above average', 'Average', 'Below average', 'Well below average']
+              config:
+                where: "progress_8_banding is not null"
+      - name: attainment_8_disadvantage_gap
+      - name: progress_8_disadvantage_gap
+```
+
+(If the DAG run later shows different capitalisation in the data, fix the accepted values to match the data, not vice versa.)
+
+- [ ] **Step 4: Parse gate** — `cd pipeline/transform && python -m dbt.cli.main parse --profiles-dir .` → `Done.`
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add pipeline/transform/models/staging/stg_ees_ks4.sql pipeline/transform/models/marts/fact_ks4_performance.sql pipeline/transform/models/marts/_marts_schema.yml
+git commit -m "feat(pipeline): Progress 8 banding and KS4 disadvantage gaps in marts"
+```
+
+---
+
+### Task 5: National averages — 2015/16 row and GPS/science/scaled-score fix
+
+Two changes. (1) `stg_ees_ks2_national.sql:34` filters `>= 201617`, which is exactly why the England line starts a year late (2015/16 RWM = 53% exists in the catalogue). (2) GPS/science expected are NULL in prod despite full end-to-end mapping — Task 1's findings say whether the catalogue CSV column names differ from `_KS2_NATIONAL_COL_MAP` (`pt_gps_exp`, `pt_scita_exp`) or whether values are suppressed at source.
+
+**Files:**
+- Modify: `pipeline/transform/models/staging/stg_ees_ks2_national.sql:34`
+- Modify (conditional on Task 1 findings): `pipeline/plugins/extractors/tap-uk-ees/tap_uk_ees/tap.py` (`_KS2_NATIONAL_COL_MAP`)
+
+**Interfaces:**
+- Produces: a 201516 row in `marts.fact_ks2_national_averages`; non-NULL `gps_expected_pct`, `science_expected_pct`, `reading_avg_score`, `maths_avg_score`, `gps_avg_score` for years the DfE publishes them. Backend/frontend consume via `/api/national-averages` unchanged (additive year + newly non-NULL fields).
+
+- [ ] **Step 1: Widen the year filter**
+
+In `stg_ees_ks2_national.sql`, change line 34:
+
+```sql
+  and cast(trim(time_period) as integer) >= 201516
+```
+
+(2015/16 was the first year of the current expected-standard tests; nothing earlier is comparable, so keep a floor.)
+
+- [ ] **Step 2: Fix the column map per Task 1 findings**
+
+If Task 1 reported the actual CSV column names for GPS/science/scaled scores differ, update `_KS2_NATIONAL_COL_MAP` in `tap.py` accordingly, e.g. (illustrative — use the diagnosed names):
+
+```python
+_KS2_NATIONAL_COL_MAP = {
+    # ... existing entries ...
+    "pt_gps_exp": "gps_expected_pct",      # replace key with diagnosed name
+    "pt_scita_exp": "science_expected_pct",  # replace key with diagnosed name
+}
+```
+
+If Task 1 showed the columns are present but suppressed (`x`) at national level for all years, instead delete the two entries from the map, delete the corresponding lines from `stg_ees_ks2_national.sql` and `fact_ks2_national_averages.sql`, and record in the PR description that GPS/science England ticks stay "not in dataset" (the mockups already carry that caveat).
+
+- [ ] **Step 3: Parse gate** — `cd pipeline/transform && python -m dbt.cli.main parse --profiles-dir .` → `Done.`
+
+- [ ] **Step 4: Commit**
+
+```bash
+git add pipeline/transform/models/staging/stg_ees_ks2_national.sql pipeline/plugins/extractors/tap-uk-ees/tap_uk_ees/tap.py
+git commit -m "fix(pipeline): include 2015/16 national averages; fix GPS/science national mapping"
+```
+
+---
+
+### Task 6: Legacy KS2 — load the 2021/22 school-level year
+
+School-level 2021/22 exists in DfE performance-tables archives (same source as the four legacy years already loaded) but in neither our legacy config (stops at 201819, `pipeline/meltano.yml:33-37`) nor EES (starts 2022/23) — unless Task 1's finding (b) showed an EES release carrying 202122, in which case skip this task and note why in the PR.
+
+The legacy URLs point at the self-hosted filebrowser (`10.0.1.224:8081`) — **the 2021/22 DfE archive must be uploaded there first; this is the one human dependency in this plan.**
+
+**Files:**
+- Modify: `pipeline/meltano.yml` (legacy_ks2_urls block, line ~33)
+
+**Interfaces:**
+- Produces: `raw.legacy_ks2` rows with `year = '202122'`, flowing through `stg_legacy_ks2` → `fact_ks2_performance` unchanged (the stream maps old column names already; 2021/22 CSVs use the same `PTRWM_EXP`-style headers as 2018/19).
+
+- [ ] **Step 1: Verify the 2021/22 CSV headers match `_LEGACY_KS2_COLUMN_MAP`**
+
+Download the DfE 2021/22 KS2 revised archive (gov.uk "Compare School Performance data download": 2021-2022 all-schools ZIP), then:
+
+Run: `python -c "import zipfile,io,pandas as pd; zf=zipfile.ZipFile('/path/to/2021-2022.zip'); n=[x for x in zf.namelist() if 'ks2final' in x.lower() and x.endswith('.csv')][0]; df=pd.read_csv(zf.open(n), dtype=str, nrows=5); import sys; sys.path.insert(0,'pipeline/plugins/extractors/tap-uk-ees'); from tap_uk_ees.tap import _LEGACY_KS2_COLUMN_MAP as m; missing=[c for c in m if c not in df.columns]; print('missing legacy columns:', missing)"`
+Expected: `missing legacy columns: []` (progress columns `READPROG` etc. may legitimately be missing/blank in 2021/22 — acceptable, they load as NULL).
+
+- [ ] **Step 2: Upload the archive to the filebrowser and add the config entry**
+
+In `pipeline/meltano.yml` under `legacy_ks2_urls`, add (with the real share URL from the filebrowser upload):
+
+```yaml
+          "202122": "http://10.0.1.224:8081/filebrowser/api/public/dl/<SHARE_ID>?inline=true"
+```
+
+- [ ] **Step 3: Commit**
+
+```bash
+git add pipeline/meltano.yml
+git commit -m "feat(pipeline): load 2021/22 school-level KS2 from legacy performance tables"
+```
+
+- [ ] **Step 4 (only if Task 1(b) showed 2022/23 subject labels differ):** widen the subject matchers in `stg_ees_ks2.sql` the same way GPS already is (`subject ilike '%grammar%' or subject = 'GPS'`), e.g. `subject in ('Reading', 'reading')` → use the diagnosed labels. Parse-gate and commit as `fix(pipeline): match 2022/23 KS2 subject labels`.
+
+---
+
+### Task 7: Ofsted report-card columns (rc_*)
+
+Resolves the tap TODO (`stg_ofsted_inspections.sql:37`). The marts/backed columns already exist as stubs; this wires real values. Uses Task 1(c)'s confirmed MI column names — the candidates below follow the MI file's existing naming style and must be corrected against the diagnostic output.
+
+**Files:**
+- Modify: `pipeline/plugins/extractors/tap-uk-ofsted/tap_uk_ofsted/tap.py` (COLUMN_PRIORITY ~line 19-72, schema ~line 100-114)
+- Create: `pipeline/transform/macros/parse_report_card_grade.sql`
+- Modify: `pipeline/transform/models/staging/stg_ofsted_inspections.sql:36-46`
+
+**Interfaces:**
+- Produces mart columns (already declared in `fact_ofsted_inspection`): `rc_safeguarding_met boolean`, and `rc_inclusion` … `rc_sixth_form` as integers on the 5-point scale `1=Exceptional, 2=Strong standard, 3=Expected standard, 4=Needs attention/Attention needed, 5=Urgent improvement`. The backend translates codes to labels (same pattern as `gias_codes.py`), verifying wording against Ofsted's published toolkit (spec §8.4).
+
+- [ ] **Step 1: Add tap column mappings**
+
+In `COLUMN_PRIORITY` add (replace candidate strings with Task 1(c)'s exact headers — keep them as priority lists so older files degrade to blank):
+
+```python
+    "rc_safeguarding_met": ["Report card safeguarding", "Safeguarding"],
+    "rc_inclusion": ["Report card inclusion", "Inclusion"],
+    "rc_curriculum_teaching": ["Report card curriculum and teaching", "Curriculum and teaching"],
+    "rc_achievement": ["Report card achievement", "Achievement"],
+    "rc_attendance_behaviour": ["Report card attendance and behaviour", "Attendance and behaviour"],
+    "rc_personal_development": ["Report card personal development and well-being", "Personal development and well-being"],
+    "rc_leadership_governance": ["Report card leadership and governance", "Leadership and governance"],
+    "rc_early_years": ["Report card early years", "Early years"],
+    "rc_sixth_form": ["Report card sixth form", "Sixth form"],
+```
+
+And in the stream schema (next to `report_url`, ~line 114):
+
+```python
+        th.Property("rc_safeguarding_met", th.StringType),
+        th.Property("rc_inclusion", th.StringType),
+        th.Property("rc_curriculum_teaching", th.StringType),
+        th.Property("rc_achievement", th.StringType),
+        th.Property("rc_attendance_behaviour", th.StringType),
+        th.Property("rc_personal_development", th.StringType),
+        th.Property("rc_leadership_governance", th.StringType),
+        th.Property("rc_early_years", th.StringType),
+        th.Property("rc_sixth_form", th.StringType),
+```
+
+- [ ] **Step 2: Write the grade-parsing macro**
+
+`pipeline/transform/macros/parse_report_card_grade.sql`:
+
+```sql
+{% macro parse_report_card_grade(column_name) %}
+    case lower(trim(nullif({{ column_name }}, 'NULL')))
+        when 'exceptional' then 1
+        when 'strong standard' then 2
+        when 'expected standard' then 3
+        when 'needs attention' then 4
+        when 'attention needed' then 4
+        when 'urgent improvement' then 5
+    end
+{% endmacro %}
+```
+
+- [ ] **Step 3: Wire staging**
+
+Replace `stg_ofsted_inspections.sql` lines 36-46 (the NULL stubs) with:
+
+```sql
+        -- Report Card fields (post-Nov 2025 framework), 5-point scale:
+        -- 1 Exceptional · 2 Strong standard · 3 Expected standard
+        -- · 4 Needs attention · 5 Urgent improvement
+        (lower(trim(nullif(rc_safeguarding_met, 'NULL'))) = 'met')        as rc_safeguarding_met,
+        {{ parse_report_card_grade('rc_inclusion') }}::integer            as rc_inclusion,
+        {{ parse_report_card_grade('rc_curriculum_teaching') }}::integer  as rc_curriculum_teaching,
+        {{ parse_report_card_grade('rc_achievement') }}::integer          as rc_achievement,
+        {{ parse_report_card_grade('rc_attendance_behaviour') }}::integer as rc_attendance_behaviour,
+        {{ parse_report_card_grade('rc_personal_development') }}::integer as rc_personal_development,
+        {{ parse_report_card_grade('rc_leadership_governance') }}::integer as rc_leadership_governance,
+        {{ parse_report_card_grade('rc_early_years') }}::integer          as rc_early_years,
+        {{ parse_report_card_grade('rc_sixth_form') }}::integer           as rc_sixth_form,
+```
+
+Note `rc_safeguarding_met` becomes boolean (NULL when blank) — matching `fact_ofsted_inspection`'s `rc_safeguarding_met` Boolean column. If `fact_ofsted_inspection.sql` casts these columns, align its casts too (inspect that model; it currently passes the text stubs through).
+
+- [ ] **Step 4: Parse gate + tap smoke test**
+
+Run: `cd pipeline/transform && python -m dbt.cli.main parse --profiles-dir .` → `Done.`
+Run: `python -c "import sys; sys.path.insert(0,'pipeline/plugins/extractors/tap-uk-ofsted'); from tap_uk_ofsted.tap import COLUMN_PRIORITY; assert 'rc_inclusion' in COLUMN_PRIORITY; print('ok')"` → `ok`
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add pipeline/plugins/extractors/tap-uk-ofsted/tap_uk_ofsted/tap.py pipeline/transform/macros/parse_report_card_grade.sql pipeline/transform/models/staging/stg_ofsted_inspections.sql
+git commit -m "feat(pipeline): extract Ofsted report-card judgements (rc_* columns)"
+```
+
+---
+
+### Task 8: PR + post-merge verification
+
+**Files:** none new
+
+- [ ] **Step 1: Push and open the PR** (Gitea — use the git credential helper + basic-auth API pattern; token-header auth 401s):
+
+```bash
+git push -u origin feat/compare-data-foundation
+# then create the PR via the Gitea API with basic auth from `git credential fill`
+```
+
+PR body: link spec §5/§8, list the new mart columns, note the Task 6 human dependency (filebrowser upload) and the Task 1 findings file.
+
+- [ ] **Step 2: After merge, verify the DAG run picked everything up**
+
+The daily/monthly DAGs rebuild the affected models (`pipeline/dags/school_data_pipeline.py`). Spot-check via the public API (production after promotion, staging first at stx.schoolcompare.co.uk — note external /api is broken at the staging proxy, so check staging from the host):
+
+```bash
+# 2015/16 national row exists
+curl -sL "https://www.schoolcompare.co.uk/api/national-averages" | python3 -c "import json,sys; d=json.load(sys.stdin); assert any(r['year']==201516 and r['primary'] for r in d['by_year']), '2015/16 missing'; print('201516 ok')"
+# 2021/22 school rows exist (Barclay)
+curl -sL "https://www.schoolcompare.co.uk/api/schools/138690" | python3 -c "import json,sys; d=json.load(sys.stdin); ys=[r['year'] for r in d['yearly_data']]; assert 202122 in [int(y) for y in ys], ys; print('202122 ok')"
+```
+
+(The admissions/CI/KS4/rc_* columns aren't API-visible until the backend PR maps them — verify those directly in Postgres from the pipeline host: `select count(*) from marts.fact_admissions where second_preference_offers is not null;` etc.)
+
+- [ ] **Step 3: Update the spec** — tick off the §5 promotions this PR delivered (edit the spec's promotion list to note "landed in PR #NN") and commit to main via a docs PR or alongside the backend PR.
+
+---
+
+## Out of scope (next plans)
+
+1. **Backend PR:** map new columns in `backend/models.py`, extend `/api/compare` with supplementary blocks + `national_averages`, computed benchmarks (FSM/EAL/SEN/size medians, disadvantaged national average), CI-based progress banding, report-card label translation (verify against Ofsted toolkit), Ofsted provider-page URLs, graded-vs-ungraded surfacing.
+2. **Frontend PR:** rebuild `/compare` per the mockups + e2e journeys (promotion gate).
+3. **Separate bug fix:** third school's series not rendering on the current production chart.
+4. **Post-v1 (spec):** census ethnicity/young-carer promotion, IDACI display, attendance section, gender-split/absence tier-2 measures.
+5. **Already in marts, no work needed:** KS4 EBacc entry/APS, grade 5+ English & maths, Progress 8 CIs — `fact_ks4_performance` carries them today; only the backend needs to expose them.
@@ -0,0 +1,399 @@
+# Compare API Enrichment (Backend PR) Implementation Plan
+
+> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
+
+**Goal:** Expose the PR #32 data through the API so the redesigned compare screen can be built: enrich `/api/compare` with supplementary blocks + national averages + computed benchmarks, translate Ofsted report-card codes to labels, and surface the new mart columns (spec §6, §8 of `docs/superpowers/specs/2026-07-11-compare-screen-redesign-design.md`).
+
+**Architecture:** All changes are additive API fields — existing consumers keep working. One small dbt change rides along: `fact_performance` (the combined KS2+KS4 mart the backend's `_MAIN_QUERY` reads) enumerates columns explicitly and was not extended in PR #32, so the new KS2 CI and KS4 banding columns must be threaded through it here. Everything else is backend Python: `models.py` mappings, `data_loader` query/supplementary additions, an Ofsted label dictionary (gias_codes pattern), and `/api/compare` composition.
+
+**Tech Stack:** FastAPI, SQLAlchemy, pandas; dbt (one model); pytest via `python -m pytest backend/tests -q` (CI installs `requirements.txt pytest "httpx<0.28"`; locally use `uv run --with-requirements requirements.txt --with pytest --with "httpx==0.27.0" python -m pytest backend/tests -q`).
+
+## Global Constraints
+
+- **Never push to `main`.** Branch: `feat/compare-api-enrichment`.
+- **Additive only** to API responses; never rename/remove existing fields (frontend + e2e depend on them).
+- **Report-card scale labels are the live-sampled vocabulary** (evidence in `pipeline/scripts/diagnose_compare_gaps.py`): `1=Exceptional, 2=Strong standard, 3=Expected standard, 4=Needs attention, 5=Urgent improvement`. Never "Attention needed". Safeguarding is boolean met/not-met, never counted as a graded area.
+- **Ofsted links** are always the provider page `https://reports.ofsted.gov.uk/provider/21/{urn}` (spec §5) labelled as the school's Ofsted page.
+- **Benchmark provenance** (spec §8.6): computed values are "state-school average (computed from our dataset)" — the API must expose them under a `benchmarks` key, clearly separate from official `national_averages`.
+- TDD: each behaviour lands with a failing test first, in `backend/tests/` following the `test_school_details.py` pattern (pandas fixture + monkeypatched `load_school_data` + `TestClient`).
+- Deploy note for the PR body: the new API fields return NULL/empty until prod's DAGs have run post-promotion.
+
+---
+
+### Task 0: Branch
+
+- [ ] `git checkout main && git pull && git checkout -b feat/compare-api-enrichment` (commit this plan file on the branch).
+
+---
+
+### Task 1: Thread PR #32 columns through `fact_performance`
+
+**Files:**
+- Modify: `pipeline/transform/models/marts/fact_performance.sql`
+- Modify: `pipeline/transform/models/marts/_marts_schema.yml` (fact_performance block, if it has one — add the columns wherever the model's other columns are listed; if the model has no column list there, skip the yml)
+
+**Interfaces:**
+- Produces (for `_MAIN_QUERY` in Task 4): `ks2.*` CI columns and `ks4.progress_8_banding`, `ks4.attainment_8_disadvantage_gap`, `ks4.progress_8_disadvantage_gap` on `marts.fact_performance`.
+
+- [ ] **Step 1:** In `fact_performance.sql`, after `ks2.reading_progress,` add `ks2.reading_progress_lower_ci,` and `ks2.reading_progress_upper_ci,`; after `ks2.writing_progress,` add `ks2.writing_progress_lower_ci,`, `ks2.writing_progress_upper_ci,`, `ks2.writing_working_towards_pct,`; after `ks2.maths_progress,` add `ks2.maths_progress_lower_ci,`, `ks2.maths_progress_upper_ci,`. In the KS4 section, after the `ks4.progress_8_upper_ci`-equivalent line (locate the Progress 8 block) add:
+
+```sql
+    ks4.progress_8_banding,
+    ks4.attainment_8_disadvantage_gap,
+    ks4.progress_8_disadvantage_gap,
+```
+
+- [ ] **Step 2:** Parse gate: `cd pipeline/transform && uv run --with dbt-postgres python -m dbt.cli.main parse --profiles-dir .` → exit 0.
+
+- [ ] **Step 3:** Commit: `feat(pipeline): thread compare-foundation columns through fact_performance`
+
+---
+
+### Task 2: ORM mappings for the new mart columns
+
+**Files:**
+- Modify: `backend/models.py` (`KS2Performance` after `maths_progress`; `FactAdmissions` after `first_preference_offers`)
+- Test: none (declarative mappings; covered by Task 4's query tests)
+
+**Interfaces:**
+- Produces attributes used by Task 4: `KS2Performance.reading_progress_lower_ci` … `maths_progress_upper_ci`, `writing_working_towards_pct` (Float); `FactAdmissions.total_offers`, `.second_preference_offers`, `.third_preference_offers`, `.cross_la_applications`, `.cross_la_offers` (Integer).
+
+- [ ] **Step 1:** Add to `KS2Performance` (next to the existing progress columns):
+
+```python
+    reading_progress_lower_ci = Column(Float)
+    reading_progress_upper_ci = Column(Float)
+    writing_progress_lower_ci = Column(Float)
+    writing_progress_upper_ci = Column(Float)
+    writing_working_towards_pct = Column(Float)
+    maths_progress_lower_ci = Column(Float)
+    maths_progress_upper_ci = Column(Float)
+```
+
+Add to `FactAdmissions` (after `first_preference_offers`):
+
+```python
+    total_offers = Column(Integer)
+    second_preference_offers = Column(Integer)
+    third_preference_offers = Column(Integer)
+    cross_la_applications = Column(Integer)
+    cross_la_offers = Column(Integer)
+```
+
+(`FactOfstedInspection` already maps all `rc_*` columns with the right types — verify, don't change.)
+
+- [ ] **Step 2:** Commit: `feat(api): map compare-foundation mart columns`
+
+---
+
+### Task 3: Ofsted label dictionary + provider URL (TDD)
+
+**Files:**
+- Create: `backend/ofsted_codes.py`
+- Test: `backend/tests/test_ofsted_codes.py`
+
+**Interfaces:**
+- Produces for Task 4: `REPORT_CARD_GRADE_NAMES: dict[int, str]`, `report_card_labels(ofsted: dict) -> dict` (returns `{area_key: {"code": int, "label": str}}` for the non-null `rc_*` grade fields, excluding safeguarding), `ofsted_page_url(urn: int) -> str`.
+
+- [ ] **Step 1: Failing tests**
+
+```python
+"""Report-card code translation uses the live-sampled Ofsted vocabulary
+(pipeline/scripts/diagnose_compare_gaps.py TASK 7 VALUE SAMPLE):
+Exceptional / Strong standard / Expected standard / Needs attention /
+Urgent improvement — never the consultation draft's 'Attention needed'."""
+from backend.ofsted_codes import (
+    REPORT_CARD_GRADE_NAMES, report_card_labels, ofsted_page_url,
+)
+
+
+def test_scale_is_sampled_vocabulary():
+    assert REPORT_CARD_GRADE_NAMES == {
+        1: "Exceptional",
+        2: "Strong standard",
+        3: "Expected standard",
+        4: "Needs attention",
+        5: "Urgent improvement",
+    }
+
+
+def test_labels_only_for_populated_areas_and_never_safeguarding():
+    ofsted = {
+        "rc_achievement": 2,
+        "rc_inclusion": 3,
+        "rc_attendance_behaviour": 4,
+        "rc_early_years": None,
+        "rc_safeguarding_met": True,
+        "overall_effectiveness": None,
+    }
+    labels = report_card_labels(ofsted)
+    assert labels == {
+        "rc_achievement": {"code": 2, "label": "Strong standard"},
+        "rc_inclusion": {"code": 3, "label": "Expected standard"},
+        "rc_attendance_behaviour": {"code": 4, "label": "Needs attention"},
+    }
+
+
+def test_unknown_code_is_skipped_not_crashed():
+    assert report_card_labels({"rc_achievement": 9}) == {}
+
+
+def test_provider_url():
+    assert ofsted_page_url(138690) == "https://reports.ofsted.gov.uk/provider/21/138690"
+```
+
+- [ ] **Step 2:** Run `uv run --with-requirements requirements.txt --with pytest --with "httpx==0.27.0" python -m pytest backend/tests/test_ofsted_codes.py -q` → FAIL (module missing).
+
+- [ ] **Step 3: Implement `backend/ofsted_codes.py`**
+
+```python
+"""Ofsted renewed-framework (Nov 2025) report-card code translation.
+
+Scale labels are the live-sampled vocabulary from the Ofsted MI file
+(see pipeline/scripts/diagnose_compare_gaps.py, TASK 7 VALUE SAMPLE) —
+verified against real data, not the consultation draft.
+"""
+
+REPORT_CARD_GRADE_NAMES = {
+    1: "Exceptional",
+    2: "Strong standard",
+    3: "Expected standard",
+    4: "Needs attention",
+    5: "Urgent improvement",
+}
+
+# Graded evaluation areas only — safeguarding is a separate boolean
+# judgement and must never appear in grade counts or label maps.
+_RC_AREA_KEYS = (
+    "rc_inclusion",
+    "rc_curriculum_teaching",
+    "rc_achievement",
+    "rc_attendance_behaviour",
+    "rc_personal_development",
+    "rc_leadership_governance",
+    "rc_early_years",
+    "rc_sixth_form",
+)
+
+
+def report_card_labels(ofsted: dict) -> dict:
+    """{area_key: {code, label}} for populated, known-valued rc_* areas."""
+    out = {}
+    for key in _RC_AREA_KEYS:
+        code = ofsted.get(key)
+        label = REPORT_CARD_GRADE_NAMES.get(code)
+        if code is not None and label is not None:
+            out[key] = {"code": code, "label": label}
+    return out
+
+
+def ofsted_page_url(urn: int) -> str:
+    """The school's page on ofsted.gov.uk (all its reports live there —
+    we never deep-link an individual report; spec §5)."""
+    return f"https://reports.ofsted.gov.uk/provider/21/{urn}"
+```
+
+- [ ] **Step 4:** Re-run the test file → 4 passed. Run the full suite (same command, `backend/tests -q`) → all pass.
+
+- [ ] **Step 5:** Commit: `feat(api): Ofsted report-card labels and provider-page URL`
+
+---
+
+### Task 4: data_loader — query columns + richer supplementary blocks (TDD)
+
+**Files:**
+- Modify: `backend/data_loader.py` (`_MAIN_QUERY` ~line 153; `get_supplementary_data` ~line 460)
+- Test: `backend/tests/test_supplementary_enrichment.py`
+
+**Interfaces:**
+- `_MAIN_QUERY` additionally selects (KS2 block, after `p.maths_progress`): `p.reading_progress_lower_ci, p.reading_progress_upper_ci, p.writing_progress_lower_ci, p.writing_progress_upper_ci, p.writing_working_towards_pct, p.maths_progress_lower_ci, p.maths_progress_upper_ci`; (KS4 block, after the Progress 8 CI columns): `p.progress_8_banding, p.attainment_8_disadvantage_gap, p.progress_8_disadvantage_gap`. Note `_MAIN_QUERY_NO_SIXTH_FORM`/`_MAIN_QUERY_LEGACY_NAMES` are string-derived from `_MAIN_QUERY` (lines 259-270) and inherit automatically — verify the assertions there still hold.
+- `get_supplementary_data(db, urn)["admissions"]` rows additionally carry: `total_offers`, `second_preference_offers`, `third_preference_offers`, `cross_la_applications`, `cross_la_offers` (add to `_admissions_row`).
+- `get_supplementary_data(db, urn)["ofsted"]` additionally carries: `report_card` (the `report_card_labels(...)` dict, `{}` when no rc data), `ofsted_page_url`, and `grade_source`: `"graded"` when `overall_effectiveness` came from the graded column, `"ungraded_carried_forward"` when the fallback `ungraded_grade` supplied it, `None` when neither.
+
+- [ ] **Step 1: Failing tests** — construct a fake Ofsted row object (simple `types.SimpleNamespace` with the model's attributes) and call the block-building logic via `get_supplementary_data` with a stubbed session (follow how existing tests stub the db; if none do, factor the ofsted-dict construction into a pure helper `_ofsted_block(o, urn)` and test that directly — preferred):
+
+```python
+import types
+from backend.data_loader import _ofsted_block
+
+
+def _row(**kw):
+    base = dict(
+        framework="RC", inspection_date=None, inspection_type=None,
+        overall_effectiveness=None, quality_of_education=None,
+        behaviour_attitudes=None, personal_development=None,
+        leadership_management=None, early_years_provision=None,
+        sixth_form_provision=None, ungraded_outcome=None, ungraded_grade=None,
+        rc_safeguarding_met=None, rc_inclusion=None, rc_curriculum_teaching=None,
+        rc_achievement=None, rc_attendance_behaviour=None,
+        rc_personal_development=None, rc_leadership_governance=None,
+        rc_early_years=None, rc_sixth_form=None, report_url=None,
+    )
+    base.update(kw)
+    return types.SimpleNamespace(**base)
+
+
+def test_report_card_block_and_provider_url():
+    o = _row(rc_achievement=2, rc_inclusion=3, rc_safeguarding_met=True)
+    block = _ofsted_block(o, urn=100140)
+    assert block["report_card"]["rc_achievement"]["label"] == "Strong standard"
+    assert "rc_safeguarding_met" not in block["report_card"]
+    assert block["rc_safeguarding_met"] is True
+    assert block["ofsted_page_url"] == "https://reports.ofsted.gov.uk/provider/21/100140"
+
+
+def test_grade_source_graded_vs_carried_forward():
+    assert _ofsted_block(_row(overall_effectiveness=1), urn=1)["grade_source"] == "graded"
+    carried = _ofsted_block(_row(ungraded_grade=2), urn=1)
+    assert carried["grade_source"] == "ungraded_carried_forward"
+    assert carried["overall_effectiveness"] == 2
+    assert _ofsted_block(_row(), urn=1)["grade_source"] is None
+
+
+def test_admissions_row_new_fields():
+    from backend.data_loader import _admissions_row_dict
+    a = types.SimpleNamespace(
+        year=202627, school_phase="Primary", places_offered=80,
+        total_applications=185, first_preference_applications=74,
+        first_preference_offers=74, first_preference_offer_pct=100.0,
+        oversubscription_ratio=0.925, oversubscribed=False,
+        total_offers=80, second_preference_offers=4, third_preference_offers=2,
+        cross_la_applications=12, cross_la_offers=3,
+    )
+    d = _admissions_row_dict(a)
+    for k in ("total_offers", "second_preference_offers", "third_preference_offers",
+              "cross_la_applications", "cross_la_offers"):
+        assert d[k] == getattr(a, k)
+```
+
+- [ ] **Step 2:** Run → FAIL (helpers don't exist).
+
+- [ ] **Step 3: Implement.** Refactor the existing inline ofsted-dict construction in `get_supplementary_data` into a module-level `_ofsted_block(o, urn)` that produces the existing keys **unchanged** plus the three new ones (`report_card` via `report_card_labels(...)` from Task 3, `ofsted_page_url` via `ofsted_page_url(urn)`, `grade_source` per the interface rule — derived from which source supplied `overall_effectiveness`). Rename/extract the local `_admissions_row` into module-level `_admissions_row_dict(a)` and append the five new fields. Add the ten new columns to `_MAIN_QUERY` exactly as the interface lists them. `get_supplementary_data` calls both helpers; its external shape gains only additive keys.
+
+- [ ] **Step 4:** Full suite → all pass (existing `test_school_details.py` etc. must not break; if a fixture enumerates yearly-data columns, extend it with the new NaN columns as needed).
+
+- [ ] **Step 5:** Commit: `feat(api): expose progress CIs, KS4 banding/gaps, admissions detail, report-card labels`
+
+---
+
+### Task 5: Computed benchmarks helper (TDD)
+
+**Files:**
+- Modify: `backend/data_loader.py` (new function)
+- Test: `backend/tests/test_benchmarks.py`
+
+**Interfaces:**
+- Produces for Task 6: `compute_benchmarks(df) -> dict` — pure function over the main dataframe (latest year, state schools), shape:
+
+```python
+{
+  "source": "state-school average (computed from our dataset)",
+  "year": 202425,
+  "primary": {
+      "disadvantaged_rwm_expected_pct": 46.1,   # weighted by eligible_pupils
+      "eal_pct": 22.3,                           # median
+      "sen_support_pct": 14.0,                   # median
+      "disadvantaged_pct": 24.8,                 # median (FSM6 proxy)
+      "median_pupils": 281,                      # median school size
+  },
+  "secondary": { "median_pupils": 1024, "eal_pct": ..., "sen_support_pct": ..., "disadvantaged_pct": ... },
+}
+```
+
+- [ ] **Step 1: Failing tests** — build a small synthetic df (6 primary rows with known eligible_pupils/rwm_expected_disadvantaged_pct so the weighted average is hand-checkable; a couple of secondary rows flagged by non-null `attainment_8_score`), assert: weighted disadvantaged average matches hand computation (not the unweighted mean), medians ignore NaN, secondary block lacks the disadvantaged-RWM key, latest-year filtering (rows from an older year must not affect results), and empty df → `{}`.
+
+- [ ] **Step 2:** Run → FAIL.
+
+- [ ] **Step 3: Implement** in `data_loader.py`:
+
+```python
+def compute_benchmarks(df: pd.DataFrame) -> dict:
+    """State-school benchmarks computed from our dataset (spec §5/§8.6).
+    These are NOT official DfE figures — consumers must label them
+    'state-school average (computed from our dataset)'."""
+    if df.empty or "year" not in df.columns:
+        return {}
+    latest_year = df["year"].max()
+    d = df[df["year"] == latest_year]
+    if d.empty:
+        return {}
+    is_secondary = d["attainment_8_score"].notna() if "attainment_8_score" in d.columns else pd.Series(False, index=d.index)
+    prim, sec = d[~is_secondary], d[is_secondary]
+
+    def _median(sub, col):
+        if col not in sub.columns:
+            return None
+        v = sub[col].median()
+        return round(float(v), 1) if pd.notna(v) else None
+
+    def _weighted_disadvantaged(sub):
+        if not {"rwm_expected_disadvantaged_pct", "eligible_pupils"} <= set(sub.columns):
+            return None
+        s = sub.dropna(subset=["rwm_expected_disadvantaged_pct", "eligible_pupils"])
+        if s.empty or s["eligible_pupils"].sum() == 0:
+            return None
+        w = (s["rwm_expected_disadvantaged_pct"] * s["eligible_pupils"]).sum() / s["eligible_pupils"].sum()
+        return round(float(w), 1)
+
+    def _block(sub, with_disadvantaged):
+        block = {
+            "eal_pct": _median(sub, "eal_pct"),
+            "sen_support_pct": _median(sub, "sen_support_pct"),
+            "disadvantaged_pct": _median(sub, "disadvantaged_pct"),
+            "median_pupils": int(sub["total_pupils"].median()) if "total_pupils" in sub.columns and pd.notna(sub["total_pupils"].median()) else None,
+        }
+        if with_disadvantaged:
+            block["disadvantaged_rwm_expected_pct"] = _weighted_disadvantaged(sub)
+        return block
+
+    return {
+        "source": "state-school average (computed from our dataset)",
+        "year": int(latest_year),
+        "primary": _block(prim, with_disadvantaged=True),
+        "secondary": _block(sec, with_disadvantaged=False),
+    }
+```
+
+(Adapt column presence to the real df — `sen_support_pct` reaches the df via `_MAIN_QUERY`; confirm and add it there if the KS2 block doesn't already select it, mirroring Task 4's additions.)
+
+- [ ] **Step 4:** Full suite → pass. **Step 5:** Commit: `feat(api): computed state-school benchmarks`
+
+---
+
+### Task 6: Enrich `/api/compare` + expose GPS/science national averages (TDD)
+
+**Files:**
+- Modify: `backend/app.py` (`compare_schools` ~line 636; `get_national_averages` ~line 730)
+- Test: `backend/tests/test_compare_enrichment.py`
+
+**Interfaces (response additions, all additive):**
+- `/api/compare` top level gains: `"national_averages"` (same payload the `/api/national-averages` endpoint returns — extract the endpoint body into a helper `_national_averages_payload(df)` and reuse; do not duplicate the logic) and `"benchmarks"` (Task 5's `compute_benchmarks(df)`).
+- Each `comparison[urn]` gains: `"ofsted"`, `"census"`, `"admissions"`, `"admissions_history"`, `"deprivation"` from `get_supplementary_data` (one `SessionLocal()` for the whole request, closed in `finally`; on exception the five keys are `None`/`[]` — mirror the detail endpoint's defensive pattern at app.py:583-590).
+- `get_national_averages`' KS2 metric list gains `"gps_expected_pct", "gps_high_pct", "science_expected_pct"` so the England ticks for GPS/science flow once the data exists.
+
+- [ ] **Step 1: Failing tests** — monkeypatch `load_school_data` with a two-school primary df (reuse/extend the fixture style of `test_school_details.py`) and monkeypatch `get_supplementary_data` to a canned dict; assert on `TestClient(app).get("/api/compare?urns=...")`:
+  - response keeps the existing shape (`comparison[urn]["school_info"]["rwm_expected_pct"]` etc.),
+  - each school gains the five supplementary keys (canned values round-tripped),
+  - top-level `national_averages` and `benchmarks` present; `benchmarks["source"]` is the exact provenance string,
+  - a supplementary-layer exception (monkeypatched to raise) degrades to `ofsted: None` etc. with HTTP 200,
+  - `/api/national-averages` includes `gps_expected_pct` in the primary block when the df/national table provides it (monkeypatch the national-averages source the endpoint reads).
+
+- [ ] **Step 2:** Run → FAIL. **Step 3:** Implement per the interfaces. **Step 4:** Full suite → pass.
+
+- [ ] **Step 5:** Commit: `feat(api): compare endpoint carries supplementary blocks, national averages and benchmarks`
+
+---
+
+### Task 7: PR + verification
+
+- [ ] **Step 1:** Full suite one more time + `uv run --with pyyaml python3 -c "import yaml; yaml.safe_load(open('.gitea/workflows/deploy.yml'))"` sanity is NOT needed (no workflow changes) — instead run the dbt parse gate again (Task 1 file).
+- [ ] **Step 2:** Push, open PR via the Gitea API (credential-helper basic auth). PR body: the new response shapes (one JSON sketch), the reused-not-duplicated national-averages helper, the provenance rule for benchmarks, deploy note (fields NULL until prod DAGs run post-promotion), and that no e2e change is needed (no user-facing behaviour changes — the compare UI still reads the old fields; the frontend PR carries the journey updates).
+- [ ] **Step 3:** After merge + staging deploy: `curl -s https://stx.schoolcompare.co.uk/api/compare?urns=138690,100140 | python3 -m json.tool | head -80` — verify the new keys and that `benchmarks.primary.disadvantaged_rwm_expected_pct` is plausible (~45-47). Verify `/api/national-averages` now carries `gps_expected_pct`/`science_expected_pct` (values or honest nulls if DfE suppresses them at national level).
+
+---
+
+## Out of scope
+
+- Frontend rebuild + e2e journeys (next PR — consumes everything this PR exposes).
+- `schemas.py` METRIC_DEFINITIONS additions for the trends picker (frontend PR decides which of the new columns become picker metrics).
+- CI-based progress banding logic (frontend computes Above/Average/Below from the CI columns; historical years only).
@@ -0,0 +1,287 @@
+# Compare Screen Frontend Rebuild Implementation Plan
+
+> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
+
+**Goal:** Rebuild `/compare` in the Next.js app to match the approved mockups — parent-first sections (At a glance / Ofsted / Academics / Getting a place / Who goes there / Explore trends), England-average anchoring with provenance-correct labels, mobile-first measure-first layout — consuming the enriched `/api/compare` payload from PR #34, with e2e journeys updated in the same PR (they are the promotion gate).
+
+**Architecture:** `ComparisonView` becomes an assembly of section components fed by one enriched fetch. All comprehension rules from the two expert reviews live in a pure, jest-tested module (`lib/compareLogic.ts`) — components stay presentational. The mockups are committed at `docs/superpowers/specs/mockups/compare-desktop.html` and `compare-mobile.html`: **all user-facing copy (labels, tooltips, chips, footnote wording) is taken verbatim from them** — they carry two rounds of education-expert review; do not paraphrase.
+
+**Tech Stack:** Next.js (app router, SSR page + client view), CSS modules, Chart.js (existing `ComparisonChart`), Jest (`npm test` in `nextjs-app/`), Playwright e2e (`e2e/`).
+
+## Global Constraints
+
+- **Never push to `main`.** Branch: `feat/compare-frontend-rebuild`.
+- **Copy is expert-reviewed:** take it verbatim from the committed mockups. Binding rules (spec §8): Ofsted scale labels come from the API's `report_card[..].label` (never hardcode area labels beyond the mockups'); official DfE numbers say "England average", computed ones say "state-school average (computed from our dataset)"; the 2021/22 chart gap note says "DfE didn't publish school-level figures for 2021/22"; never derive an overall grade from report-card areas; safeguarding never counts as a graded area; "Latest Ofsted inspection", "EHC plans", "at or above capacity", "Over 1 in 4", "first choice (officially 'first preference')".
+- **Mobile-first:** the measure-first stacked layout (mobile mockup) is the base CSS; the desktop label-column grid is the `min-width` enhancement.
+- **URL contract unchanged:** `?urns=` (and `metric=` now scoped to Explore trends) keep working; share flow, `useComparison` basket, phase tabs, and `compare_viewed`/`compare_metric_changed` analytics events are preserved.
+- **Do not run a local server** (CLAUDE.md); verification = jest + `tsc` + the e2e suite against staging after merge. e2e must pass on **staging data** — remember staging has partial history: assert against the *latest* year, never oldest.
+- Existing `/api/compare` consumers elsewhere in the app (SchoolDetail links, toasts) must not break — the response is additive, and this PR only rewrites the compare page's own components.
+- **Post-v1 (do not build):** IDACI, attendance section, gender-split/absence tier-2 measures, finance (spec §4).
+
+---
+
+### Task 0: Branch + design sources
+
+- [ ] `git checkout main && git pull && git checkout -b feat/compare-frontend-rebuild`
+- [ ] The mockups and this plan are already in the working tree (`docs/superpowers/specs/mockups/compare-{desktop,mobile}.html`) — commit them: `docs: compare mockups as frontend design source + rebuild plan`
+
+---
+
+### Task 1: Types for the enriched payload
+
+**Files:**
+- Modify: `nextjs-app/lib/types.ts` (extend `SchoolResult`, `ComparisonData`, `ComparisonResponse` — located around lines 293-314)
+
+**Interfaces (produced for every later task):**
+
+```ts
+export interface ReportCardEntry { code: number; label: string; }
+
+export interface OfstedBlock {
+  framework: string | null;
+  inspection_date: string | null;
+  inspection_type: string | null;
+  overall_effectiveness: number | null;
+  grade_source: 'graded' | 'ungraded_carried_forward' | null;
+  quality_of_education: number | null;
+  behaviour_attitudes: number | null;
+  personal_development: number | null;
+  leadership_management: number | null;
+  early_years_provision: number | null;
+  sixth_form_provision: number | null;
+  rc_safeguarding_met: boolean | null;
+  report_card: Record<string, ReportCardEntry>;
+  ofsted_page_url: string;
+  report_url: string | null;
+}
+
+export interface CensusBlock {
+  year: number | null; total_pupils: number | null;
+  female_pupils: number | null; male_pupils: number | null;
+  fsm_pct: number | null; eal_pct: number | null;
+}
+
+export interface AdmissionsRow {
+  year: number; school_phase: string | null;
+  places_offered: number | null; total_applications: number | null;
+  first_preference_applications: number | null; first_preference_offers: number | null;
+  first_preference_offer_pct: number | null; oversubscription_ratio: number | null;
+  oversubscribed: boolean | null;
+  total_offers: number | null; second_preference_offers: number | null;
+  third_preference_offers: number | null;
+  cross_la_applications: number | null; cross_la_offers: number | null;
+}
+
+export interface DeprivationBlock {
+  lsoa_code: string | null; idaci_score: number | null; idaci_decile: number | null;
+}
+
+export interface BenchmarkBlock {
+  eal_pct: number | null; sen_support_pct: number | null;
+  disadvantaged_pct: number | null; median_pupils: number | null;
+  disadvantaged_rwm_expected_pct?: number | null;
+}
+
+export interface Benchmarks {
+  source: string; year: number;
+  primary: BenchmarkBlock; secondary: BenchmarkBlock;
+}
+
+export interface NationalAverages {
+  year: number;
+  primary: Record<string, number>;
+  secondary: Record<string, number>;
+  by_year: Array<{ year: number; primary: Record<string, number>; secondary: Record<string, number> }>;
+}
+```
+
+- [ ] **Step 1:** Add the interfaces above; extend `ComparisonData` with optional `ofsted?: OfstedBlock | null; census?: CensusBlock | null; admissions?: AdmissionsRow | null; admissions_history?: AdmissionsRow[]; deprivation?: DeprivationBlock | null;` and `ComparisonResponse` with `national_averages?: NationalAverages; benchmarks?: Benchmarks;` (optional so the UI degrades on an old backend). Extend `SchoolResult` with the ten new yearly columns (`reading_progress_lower_ci` … `maths_progress_upper_ci`, `writing_working_towards_pct`, `progress_8_banding: string | null`, `attainment_8_disadvantage_gap`, `progress_8_disadvantage_gap`).
+- [ ] **Step 2:** `cd nextjs-app && npx tsc --noEmit` → clean. Commit: `feat(compare): types for enriched comparison payload`
+
+---
+
+### Task 2: `lib/compareLogic.ts` — the comprehension rules, jest-tested
+
+**Files:**
+- Create: `nextjs-app/lib/compareLogic.ts`
+- Test: `nextjs-app/__tests__/lib/compareLogic.test.ts`
+
+**Interfaces (produced):**
+
+```ts
+export type Verdict = 'above' | 'close' | 'below';
+export function verdict(value: number, anchor: number, tolerance?: number): Verdict; // default tolerance 2pp
+
+// Report-card summary per spec §4.2: count graded areas per label (best
+// first), NAME any 'Needs attention'/'Urgent improvement' area, safeguarding
+// separate, "No areas need attention" reassurance when applicable.
+export interface ReportCardSummary {
+  counts: Array<{ label: string; count: number }>;        // best grade first
+  problems: Array<{ areaLabel: string; label: string }>;  // named, never counted-away
+  safeguarding: 'met' | 'not_met' | null;
+  allClear: boolean;
+}
+export function summariseReportCard(ofsted: OfstedBlock): ReportCardSummary;
+
+// One display model for all three inspection regimes.
+export type OfstedDisplay =
+  | { kind: 'none' }
+  | { kind: 'graded'; grade: number; gradeLabel: string; carriedForward: false }
+  | { kind: 'carried_forward'; grade: number; gradeLabel: string; carriedForward: true }
+  | { kind: 'report_card'; summary: ReportCardSummary };
+export function ofstedDisplay(ofsted: OfstedBlock | null | undefined): OfstedDisplay;
+export const OFSTED_LEGACY_GRADES: Record<number, string>; // 1 Outstanding, 2 Good, 3 Requires improvement, 4 Inadequate
+
+// Human-readable area label from an rc_ key: 'rc_attendance_behaviour' →
+// 'Attendance & behaviour' (mapping table copied from the mockups' area rows).
+export function rcAreaLabel(key: string): string;
+
+// Admissions, one consistent chip metric (first-preference success).
+export interface AdmissionsSummary {
+  firstPrefPct: number | null;
+  chip: { tone: 'good' | 'warn' | 'neutral'; text: string } | null; // "97% of first choices offered" / "Over 1 in 4 first choices missed out" wording per mockups
+  interest: string | null;   // "Named on 457 forms · 180 places"
+}
+export function summariseAdmissions(a: AdmissionsRow | null | undefined): AdmissionsSummary;
+
+// CI-based progress band for historical years (null when no CI published).
+export function progressBand(score: number | null, lower: number | null, upper: number | null):
+  'above' | 'average' | 'below' | null; // CI entirely >0 → above; entirely <0 → below; straddles → average
+
+// Dot-strip geometry (used by the DotStrip component; pure for testing).
+export interface StripPoint { pos: number; labelAbove: boolean; value: number; schoolIndex: number; }
+export function stripPositions(values: Array<number | null>, min: number, max: number): StripPoint[];
+// pos = (v-min)/(max-min)*100 clamped 0..100; labels within 4% of range of a
+// lower neighbour flip above (the mockups' collision nudge).
+```
+
+- [ ] **Step 1: Failing tests** covering, at minimum:
+  - `summariseReportCard`: 4 Strong + 2 Expected + 1 Needs-attention + safeguarding met → counts `[Strong standard×4, Expected standard×2]`, `problems=[{areaLabel:'Attendance & behaviour', label:'Needs attention'}]`, `allClear=false`; safeguarding NEVER in counts; all-Expected+met → `allClear=true`; labels come from the input's `.label` (assert the function never invents "Attention needed").
+  - `ofstedDisplay`: report_card present → `kind:'report_card'` even if a legacy grade also exists; `grade_source:'ungraded_carried_forward'` → `carriedForward:true`; null → `'none'`.
+  - `summariseAdmissions`: 73% → warn chip text `Over 1 in 4 first choices missed out`; 97% → good chip `97% of first choices offered`; 100% → `All first choices offered`; interest string `Named on 342 forms · 120 places`; nulls → null chip.
+  - `progressBand`: (1.2, 0.4, 2.0)→above; (-1.2, -2.0, -0.4)→below; (0.3, -0.5, 1.1)→average; missing CI → null.
+  - `stripPositions`: 100–120 domain maps 106→30; values 91 and 92 on 0–100 → second label flips above; nulls skipped.
+  - `verdict`: 87 vs 62 → above; 61 vs 62 → close (within 2pp); 40 vs 62 → below.
+- [ ] **Step 2:** `cd nextjs-app && npm test -- compareLogic` → FAIL. **Step 3:** implement. **Step 4:** pass + `tsc` clean. **Step 5:** Commit: `feat(compare): comprehension logic (report cards, admissions, verdicts, strips)`
+
+---
+
+### Task 3: `DotStrip` component
+
+**Files:**
+- Create: `nextjs-app/components/DotStrip.tsx`, `nextjs-app/components/DotStrip.module.css`
+
+**Interfaces:**
+
+```ts
+export interface DotStripProps {
+  label: string;
+  values: Array<number | null>;      // one per school, school order = chart colour order
+  anchor?: { value: number; label: string } | null; // e.g. {62, "England 62%"} — omit when benchmark absent
+  min?: number; max?: number;        // default 0..100
+  unit?: string;                     // default '%'
+  tip?: string;                      // title tooltip on the label
+  note?: string;                     // e.g. "(teacher-assessed)" suffix handled by caller in label
+}
+```
+
+- [ ] Render per the mockups' `.strip-row` anatomy: label row, 4px track, England tick + tick label, 16px dots coloured by `CHART_COLORS[index]` with white ring, value labels below (flipped above on collision via `stripPositions`). `role="img"` + `aria-label` enumerating anchor and each school's value (copy the aria pattern from the mockups). CSS module mirrors the mockup styles using the app's CSS variables (`--border-light`, `--text-muted`, etc.).
+- [ ] Jest: render with `@testing-library/react` (already configured — see `__tests__/components/SecondarySchoolRow.test.tsx` for the harness pattern): asserts aria-label content, tick present when anchor given, absent otherwise.
+- [ ] Commit: `feat(compare): DotStrip with England-average anchor`
+
+---
+
+### Task 4: Section components — At a glance, Ofsted, Getting a place, Who goes there
+
+**Files:**
+- Create: `nextjs-app/components/compare/CompareAtAGlance.tsx` (+ `.module.css`)
+- Create: `nextjs-app/components/compare/CompareOfsted.tsx`
+- Create: `nextjs-app/components/compare/CompareAdmissions.tsx`
+- Create: `nextjs-app/components/compare/CompareCommunity.tsx`
+- Create: `nextjs-app/components/compare/compareSections.module.css` (shared measure-first grid)
+- Test: `nextjs-app/__tests__/components/CompareOfsted.test.tsx`
+
+**Shared layout contract (all four):** props `{ schools: School[]; data: Record<string, ComparisonData>; benchmarks?: Benchmarks; nationalAverages?: NationalAverages }`. Base CSS is the mobile mockup's measure-first stack (`.measure` card → `.srow` per school with colour dot + short name + value + chip + note); at `min-width: 761px` it becomes the desktop mockup's grid (200px row-label column + one column per school). Section headers use the existing `.section-title` idiom; every section carries its mockup "how" line verbatim.
+
+**Content per section = the mockups, row for row.** Structure/tone rules already encoded in Task 2's helpers:
+- *At a glance*: Latest Ofsted inspection row (badge via `ofstedDisplay`; report-card case renders `ReportCardSummary` chips — counts best-first + named problem chips + safeguarding line); expected-standard row (big % + `verdict` chip vs `national_averages.primary.rwm_expected_pct`, small "England average N%"); Getting a place row (chip from `summariseAdmissions`, note = `interest`); Size row (pupils + "at or above capacity"/"N% full" from census/capacity, vs `benchmarks.*.median_pupils` for "larger/smaller than average" phrasing).
+- *Ofsted*: the section's `how` paragraph (regime explanation + non-comparability + "Expected standard" disambiguation) verbatim from the desktop mockup; Result row; Inspected row (date + "4+ years ago" chip when >4y, computed from `inspection_date`); Judgement detail row — **one chip-list grammar for both regimes** (legacy subgrades via `OFSTED_LEGACY_GRADES`; report card via `report_card` labels; "We don't hold area-by-area detail for this inspection" when neither); Ofsted page row linking `ofsted_page_url` ("<Name>'s Ofsted page →").
+- *Getting a place*: `how` paragraph (first preference/equal preference/offer-day caveats) verbatim; Interest row; first-choice success row with mini bar; "What this means" row (distance note: "check the school's admission criteria (for most non-faith primaries, distance decides)" only when oversubscribed).
+- *Who goes there*: pupils-on-roll (census + capacity), girls/boys, FSM (chip vs `benchmarks` with "state-school average" wording), EAL, SEN (tooltip incl. "EHC plans" + specialist-provision note), faith, ages · nursery, run by (trust name or "<LA> council").
+
+- [ ] **Step 1:** Failing jest test for `CompareOfsted` (the riskiest): given one graded school, one carried-forward, one report-card school → asserts the three Result cells ("Outstanding" badge; badge + carried-forward marker; "Report card" + no invented overall grade), the chip-list judgement rows, and the comparability note appearing only for the mixed case.
+- [ ] **Step 2-4:** Implement all four sections; test passes; `tsc` clean; `npm test` full suite green.
+- [ ] **Step 5:** Commit: `feat(compare): at-a-glance, Ofsted, admissions and community sections`
+
+---
+
+### Task 5: `CompareAcademics` — strips + More measures
+
+**Files:**
+- Create: `nextjs-app/components/compare/CompareAcademics.tsx`
+- Test: extend `nextjs-app/__tests__/lib/compareLogic.test.ts` with the metric-extraction helper below
+
+**Interfaces:**
+- Add to `compareLogic.ts`: `latestValues(data, urns, metricKey) => Array<number|null>` (latest non-null yearly value per school) — tested.
+
+- [ ] Tier 1 strips (always visible), each a `DotStrip` with the England anchor from `national_averages.primary`: RWM expected, Reading, Writing, Maths, "Working at a higher standard than expected" (tooltip: composition sentence from the mockups). Section `how` line: "tests and teacher assessments … writing is assessed by teachers, not tested" verbatim.
+- [ ] Tier 2 `<details>` "More measures — grammar, punctuation & spelling, science, average scaled scores": GPS + Science (teacher-assessed, tooltip verbatim) with anchors from `national_averages` **when present, no tick + honest note when null**; scaled scores (reading/maths/GPS) on `min=100 max=120` with the mockups' window caption.
+- [ ] Equity row: disadvantaged pupils' RWM per school + chip vs `benchmarks.primary.disadvantaged_rwm_expected_pct` with the "state-school average" wording and small-cohort tooltip verbatim.
+- [ ] Secondary phase variant (when active phase is secondary): tier-1 rows are Attainment 8 (anchor `national_averages.secondary.attainment_8_score`), Progress 8 banding (chip showing `progress_8_banding` verbatim — DfE's own label), grade 5+ English & maths %; tier-2: EBacc entry/APS. Measure-first rows (no strips needed for banding).
+- [ ] `npm test` + `tsc`; commit: `feat(compare): academics strips with England anchors and More measures`
+
+---
+
+### Task 6: Trends explorer — England line, gap-honest axis, series bug
+
+**Files:**
+- Modify: `nextjs-app/components/ComparisonChart.tsx`
+- Create: `nextjs-app/components/compare/TrendsExplorer.tsx`
+- Test: `nextjs-app/__tests__/components/ComparisonChart.test.tsx`
+
+- [ ] **Step 1 (bug first): root-cause the missing third series** seen on production (3 schools in table, 2 lines on chart). Write a failing jest test: 3 schools whose `yearly_data` year values are floats (`202425.0`) vs the labels array — the suspect is the year-matching in `ComparisonChart.tsx:69` (`years.map(...)` built from school 1 only + strict equality against other schools' years). Fix so every school's series renders and years are the union of all schools' years, sorted.
+- [ ] **Step 2:** Add optional `nationalByYear?: Record<number, number|null>` prop → dashed grey "England average" dataset (colour `--text-muted`, `borderDash:[5,4]`, no fill, `spanGaps:false`).
+- [ ] **Step 3:** Gap honesty: x-axis category labels include 2019/20 and 2020/21 as empty slots (band label "tests cancelled 2019/20–2020/21" via a Chart.js annotation-free approach: two category ticks with all-null data and a subtitle note under the chart, copy verbatim: the chart footnote "DfE didn't publish school-level figures for 2021/22" appears when the metric is a KS2 measure and 2021/22 school values are null while the England value exists). `spanGaps:false` on school datasets so dataset gaps break lines.
+- [ ] **Step 4:** `TrendsExplorer` wraps the grouped metric picker (existing optgroup structure and `metrics` from `/api/metrics`, existing analytics event) + the chart + the existing year-by-year table, inside a collapsed-by-default `<details>` ("Explore trends"). Progress metrics annotate cells with `progressBand` chips for years where CIs exist.
+- [ ] Tests pass; commit: `feat(compare): trends explorer with England line; fix missing series`
+
+---
+
+### Task 7: Assemble the new `ComparisonView`
+
+**Files:**
+- Rewrite: `nextjs-app/components/ComparisonView.tsx` (+ its `.module.css`)
+- Modify: `nextjs-app/app/compare/page.tsx` metadata description (mention Ofsted/admissions, not just KS2)
+
+- [ ] Preserve intact: `useComparison` basket seeding/URL sync (lines 76-122 of the current file), share handler, phase tabs + auto-detection, `compare_viewed` analytics, empty states, `SchoolSearchModal`, max-4-visible column scroll. Replace the metric-picker/chart/table body with the section stack: sticky school chip bar (mockup `.school-bar`) → `CompareAtAGlance` → `CompareOfsted` → `CompareAcademics` → `CompareAdmissions` → `CompareCommunity` → `TrendsExplorer`. The page-level `metric` URL param now initialises `TrendsExplorer`'s picker only.
+- [ ] Top-of-page subtitle + sources footnote verbatim from the mockups (minus the "Mockup" banner), including the suppression rule sentence and provenance sentence.
+- [ ] `npm test` full suite + `tsc` clean. Commit: `feat(compare): parent-first compare screen assembly`
+
+---
+
+### Task 8: e2e journeys (the promotion gate)
+
+**Files:**
+- Modify: `e2e/tests/journeys.spec.ts` (the two compare tests, lines ~141-215; extend, don't delete coverage)
+
+- [ ] Update 'comparing two schools shows both side by side': after loading `/compare?urns=…` assert the new section headings (`At a glance`, `Ofsted inspection`, `How children do academically`, `Getting a place`, `Who goes there`, `Explore trends`), both school names in the sticky bar, at least one England-average tick label (`text=/England \d+%/`), and one provenance string `state-school average` somewhere (benchmarks row). Data-invariant style — no exact numbers (staging data shifts; use latest-year values only).
+- [ ] Update the mobile test: 390px viewport, assert measure-first stacking (a `.measure`-card contains all selected school names within one card) and that the trends chart container scrolls (`overflow-x`).
+- [ ] Add a report-card presence-agnostic assertion: the Ofsted section renders either a grade badge or "Report card" without an overall grade — i.e. never both an overall-grade badge AND report-card chips for the same school.
+- [ ] Run against staging from the host if reachable (`cd e2e && BASE_URL=https://stx.schoolcompare.co.uk npx playwright test -g "compar"`) — staging still runs the OLD UI until this PR merges, so expect failures locally; the authoritative run is the Stage pipeline post-merge. Still commit only after jest+tsc are green.
+- [ ] Commit: `test(e2e): compare journeys for the parent-first redesign`
+
+---
+
+### Task 9: PR + post-merge verification
+
+- [ ] Full gates: `cd nextjs-app && npm test && npx tsc --noEmit`.
+- [ ] Push; open PR via Gitea API (credential-helper basic auth). PR body: before/after summary, link to mockups + spec §4/§8, the copy-verbatim rule, the fixed third-series bug, deploy note (needs PR #34's API on the same environment — merge order: #34 first), and that the e2e suite is the staging gate.
+- [ ] Post-merge: watch the Stage pipeline — its e2e run against staging is the real verification. Then the human tests staging and promotes (two-stage model). Update memory: compare redesign shipped to staging.
+
+---
+
+## Out of scope
+
+- IDACI / attendance / gender-absence / finance (post-v1, spec §4).
+- Backend changes of any kind (PR #34 must merge first).
+- Chart palette overhaul beyond the England-line addition (`CHART_COLORS` swap to the validated trio is a candidate follow-up, flagged not included — it affects every chart in the app).
@@ -0,0 +1,275 @@
+# Staged Production Promotion (Manual Gate) Implementation Plan
+
+> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
+
+**Goal:** Merging a PR deploys to staging only; production deployment requires a second, explicit human approval after manual testing on staging.
+
+**Architecture:** Split the existing single `deploy.yml` pipeline in two. The push-to-main workflow keeps build → staging deploy → e2e gate and **stops there**. A new `promote.yml` runs only on `workflow_dispatch` (the "Run workflow" button in Gitea's Actions UI, supported on this server — Gitea 1.26.4): it verifies the chosen commit passed the staging e2e gate, retags its `:sha-*` images to `:prod` (keeping `:prod-previous` for rollback), and triggers the Portainer prod webhook. Promotion granularity is a main-branch commit: staging always runs the latest main, so you approve a *state of main*, not an individual PR.
+
+**Tech Stack:** Gitea Actions (1.26.4), Docker buildx imagetools, Portainer webhooks, Gitea commit-status API.
+
+## Global Constraints
+
+- **Never push to `main` directly** — this change itself goes through a PR (`chore/staged-prod-promotion` branch).
+- Existing image tagging scheme is unchanged: `type=sha` (e.g. `sha-6f925ab`) + `:staging`; promotion still retags `:sha-*` → `:prod` with `:prod-previous` kept as the rollback pointer.
+- The e2e journeys remain a **hard gate before human testing** (a red staging never reaches the promote button) and the promote workflow must refuse to promote a commit whose staging e2e did not succeed.
+- Secrets already exist and are reused: `REGISTRY_TOKEN` (also a Gitea API token), `PORTAINER_STAGING_WEBHOOK`, `PORTAINER_PROD_WEBHOOK`, `STAGING_BASE_URL`, `PROD_BASE_URL`.
+- Staging quirk (memory): external `/api` is broken at the staging proxy — manual API testing happens from the host, not through stx.schoolcompare.co.uk; note it in the runbook, don't try to fix it in this plan.
+
+## Considered approaches (context for the reviewer)
+
+1. **Manual `workflow_dispatch` promote workflow (chosen).** Native on Gitea 1.26; the second approval is clicking "Run workflow" (or one API call) after testing staging. Least machinery, auditable via the Actions run history.
+2. *Tag-driven promotion* (`push: tags: promote-*`): works on any Gitea version; approval = pushing a tag. Slightly more scriptable, less discoverable; kept as documented fallback only.
+3. *GitOps `production` branch + promotion PR:* approval literally reuses the PR-review UI, but adds a second long-lived branch to keep in sync — too much ceremony for a solo project. Rejected.
+
+---
+
+### Task 0: Branch
+
+- [ ] `git checkout main && git pull && git checkout -b chore/staged-prod-promotion`
+
+---
+
+### Task 1: Stop the push-to-main workflow after the e2e gate
+
+**Files:**
+- Modify: `.gitea/workflows/deploy.yml`
+
+**Interfaces:**
+- Produces: images tagged `:sha-<short>` + `:staging` (unchanged), a green `E2E Journeys against Staging` commit status that Task 2's promote workflow checks by name. **Do not rename the `e2e-staging` job's `name:` without updating Task 2's status check.**
+
+- [ ] **Step 1: Remove the auto-promotion**
+
+In `.gitea/workflows/deploy.yml`:
+1. Change line 1 to: `name: Stage (build -> staging -> E2E gate)`
+2. Delete the entire `promote-prod` job (lines 196–240 in the current file: from `  promote-prod:` to the end of the file).
+3. Leave `build-*`, `deploy-staging`, and `e2e-staging` untouched.
+
+- [ ] **Step 2: Sanity-check the YAML**
+
+Run: `python3 -c "import yaml; yaml.safe_load(open('.gitea/workflows/deploy.yml')); print('yaml ok')"`
+Expected: `yaml ok`
+
+- [ ] **Step 3: Commit**
+
+```bash
+git add .gitea/workflows/deploy.yml
+git commit -m "ci: stop deploy pipeline at staging; production promotion becomes manual"
+```
+
+---
+
+### Task 2: Manual promote workflow
+
+**Files:**
+- Create: `.gitea/workflows/promote.yml`
+
+**Interfaces:**
+- Consumes: `:sha-<short>` images built by deploy.yml; the `E2E Journeys against Staging` commit status.
+- Produces: `:prod` and `:prod-previous` tags; prod stack update.
+
+- [ ] **Step 1: Write the workflow**
+
+```yaml
+name: Promote to Production (manual)
+
+on:
+  workflow_dispatch:
+    inputs:
+      sha:
+        description: >-
+          Commit SHA on main to promote (full or >=7 chars).
+          Leave empty to promote the latest main commit.
+        required: false
+        default: ""
+
+env:
+  REGISTRY: privaterepo.sitaru.org
+  BACKEND_IMAGE_NAME: ${{ gitea.repository }}-backend
+  FRONTEND_IMAGE_NAME: ${{ gitea.repository }}-frontend
+  PIPELINE_IMAGE_NAME: ${{ gitea.repository }}-pipeline
+
+jobs:
+  promote-prod:
+    name: Promote approved commit to Production
+    runs-on: ubuntu-latest
+    steps:
+      - name: Resolve target SHA
+        id: resolve
+        run: |
+          SHA_INPUT="${{ gitea.event.inputs.sha }}"
+          if [ -z "$SHA_INPUT" ]; then
+            SHA_INPUT="${{ gitea.sha }}"
+          fi
+          # Normalise to the full sha via the API so short inputs work
+          FULL_SHA=$(curl -fsS \
+            -H "Authorization: token ${{ secrets.REGISTRY_TOKEN }}" \
+            "https://${REGISTRY}/api/v1/repos/${{ gitea.repository }}/git/commits/${SHA_INPUT}" \
+            | python3 -c "import json,sys; print(json.load(sys.stdin)['sha'])")
+          SHORT_SHA="sha-$(echo "$FULL_SHA" | cut -c1-7)"
+          echo "full=$FULL_SHA" >> "$GITHUB_OUTPUT"
+          echo "short=$SHORT_SHA" >> "$GITHUB_OUTPUT"
+          echo "Promoting $FULL_SHA (images tagged $SHORT_SHA)"
+
+      - name: Verify the staging E2E gate passed for this commit
+        run: |
+          STATUS_JSON=$(curl -fsS \
+            -H "Authorization: token ${{ secrets.REGISTRY_TOKEN }}" \
+            "https://${REGISTRY}/api/v1/repos/${{ gitea.repository }}/commits/${{ steps.resolve.outputs.full }}/status")
+          echo "$STATUS_JSON" | python3 -c "
+          import json, sys
+          d = json.load(sys.stdin)
+          ok = [s for s in d.get('statuses', [])
+                if 'E2E Journeys against Staging' in s.get('context', '')
+                and s.get('status') == 'success']
+          if not ok:
+              print('REFUSED: no successful \"E2E Journeys against Staging\" status on this commit.')
+              print('Contexts found:', [s.get('context') for s in d.get('statuses', [])])
+              sys.exit(1)
+          print('E2E gate verified green for this commit.')
+          "
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Log in to Gitea Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ gitea.actor }}
+          password: ${{ secrets.REGISTRY_TOKEN }}
+
+      - name: Retag approved images as prod (keeping rollback pointer)
+        run: |
+          SHORT_SHA="${{ steps.resolve.outputs.short }}"
+          for IMAGE in \
+            "${REGISTRY}/${BACKEND_IMAGE_NAME}" \
+            "${REGISTRY}/${FRONTEND_IMAGE_NAME}" \
+            "${REGISTRY}/${PIPELINE_IMAGE_NAME}"; do
+            docker buildx imagetools create -t "${IMAGE}:prod-previous" "${IMAGE}:prod" || true
+            docker buildx imagetools create -t "${IMAGE}:prod" "${IMAGE}:${SHORT_SHA}"
+            echo "Promoted ${IMAGE}:${SHORT_SHA} -> :prod"
+          done
+
+      - name: Trigger production stack update
+        run: curl -fsSk -X POST "${{ secrets.PORTAINER_PROD_WEBHOOK }}"
+
+      - name: Wait for production to become healthy
+        run: |
+          echo "Polling ${PROD_BASE_URL} for up to 5 minutes..."
+          for i in $(seq 1 60); do
+            if curl -fsS -o /dev/null --max-time 10 "${PROD_BASE_URL}/"; then
+              echo "Production is up (attempt $i)"
+              exit 0
+            fi
+            sleep 5
+          done
+          echo "Production did not become healthy in time" >&2
+          exit 1
+        env:
+          PROD_BASE_URL: ${{ secrets.PROD_BASE_URL }}
+```
+
+Implementation notes for the engineer:
+- Gitea Actions uses the GitHub-compatible `$GITHUB_OUTPUT` file for step outputs; if the runner image doesn't populate it, fall back to `$GITEA_OUTPUT` (check the runner's docs/output at first run).
+- The retag step is copied verbatim from the old `promote-prod` job except the SHA comes from the resolved input instead of `gitea.sha` — behaviour for the default (empty input on latest main) is identical to before.
+- If `docker buildx imagetools create` fails with "not found" for `${IMAGE}:${SHORT_SHA}`, the chosen commit predates the registry's retention or never built — the error message is the desired behaviour (refuse loudly).
+
+- [ ] **Step 2: YAML sanity check**
+
+Run: `python3 -c "import yaml; yaml.safe_load(open('.gitea/workflows/promote.yml')); print('yaml ok')"`
+Expected: `yaml ok`
+
+- [ ] **Step 3: Commit**
+
+```bash
+git add .gitea/workflows/promote.yml
+git commit -m "ci: manual production promotion workflow with e2e-gate verification"
+```
+
+---
+
+### Task 3: Documentation — deploy model + runbook
+
+**Files:**
+- Modify: `docs/DEPLOY.md`
+- Modify: `claude.md` (the SDLC section)
+
+- [ ] **Step 1: Rewrite the flow description in `docs/DEPLOY.md`**
+
+Replace the staging→prod description with the new model (adapt to the file's existing structure; the substance to convey):
+
+```markdown
+## Deploy model
+
+1. **PR → main (first approval).** Branch-protected merge; PR checks
+   (typecheck, tests, builds, AI review) must pass.
+2. **Merge → staging (automatic).** Images are built once and tagged
+   `sha-<short>` + `staging`; the staging stack updates; Playwright
+   journeys in `e2e/` run against staging. A red e2e run means staging
+   is not fit for testing — fix forward before considering promotion.
+3. **Manual testing on staging.** stx.schoolcompare.co.uk. Note:
+   external `/api` is broken at the staging proxy — exercise API
+   endpoints from the host.
+4. **Promote → production (second approval).** Actions → "Promote to
+   Production (manual)" → Run workflow. Leave the SHA empty to promote
+   the latest main, or paste a specific commit SHA. The workflow
+   refuses commits whose staging e2e gate is not green, retags the
+   images `:prod` (keeping `:prod-previous`), and updates the prod
+   stack.
+
+### Promotion granularity
+
+Staging always runs the latest `main`. Promoting approves a *state of
+main*, not a single PR — if two PRs merged since the last promotion,
+they ship together. Test staging accordingly.
+
+### Rollback
+
+Re-run "Promote to Production (manual)" with the SHA of the last good
+commit (or retag manually: `docker buildx imagetools create -t
+<image>:prod <image>:prod-previous` for each of the three images, then
+POST the prod Portainer webhook).
+```
+
+- [ ] **Step 2: Update the SDLC bullet in `claude.md`**
+
+Replace the sentence "Merging to `main` deploys automatically: … retagged `:prod` and rolled out to production." with:
+
+```markdown
+- Merging to `main` deploys automatically **to staging only**: images
+  are built once, deployed to the staging Portainer stack, and verified
+  by the Playwright journeys in `e2e/`. Production is a second, manual
+  approval: the "Promote to Production (manual)" workflow in Gitea
+  Actions, run after testing the feature on staging. It refuses commits
+  whose staging e2e gate isn't green.
+```
+
+- [ ] **Step 3: Commit**
+
+```bash
+git add docs/DEPLOY.md claude.md
+git commit -m "docs: two-stage deploy model (staging auto, production manual)"
+```
+
+---
+
+### Task 4: PR + live validation
+
+- [ ] **Step 1: Push and open the PR** (Gitea API with credential-helper basic auth, as usual). PR body: the new model in three lines, the rollback recipe, and a warning that between merging this PR and its first promotion run, production receives no deployments (expected).
+
+- [ ] **Step 2: Validate after merge (human-in-the-loop):**
+1. Merge this PR → confirm the `Stage (build -> staging -> E2E gate)` run goes green and **no** production deployment happens (prod image digest unchanged: `docker buildx imagetools inspect <image>:prod` before/after, or check the Portainer prod stack's last-update time).
+2. Test something trivial on staging.
+3. Run "Promote to Production (manual)" with the SHA empty → confirm e2e verification passes, retag happens, prod becomes healthy.
+4. Negative test: run the promote workflow with a garbage SHA (e.g. `deadbeef1`) → confirm it fails at resolve/verify without touching `:prod`.
+
+- [ ] **Step 3: Update the ledger/memory** with the new deploy model so future sessions stop assuming auto-promotion.
+
+---
+
+## Out of scope / future options
+
+- Notifications when staging is ready for testing (Gitea can email on workflow completion; a webhook to ntfy/Matrix could be added later).
+- Restricting who can run the promote workflow: Gitea 1.26 runs `workflow_dispatch` with the permissions of the dispatching user; for a solo repo this is already effectively restricted.
+- The tag-driven fallback (`on: push: tags: promote-*`) if `workflow_dispatch` ever proves unreliable on the runner.
@@ -0,0 +1,215 @@
+# Exam Results Taxonomy — Phase Grouping and Sixth-Form Separation
+
+**Date:** 2026-07-07
+**Status:** Approved design (taxonomy/analysis only — no implementation in this doc's scope)
+
+## Purpose
+
+Classify every exam-result metric SchoolCompare displays today into four phase
+groups — **Primary**, **Secondary**, **Sixth form**, **Other** — and define an
+authoritative rule for separating schools that have a sixth form from those
+that don't. This document is the reference for:
+
+1. How the UI should group results sections and rankings by phase.
+2. The future KS5 (A-level) ingestion work — the Sixth form group lists the
+   concrete DfE metrics as placeholders with source columns.
+3. Replacing the fragile `age_range contains "18"` heuristic with the GIAS
+   `OfficialSixthForm` flag.
+
+## 1. Grouping principle
+
+Metrics are grouped by **the key stage of the assessment**, not by the phase
+of the school displaying them. An all-through school (4–18) shows metrics in
+all three exam groups; a pure primary shows only the Primary group.
+
+| Group | Assessments | Key stage | Taken at age | Data status |
+|---|---|---|---|---|
+| **Primary** | KS2 SATs (reading, writing TA, maths, GPS, science TA) | KS2 | 10–11 (Year 6) | ✅ Live — `marts.fact_ks2_performance` |
+| **Secondary** | GCSEs, Attainment 8 / Progress 8, EBacc | KS4 | 15–16 (Year 11) | ✅ Live — `marts.fact_ks4_performance` |
+| **Sixth form** | A levels, applied general, tech levels | KS5 (16–18) | 17–18 (Year 12–13) | ⏳ Not ingested — placeholders in §4 |
+| **Other** | Non-exam context displayed alongside results | n/a | n/a | ✅ Live — various marts |
+
+Not covered (not displayed today, candidates for future "Other"/Primary):
+EYFS Good Level of Development, Year 1 Phonics check, Year 4 Multiplication
+Tables Check, KS1 assessments (no longer published at school level by DfE).
+
+## 2. Metric-by-metric mapping (current site)
+
+Every key in `backend/schemas.py` `METRIC_DEFINITIONS` — the single source of
+truth for what the site displays — mapped to its phase group. `category` is
+the existing schema category; source columns are the DfE names used at
+ingestion (legacy performance-tables CSV for KS2, EES for KS4).
+
+### Primary (KS2 SATs)
+
+| Metric key | Category | DfE source column |
+|---|---|---|
+| `rwm_expected_pct` | expected | `PTRWM_EXP` |
+| `reading_expected_pct` | expected | `PTREAD_EXP` |
+| `writing_expected_pct` | expected | `PTWRITTA_EXP` |
+| `maths_expected_pct` | expected | `PTMAT_EXP` |
+| `gps_expected_pct` | expected | `PTGPS_EXP` |
+| `science_expected_pct` | expected | `PTSCITA_EXP` |
+| `rwm_high_pct` | higher | `PTRWM_HIGH` |
+| `reading_high_pct` | higher | `PTREAD_HIGH` |
+| `writing_high_pct` | higher | `PTWRITTA_HIGH` |
+| `maths_high_pct` | higher | `PTMAT_HIGH` |
+| `gps_high_pct` | higher | `PTGPS_HIGH` |
+| `reading_progress` | progress | `READPROG` |
+| `writing_progress` | progress | `WRITPROG` |
+| `maths_progress` | progress | `MATPROG` |
+| `reading_avg_score` | average | `READ_AVERAGE` |
+| `maths_avg_score` | average | `MAT_AVERAGE` |
+| `gps_avg_score` | average | `GPS_AVERAGE` |
+| `rwm_expected_boys_pct` | gender | `PTRWM_EXP_B` |
+| `rwm_expected_girls_pct` | gender | `PTRWM_EXP_G` |
+| `rwm_high_boys_pct` | gender | `PTRWM_HIGH_B` |
+| `rwm_high_girls_pct` | gender | `PTRWM_HIGH_G` |
+| `rwm_expected_disadvantaged_pct` | equity | `PTRWM_EXP_FSM6CLA1A` |
+| `rwm_expected_non_disadvantaged_pct` | equity | `PTRWM_EXP_NotFSM6CLA1A` |
+| `disadvantaged_gap` | equity | `DIFFN_RWM_EXP` |
+| `reading_absence_pct` | absence | `PTREAD_AT` |
+| `gps_absence_pct` | absence | `PTGPS_AT` |
+| `maths_absence_pct` | absence | `PTMAT_AT` |
+| `writing_absence_pct` | absence | `PTWRITTA_AD` |
+| `science_absence_pct` | absence | `PTSCITA_AD` |
+| `rwm_expected_3yr_pct` | trends | `PTRWM_EXP_3YR` |
+| `reading_avg_3yr` | trends | `READ_AVERAGE_3YR` |
+| `maths_avg_3yr` | trends | `MAT_AVERAGE_3YR` |
+
+The absence metrics measure absence *from KS2 tests*, so they belong to
+Primary even though they are not attainment scores. National comparators for
+this group come from `marts.fact_ks2_national_averages`.
+
+### Secondary (KS4 / GCSE)
+
+| Metric key | Category | EES source column |
+|---|---|---|
+| `attainment_8_score` | gcse | `attainment8_average` |
+| `progress_8_score` | gcse | `progress8_average` |
+| `english_maths_standard_pass_pct` | gcse | `engmath_94_percent` |
+| `english_maths_strong_pass_pct` | gcse | `engmath_95_percent` |
+| `ebacc_entry_pct` | gcse | `ebacc_entering_percent` |
+| `ebacc_standard_pass_pct` | gcse | `ebacc_94_percent` |
+| `ebacc_strong_pass_pct` | gcse | `ebacc_95_percent` |
+| `ebacc_avg_score` | gcse | `ebacc_aps_average` |
+| `gcse_grade_91_pct` | gcse | `gcse_91_percent` |
+
+Also stored in `marts.fact_ks4_performance` (and `fact_performance`) but not
+yet in `METRIC_DEFINITIONS` — Secondary group members when surfaced:
+`progress_8_lower_ci`, `progress_8_upper_ci`, `progress_8_english`,
+`progress_8_maths`, `progress_8_ebacc`, `progress_8_open`,
+`prior_attainment_avg` (KS2 baseline of the GCSE cohort), `sen_pct`.
+
+### Sixth form (KS5)
+
+No metrics today. The secondary school detail view renders a static note
+("Post-16 destination data coming soon") when the school has a sixth form.
+Placeholders for ingestion are specified in §4.
+
+### Other (non-exam context)
+
+Displayed alongside results but not tied to any assessment:
+
+| Metric key / surface | Category | Source |
+|---|---|---|
+| `disadvantaged_pct` | context | KS2 CSV `PTFSM6CLA1A` |
+| `eal_pct` | context | KS2 CSV `PTEALGRP2` |
+| `sen_support_pct` | context | KS2 CSV `PSENELK` (KS4 fallback `sen_no_ehcp_pupil_percent`) |
+| `stability_pct` | context | KS2 CSV `PTMOBN` |
+| Ofsted grades incl. `sixth_form_provision` / `rc_sixth_form` | — | `marts.fact_ofsted_inspection` |
+| Admissions (offers, oversubscription) | — | `marts.fact_admissions` |
+| Finance (per-pupil spend, cost shares) | — | `marts.fact_finance` |
+| Deprivation (IDACI) | — | `marts.fact_deprivation` |
+| Pupil characteristics (census) | — | `marts.fact_pupil_characteristics` |
+
+Note: the context metrics are cohort characteristics of the KS2 cohort at
+source, but they are presented (and should stay presented) as school-level
+context, so they group as Other, not Primary.
+
+## 3. Sixth-form separation
+
+### Definition (authoritative)
+
+> A school **has a sixth form** iff GIAS `OfficialSixthForm (name)` =
+> `"Has a sixth form"` for its URN.
+
+GIAS values are `Has a sixth form`, `Does not have a sixth form`, and
+`Not applicable` / blank. `Not applicable` (nurseries, primaries, PRUs) maps
+to **false**. This field is the DfE's registry flag, updated continuously,
+and is the only source that correctly classifies:
+
+- 16–19 sixth-form colleges and UTCs (age ranges like `14-19`, `16-19` that
+  the current substring heuristic misclassifies as *no* sixth form);
+- schools whose statutory age range extends to 18 on paper but which have no
+  registered post-16 provision.
+
+### Pipeline change (implemented 2026-07-07)
+
+1. `stg_gias_establishments.sql`: add
+   `"OfficialSixthForm (name)" as official_sixth_form`.
+2. `dim_school.sql` (+ `models.py` `DimSchool`, `_marts_schema.yml`): add
+   `has_sixth_form boolean` = `official_sixth_form = 'Has a sixth form'`.
+3. Expose `has_sixth_form` on the school API payloads.
+
+Implemented in `feat/gias-sixth-form-flag` — see
+`docs/superpowers/plans/2026-07-07-gias-sixth-form-flag.md`.
+
+### Current heuristic — audit of `age_range` ~ "18" sites
+
+All must migrate to the `has_sixth_form` flag once exposed:
+
+| Site | Current behaviour |
+|---|---|
+| `backend/app.py:419-422` | `/api/schools?has_sixth_form=yes\|no` filters on `age_range.str.contains("18")` |
+| `nextjs-app/components/SecondarySchoolDetailView.tsx:101` | "Sixth form" badge + coming-soon note from `age_range?.includes('18')` |
+| `nextjs-app/components/FilterBar.tsx:370-372` | Filter labels hard-code "(11-18)" / "(11-16)" — labels should drop the age-range parenthetical since sixth form ≠ age range |
+
+Fallback rule: if GIAS is blank for a URN (rare; new establishments), fall
+back to the age-range heuristic and log the URN.
+
+### UI separation rules
+
+- **School page**: schools with `has_sixth_form = true` show a Sixth form
+  results section (placeholder until KS5 data lands); schools without never
+  show it. Badge on the header as today, but driven by the flag.
+- **Search/rankings filter**: "With sixth form" / "Without sixth form" uses
+  the flag; applies to secondary and all-through phases.
+- **Comparison**: when comparing a with-sixth-form school against one
+  without, the Sixth form group renders "No sixth form" for the latter
+  rather than blank cells, making the structural difference explicit.
+
+## 4. Sixth form placeholders — future KS5 ingestion spec
+
+Source: DfE "A level and other 16 to 18 results" (EES, preferred — matches
+the KS4 EES tap) or legacy performance-tables `england_ks5final.csv`.
+Column names below are from the legacy KS5 CSV; verify against the EES
+release chosen at ingestion time.
+
+| Proposed metric key | Name | Legacy source column | Type |
+|---|---|---|---|
+| `alevel_aps_per_entry` | A level average points per entry | `TALLPPE_ALEV_1618` | score |
+| `alevel_avg_grade` | A level average grade (e.g. B-) | `TALLPPEGRD_ALEV_1618` | grade |
+| `academic_aps_per_entry` | Academic qualifications APS per entry | `TALLPPE_ACAD_1618` | score |
+| `applied_general_aps_per_entry` | Applied general APS per entry | `TALLPPE_AGEN_1618` | score |
+| `tech_level_aps_per_entry` | Tech level APS per entry | `TALLPPE_TLEV_1618` | score |
+| `english_progress_1618` | English progress (16–18, unfinished GCSE 4+) | `PROGENG_1618` | score |
+| `maths_progress_1618` | Maths progress (16–18) | `PROGMAT_1618` | score |
+| `ks5_cohort_size` | Students at end of 16–18 study | `TALLPUP_1618` | count |
+| `alevel_3plus_aab_pct` | % achieving AAB+ in ≥2 facilitating subjects | `TAAB2FAC_1618` | percentage |
+| `ks5_retention_pct` | Retention (completed main programme) | study-programme retention measure | percentage |
+| `ks5_destinations_pct` | Sustained education/employment destination | 16–18 destination measures dataset | percentage |
+
+Proposed landing shape mirrors KS4: `stg_ees_ks5.sql` →
+`int_ks5_with_lineage.sql` → `marts.fact_ks5_performance` (one row per URN
+per year), joined into `fact_performance`, with a `category: "sixth_form"`
+(or `"alevel"`) block added to `METRIC_DEFINITIONS`.
+
+## 5. Out of scope
+
+- Any implementation (pipeline, API, or UI changes) — this is the taxonomy
+  reference; implementation work items are §3 "Pipeline change", the
+  heuristic migration audit, and §4 ingestion, each to be planned separately.
+- Middle schools (deemed secondary/primary): they follow the assessment-based
+  grouping automatically — no special casing.
+- Independent schools: no DfE performance data published; unaffected.
@@ -0,0 +1,182 @@
+# GIAS Code Dictionaries — Codes in Marts, Names in Code
+
+**Date:** 2026-07-09
+**Status:** Implemented 2026-07-09 — see docs/superpowers/plans/2026-07-09-gias-code-dictionaries.md
+
+## Goal
+
+Six GIAS classification fields are stored in the marts as repeated name
+strings. Replace them with the official DfE integer codes and translate
+code → name in application code. After this change the marts carry only
+codes for:
+
+| GIAS field | Today (marts, string) | After (marts, int) |
+|---|---|---|
+| `TypeOfEstablishment (name)` | `dim_school.school_type` | `school_type_code` |
+| `EstablishmentStatus (name)` | `dim_school.status` | `status_code` |
+| `PhaseOfEducation (name)` | `dim_school.phase` | `phase_code` |
+| `OfficialSixthForm (name)` | (already reduced to `has_sixth_form` bool) | `official_sixth_form_code` in staging only; mart keeps the bool |
+| `ReligiousCharacter (name)` | `dim_school.religious_character` | `religious_character_code` |
+| `AdmissionsPolicy (name)` | `dim_school.admissions_policy` | `admissions_policy_code` |
+
+Motivation: smaller marts and stable enum values for filtering. (Honest
+sizing note: at ~25k open schools the raw performance win is modest; the
+durable benefits are storage, DfE-governed vocabulary, and filter values
+that can't drift with GIAS renames.)
+
+## Decisions (made during brainstorming)
+
+1. **GIAS native codes**, not custom enums. The GIAS bulk CSV publishes an
+   official `X (code)` column beside every `X (name)` column. We ingest the
+   DfE's own codes; no invented mapping to maintain.
+2. **Translation lives in the backend at the API boundary.** The API keeps
+   serving today's name strings; the frontend, e2e journeys, and API
+   consumers are untouched.
+
+## Design
+
+### 1. Tap (Singer schema)
+
+Add the six `(code)` columns to `GIASEstablishmentsStream.schema` in
+`pipeline/plugins/extractors/tap-uk-gias/tap_uk_gias/tap.py`:
+
+```
+"TypeOfEstablishment (code)", "EstablishmentStatus (code)",
+"PhaseOfEducation (code)", "OfficialSixthForm (code)",
+"ReligiousCharacter (code)", "AdmissionsPolicy (code)"
+```
+
+The `(name)` columns **stay declared** — raw keeps both so we can detect
+dictionary drift (§4) and regenerate dictionaries from live data.
+
+### 2. Staging (`stg_gias_establishments.sql`)
+
+- Add int casts: `school_type_code`, `status_code`, `phase_code`,
+  `official_sixth_form_code`, `religious_character_code`,
+  `admissions_policy_code` (all `cast(nullif(trim(...), '') as integer)`).
+- Remove the corresponding name columns from the staging select
+  (`school_type`, `status`, `phase`, `official_sixth_form`,
+  `religious_character`, `admissions_policy`). Names live only in raw.
+
+### 3. Marts
+
+**`dim_school`** stores codes only:
+
+- `school_type_code`, `status_code`, `phase_code`,
+  `religious_character_code`, `admissions_policy_code` replace their
+  string columns.
+- Status filter becomes `where status_code in (<open>, <proposed-to-close>)`.
+  The numeric values are read from live raw data at implementation time
+  (`select distinct "EstablishmentStatus (code)", "EstablishmentStatus (name)"`),
+  never assumed from memory. Same filter in `dim_location`.
+- `has_sixth_form` derives from `official_sixth_form_code`
+  (`<has-code>` → true, `<does-not>/<not-applicable>` → false, null →
+  `statutory_high_age >= 18` fallback). The `lower(trim(...))` string guard
+  becomes obsolete and is removed.
+- `phase_code` derivation keeps today's cascade but emits codes:
+  1. GIAS `phase_code` when it is a real value (not the not-applicable code);
+  2. statutory-age inference emits the matching GIAS code
+     (Primary / Secondary / All-through — numeric values confirmed from
+     live data at implementation);
+  3. school-name heuristics (unchanged — they match `school_name`, which is
+     not one of the six fields) emit the same codes;
+  4. else null.
+- dbt schema tests: `accepted_values` (severity **warn**) on every code
+  column, values taken from the dictionary; `not_null` warn on `phase_code`
+  (mirrors today's phase test); `has_sixth_form` tests unchanged.
+
+**`dim_location`**: only the status filter changes (must stay byte-identical
+to `dim_school`'s — the API inner-joins the two).
+
+### 4. Dictionaries
+
+**Canonical module: `backend/gias_codes.py`**
+
+```python
+ESTABLISHMENT_STATUS: dict[int, str]
+SCHOOL_TYPE: dict[int, str]
+PHASE_OF_EDUCATION: dict[int, str]
+OFFICIAL_SIXTH_FORM: dict[int, str]
+RELIGIOUS_CHARACTER: dict[int, str]
+ADMISSIONS_POLICY: dict[int, str]
+
+def translate(code: int | None, mapping: dict[int, str]) -> str | None:
+    """None -> None; unknown code -> 'Unknown (<code>)' + warning log."""
+```
+
+- Contents are generated from live raw data
+  (`SELECT DISTINCT code, name FROM raw.gias_establishments ...` per field)
+  and sanity-checked against the DfE GIAS registers. Names must be
+  byte-identical to what the API serves today.
+- Unknown codes never blank the UI: `translate` returns `"Unknown (<code>)"`
+  and logs, so a new DfE value degrades gracefully.
+
+**Pipeline copy: `pipeline/scripts/gias_codes.py`**
+
+The app and pipeline Docker images have disjoint build contexts
+(`Dockerfile` copies `backend/`; `pipeline/Dockerfile` copies `pipeline/`),
+so the Typesense sync cannot import the backend module. It gets a
+byte-identical copy, and a backend unit test asserts
+`backend/gias_codes.py` and `pipeline/scripts/gias_codes.py` have identical
+content — drift fails CI. (Deliberately chosen over codegen: six dicts do
+not justify build machinery.)
+
+**Seed for drift detection: `pipeline/transform/seeds/gias_code_names.csv`**
+
+Columns `field,code,name` mirroring the dictionary. A dbt test (severity
+warn) compares live raw `(code, name)` pairs against the seed; when DfE adds
+or renames a value the nightly run warns, prompting a dictionary + seed
+update in one PR.
+
+### 5. Backend translation (API contract unchanged)
+
+- `_MAIN_QUERY` selects the code columns instead of the name columns.
+- `load_school_data_as_dataframe()` translates immediately after
+  `pd.read_sql`, writing today's column names:
+
+```python
+df["phase"]                  = df["phase_code"].map(...)
+df["school_type"]            = df["school_type_code"].map(...)   # then normalize_school_type as today
+df["status"]                 = df["status_code"].map(...)
+df["religious_denomination"] = df["religious_character_code"].map(...)
+df["admissions_policy"]      = df["admissions_policy_code"].map(...)
+```
+
+Everything downstream — `PHASE_GROUPS`, filters, payload builders,
+`/api/filters`, frontend, e2e — sees exactly today's strings. No frontend
+changes.
+
+- `backend/models.py` `DimSchool`: string columns replaced by
+  `*_code = Column(Integer)`.
+
+### 6. Typesense sync
+
+`pipeline/scripts/sync_typesense.py` selects `phase`, `school_type`,
+`religious_character` today. It switches to the code columns and translates
+via `pipeline/scripts/gias_codes.py` before indexing, so facet values in
+search are unchanged.
+
+### 7. Rollout
+
+- No DB migration: marts are full-rebuild tables.
+- Deploy window: until the first post-merge pipeline run, the old marts
+  still carry string columns while the new backend queries code columns, so
+  the backend's query fails and it serves empty data (the one-column retry
+  built for `has_sixth_form` doesn't generalise to six columns, and a full
+  old-schema fallback query isn't worth it). **Decision: accept the window
+  and close it operationally — the runbook is merge → deploy → trigger
+  `school_data_daily` immediately.** The DAG's final step already calls
+  `/api/admin/reload`, so the backend recovers without a restart.
+- Tests: backend unit tests for `translate()` (known / unknown / None),
+  payload tests asserting names still served, the file-parity test, dbt
+  schema/seed tests. Frontend: no changes; existing Jest suite is the
+  regression net.
+
+## Out of scope
+
+- Recoding other string columns (`gender`, `urban_rural`,
+  `nursery_provision`, `local_authority_name` …) — same pattern can follow
+  later if this proves out.
+- Collapsing academy subtypes (today's `normalize_school_type`) — kept
+  as-is, applied after translation.
+- Serving codes through the API — the contract deliberately keeps names.
@@ -0,0 +1,177 @@
+# Compare Screen Redesign — Expert Data Review
+
+**Date:** 2026-07-11
+**Reviewer:** subagent briefed as an English education-standards / DfE-Ofsted data expert
+**Subject:** desktop + mobile compare mockups and the redesign spec
+(`2026-07-11-compare-screen-redesign-design.md`)
+**Status:** first-pass must-fixes applied 2026-07-12; second-pass
+findings (below) applied 2026-07-12 — mockups + spec §4/§8 updated
+
+## Must-fix
+
+1. **COVID gap is wrong and drops a real results year.** KS2 tests were
+   cancelled 2019/20 and 2020/21 only; they resumed in 2021/22 with
+   published school-level results (England RWM ≈ 59%). The mockup charts
+   omit 2021/22 entirely and the tooltip claims no tests were held
+   2019/20–2021/22. Fix: add 2021/22 to axis and all series; shrink the
+   gap band; optionally annotate 2021/22 with DfE's post-pandemic
+   comparability caution.
+2. **Report-card at-a-glance summary miscounts areas.** Detail list has
+   4 Strong / 2 Expected / 1 Attention needed + Safeguarding met, but
+   the summary says "3 areas Expected standard" — it counts safeguarding
+   as a graded area. Safeguarding is a separate binary judgement and
+   must be excluded from rating counts.
+3. **"Where the offers went" derivation is unsound.** Places − 1st-pref
+   offers ≠ "second or third choices": the residual can include 4th–6th
+   preference offers (pan-London scheme) and LA-allocated children who
+   didn't choose the school; and offers don't necessarily equal PAN.
+   Use the real 2nd/3rd-preference fields being promoted from
+   `raw.ees_admissions`; until then drop the row.
+4. **Ofsted timeline in the copy is wrong.** Overall grades were
+   abolished September 2024, not November 2025; Sept 2024–Nov 2025
+   inspections kept the four key judgements without an overall grade
+   (ungraded inspections carried grades forward). Neither mockup shows
+   the interim regime, which will dominate real comparisons. Fix copy
+   and add an interim example.
+5. **Barclay's "published an overall grade only — no area-by-area
+   detail" misdescribes inspections.** No inspection type does that; a
+   2021 graded inspection necessarily had subgrades — the gap is in our
+   dataset. If it was an ungraded (s8) inspection, "Outstanding" is a
+   carried-forward grade and should say so. Fix: "We don't hold
+   area-by-area detail for this inspection", and distinguish graded vs
+   ungraded in the data model.
+
+## Should-fix
+
+6. Writing is teacher assessment, not a test — "national tests and
+   teacher assessments"; note TA caveat on the Writing strip.
+7. Verify renewed-framework wording against Ofsted's final toolkit:
+   likely "Needs attention" (not "Attention needed") and "Personal
+   development and well-being" (which otherwise collides with the
+   identically-named legacy judgement). Pin every label to the
+   published toolkit.
+8. "Expected standard" now means two things on one page (Ofsted area
+   rating vs KS2 measure) — disambiguate in tooltips.
+9. Disadvantaged row: DfE definition includes looked-after / previously
+   looked-after children, not just FSM6; benchmark labels inconsistent
+   across desktop/mobile; subgroup percentages need cohort sizes or a
+   volatility threshold before chips are attached.
+10. "Trend, last 7 years" spans ten years; sparklines render the COVID
+    gap as equal spacing (the exact defect the audit criticises) and
+    "Improved: 52% → 87%" endpoint-cherry-picks a volatile series.
+11. At-a-glance "Getting a place" uses different metrics per school
+    (Barclay is also oversubscribed on total preferences but shows a
+    green chip). Standardise on first-preference success %. Explain the
+    equal-preference rule; condition "living close by matters" on the
+    school's actual oversubscription criteria.
+12. "457 applications for 180 places" = total preferences at any rank,
+    not head-to-head applicants; lead with first preferences vs places.
+    Add offers-vs-final-intake (waiting lists/appeals) caveat.
+13. Elmhurst's subgrade list is likely missing Early years provision
+    (school has a nursery) — possible pipeline gap.
+14. "Ofsted rating" label is obsolete post-Sept-2024 — use "Latest
+    Ofsted inspection"; check whether Oct 2021 is the latest inspection
+    or merely the latest graded one.
+15. SEN: "EHCP plans" is redundant; 28% SEN support often indicates
+    resourced provision — add a note; England SEN-support ≈ 14%, not 13%.
+
+## Nice-to-have
+
+16. Consistent labelling of official DfE vs dataset-computed benchmarks
+    (and medians shouldn't be called averages inconsistently).
+17. England 2015/16 RWM (53%) exists in DfE publications — the null is
+    a dataset gap; source it or the England line looks broken.
+18. "1 in 4 first choices missed out" — actually more than 1 in 4.
+19. "1,273 of 1,260 places (full)" is over capacity; capacity figures
+    are often stale — say "at or above capacity".
+20. State the actual suppression rule (DfE: ≤5 pupils suppressed,
+    small numbers rounded) instead of "a handful".
+21. Spec §4.3 progress chips can't exist for displayed years: KS2
+    progress ended with 2022/23 (no KS1 baseline) and returns
+    ~2027/28 with the reception baseline. Make explicit in the spec.
+    IDACI (spec §4.5) is absent from mockups; if shipped, caveat it
+    describes pupils' neighbourhoods, not the school.
+22. Tooltips should give the official term "first preference" alongside
+    the plain-English "first choice".
+
+## Overall assessment (verbatim gist)
+
+The bones are genuinely good by education-data standards —
+England-average anchoring, explicit non-comparability messaging across
+Ofsted regimes, refusal to synthesise an overall grade, time-true
+x-axis, neutral FSM/EAL framing — better than most commercial
+school-comparison sites. But items 1–5 are outright factual errors or
+misdescriptions that a well-informed parent or Ofsted would catch;
+the admissions section needs the most conceptual work (equal
+preference, preferences-vs-applicants, offers-vs-intake). Fix 1–5
+before user testing; the rest fold into the planned PRs.
+
+---
+
+# Second-pass review (2026-07-12)
+
+Same reviewer, after the must-fixes and the new three-tier metric
+exposure model were applied.
+
+## Verification of first-pass must-fixes
+
+- **1 (COVID/2021/22): resolved.** Time-true axis, band covers only the
+  cancelled years, England 58.7% consistent with official figures,
+  dataset gaps break lines honestly; reading/maths England series all
+  match published figures; RWM ≤ min(subject) checks pass.
+- **2 (report-card count): resolved** — safeguarding excluded, spec §8.2.
+- **3 (offers derivation): resolved** — row removed, spec §8.3 bans it.
+- **4 (Ofsted timeline): resolved on desktop; mobile omits the interim
+  regime clause** (see finding 6).
+- **5 (Barclay explanation): resolved.**
+
+## New findings
+
+1. **Should-fix — scaled-score strip domain contradicts caption.**
+   Caption says "scaled scores run 80–120", strips render 100–120;
+   truncated domain exaggerates small gaps and below-100 averages
+   would fall off the edge. Render 80–120, or caption the 100–120
+   window honestly and define below-100 behaviour.
+2. **Should-fix — scaled-score England ticks (106/105/105) unsourced.**
+   Plausible but hand-entered; verify against DfE 2024/25 tables and
+   add loading official England scaled scores to the pipeline list
+   (absent from §8.1/§8.6).
+3. **Should-fix — "Writing" listed under "Higher standard" in the
+   picker.** Writing TA outcome is "greater depth" (GDS), never
+   "higher standard". Label "Writing — greater depth (teacher
+   assessment)"; tooltip the combined higher-standard composition.
+4. Nice — "grammar & punctuation" summary line drops "spelling" (GPS).
+5. Nice — science is teacher-assessed (no KS2 test since 2009) and
+   coarse; tooltip it like writing; reconsider its tier-2 slot.
+6. **Should-fix — mobile Ofsted copy skips the interim regime**
+   (Sept 2024–Nov 2025) that desktop explains. One clause fixes it.
+7. **Should-fix — benchmark provenance still inconsistent** (EAL
+   tooltip unsourced; FSM/disadvantaged chips vs tooltips use three
+   vocabularies; header note says all England averages are official).
+   Adopt one house style: official = "England average", computed =
+   "benchmark / typical state school (our dataset)". Also tighten EAL
+   definition to census wording ("first language known or believed to
+   be other than English").
+8. Nice — "community primaries" distance note attached to an academy
+   (Elmhurst); say "non-faith primaries" or condition on policy field.
+9. Nice — "Improving since 2022" → "since 2022/23".
+10. Nice — England chart tooltips show decimals; §7 mandates whole
+    percents.
+
+## Residual gaps not covered by spec §8
+
+11. Spec promises IDACI-in-words, Attendance section, and tier-2
+    gender/absence that the mockups never show — mark post-v1 or
+    demonstrate, so implementation scope is unambiguous.
+12. Add official England scaled-score averages to the pipeline task
+    list.
+13. Add the writing/greater-depth terminology rule to §8.7.
+
+## Verdict
+
+All must-fixes genuinely resolved; the tier model is conceptually
+sound ("no measure is lost", honest dataset-gap breaks, grouped
+picker). Remaining issues are contained: one internal contradiction
+(80–120 vs 100–120), one provenance inconsistency, one terminology
+error (writing/GDS). With findings 1–3 and 6–7 addressed, the data
+framing is fit to put in front of parents.
@@ -0,0 +1,324 @@
+# Compare Screen Redesign — Audit & Design
+
+**Date:** 2026-07-11
+**Status:** Draft — awaiting review
+**Scope:** `/compare` page (nextjs-app), `/api/compare` endpoint (backend)
+
+## 1. Audit of the current screen
+
+The current compare page (`nextjs-app/components/ComparisonView.tsx`) is a
+single-metric analyst tool: a `<select>` with ~40 KS2/GCSE metrics, one
+line chart over time, and a year-by-year table — all for the one selected
+metric. Observed on production with 3 primary schools:
+
+**What works**
+
+- URL-shareable state (`?urns=…&metric=…`), native share sheet.
+- Phase tabs (primary/secondary) with sensible auto-detection.
+- Colour-coded school cards tied to chart series.
+- Metric descriptions from `/api/metrics` (single source of truth).
+
+**What doesn't**
+
+1. **Performance-only.** The database already holds Ofsted inspections,
+   admissions/oversubscription history, pupil characteristics (FSM/EAL),
+   SEN, deprivation (IDACI), finance, capacity, faith, gender, trust —
+   none of it reaches the compare screen. `/api/compare` returns only
+   `yearly_data` + minimal `school_info`, while `/api/schools/{urn}`
+   already returns all supplementary blocks.
+2. **One metric at a time.** A parent must know which of ~40 metrics
+   matters, select each in turn, and hold results in their head. There is
+   no side-by-side overview and no way to see two dimensions at once.
+3. **No benchmarks.** Numbers float without anchors: is 79% RWM good?
+   The DB has official national averages (`fact_ks2_national_averages`)
+   but the page never shows them.
+4. **Domain jargon untranslated.** "GPS Expected %", "Progress scores",
+   "RWM Combined" assume DfE literacy. The only plain-English help is one
+   note for progress scores.
+5. **Raw numbers, no judgement support.** 87.0% vs 92.0% vs 79.0% — the
+   page never says "all three are well above the England average of 62%",
+   which is the fact a parent actually needs.
+6. **Bugs/paper cuts observed:** the third school's series did not render
+   on the production chart despite table data (worth a separate fix);
+   the COVID gap (2018/19 → 2022/23) renders as equal spacing with no
+   annotation; table shows "87.0%" precision that implies false accuracy.
+
+## 2. Data inventory (available vs shown)
+
+| Domain | Source table | On detail page | On compare |
+|---|---|---|---|
+| KS2 attainment/progress | fact_ks2_performance | yes | **yes** (only thing shown) |
+| National averages | fact_ks2_national_averages | partial | no |
+| Ofsted (latest + subgrades + report-card fields) | fact_ofsted_inspection, dim_school | yes | no |
+| Admissions & oversubscription (multi-year) | fact_admissions | yes | no |
+| Pupil characteristics (FSM, EAL, gender split) | fact_pupil_characteristics | yes | no |
+| Context (SEN, disadvantaged, stability, absence) | fact_ks2_performance | via metric picker | buried in picker |
+| Deprivation (IDACI) | fact_deprivation | yes | no |
+| Finance (per-pupil spend) | fact_finance | yes | no |
+| School facts (capacity, faith, ages, trust, nursery, gender) | dim_school | yes | no |
+| Location/distance | dim_location | map | no |
+
+## 3. Design goals
+
+1. **Answer parent questions, in order:** Is it a good school (Ofsted)?
+   Do children do well there (academics vs England)? Will my child get a
+   place (admissions)? What is the school like (size, community, faith)?
+2. **Every number gets an anchor** — the England average, rendered as a
+   consistent visual tick, plus a plain-English chip
+   (Above / Close to / Below England average).
+3. **Plain English first, jargon on demand.** Labels are questions or
+   sentences ("Children reaching the expected standard in reading,
+   writing and maths"), codes/acronyms live in tooltips.
+4. **Scan whole-picture first, drill down second.** The single-metric
+   trend explorer survives, demoted to an "Explore trends" section at the
+   bottom rather than being the entire page.
+
+## 4. Proposed structure
+
+Columns = schools (max 4 visible on desktop, horizontal scroll beyond),
+rows = dimensions. Sticky compact school header keeps column identity
+while scrolling. Sections, in order:
+
+1. **At a glance** — verdict row per school: Ofsted badge, headline
+   attainment vs England (dot strip + chip), oversubscription chip,
+   size, distance (when a location is set).
+2. **Ofsted inspection** — must handle all three inspection regimes,
+   which will coexist in comparisons for years:
+   - **Legacy graded (pre-Sept 2024):** overall grade badge
+     (Outstanding/Good/Requires improvement/Inadequate). Subgrades,
+     where published, are rendered in the **same area-by-rating chip
+     list UX as report cards** (one row per judgement area, rating as
+     a chip) — one visual grammar for inspection detail across both
+     regimes. Where our dataset has no subgrades for an inspection,
+     say so honestly ("We don't hold area-by-area detail for this
+     inspection") and point to the school's Ofsted page — never claim
+     the inspection itself published no detail (graded inspections
+     always have subgrades; if it was ungraded, the grade is
+     carried forward and must be labelled as such).
+   - **Interim ungraded (Sept 2024 – Nov 2025):** parsed outcome
+     ("remains Good") shown as the effective grade, marked as such.
+   - **Renewed framework report card (from Nov 2025):** no overall
+     grade exists. Render the report card as an area-by-rating list
+     using Ofsted's 5-point scale (Exceptional / Strong standard /
+     Expected standard / Attention needed / Urgent improvement) across
+     the evaluation areas we model (`rc_inclusion`,
+     `rc_curriculum_teaching`, `rc_achievement`,
+     `rc_attendance_behaviour`, `rc_personal_development`,
+     `rc_leadership_governance`, `rc_early_years`, `rc_sixth_form`)
+     plus the separate safeguarding met/not-met flag. **At-a-glance
+     summary rule:** never an unlabelled colour strip — summarise by
+     counting areas per rating, best first ("5 areas Strong standard ·
+     3 areas Expected standard"), and always name any area rated
+     Attention needed or Urgent improvement explicitly (never fold
+     problems into a count), plus "Safeguarding not met" whenever that
+     flag is false. When everything is Expected standard or better,
+     add the reassurance line "No areas need attention".
+   When a comparison mixes regimes, show a one-line comparability note
+   ("Ofsted changed how it reports in Nov 2025 — a report card and an
+   older overall grade aren't directly comparable"). Never derive a
+   fake overall grade from report-card areas.
+3. **Academics (KS2)** — one dot-strip row per headline measure (RWM
+   expected, RWM higher, reading/writing/maths expected), each with the
+   England-average tick and per-school dots; copy must say "tests and
+   teacher assessments" (writing is TA, not a test). Progress scores
+   translated to Above/Average/Below chips (CI-based) — **but note KS2
+   progress measures ended with 2022/23** (no KS1 baseline afterwards)
+   and return only when the reception-baseline cohort reaches Y6
+   (~2027/28), so progress chips apply to historical years in the
+   trends explorer, not the headline view. Sparkline per school over
+   the full published period, with an honest gap for the cancelled
+   test years (2019/20–2020/21). Disadvantaged-pupils row under an
+   "Equity" subheading, always with cohort size shown and DfE's full
+   definition (FSM6 **or** looked-after/previously looked-after).
+4. **Getting a place** — oversubscription ratio as plain sentence
+   ("184 applications for 80 places"), first-preference success %, trend
+   vs last year, admissions policy.
+5. **Who goes there** — pupils on roll (vs capacity), boys/girls, FSM %,
+   EAL %, SEN support %, faith, ages, nursery, trust. *Post-v1:* IDACI
+   decile in words (needs a coverage check of `fact_deprivation` and
+   the neighbourhood-not-school caveat, §8.7).
+6. **Attendance** — *post-v1.* The KS2 test-day absence fields are the
+   only per-school absence data we hold; they're near-zero for most
+   schools and easy to misread as general attendance. Ship only if a
+   general-absence source lands.
+7. **Explore trends** (existing feature, collapsed) — metric picker +
+   multi-year line chart + table, with an added England-average
+   reference line and a COVID-gap annotation.
+
+**Metric exposure model (three tiers).** No measure from the current
+page is lost; they surface at three levels of prominence:
+- **Tier 1 — headline strips (always visible):** RWM expected,
+  reading/writing/maths expected, RWM higher standard.
+- **Tier 2 — "More measures" expansion inside Academics:** GPS and
+  science expected % (science labelled teacher-assessed), average
+  scaled scores (reading/maths/GPS, same dot-strip grammar showing
+  the 100–120 window of the 80–120 scale, widening below 100, with
+  the England tick) — one tap/click away, same visual language.
+  *Post-v1:* gender split and absence (see §4.6).
+- **Tier 3 — Explore trends:** the full grouped catalogue (the
+  current page's ~40 metrics, including equity and school-context
+  measures, and the GCSE set for secondary phase) drives the
+  year-by-year chart and table via the grouped metric picker.
+The tier assignment is a content decision per phase (secondary:
+Attainment 8, Progress 8 banding, grade 5+ English & maths as tier 1;
+EBacc and subject entries as tier 2).
+
+Finance (per-pupil spend) is deliberately deferred: low parent value,
+risk of misreading. Revisit later.
+
+**Mobile (design target — mobile first):** the desktop grid is the
+adaptation, not the other way round. On mobile the layout goes
+*measure-first*: each row is one measure with all schools listed under
+it (colour dot + short name + value + chip), so comparison never
+requires horizontal swiping between school cards. A sticky horizontal
+school-chip bar keeps identity and add/remove available while
+scrolling. Dot strips already read measure-first and carry over
+unchanged. The trend chart scrolls horizontally inside its container.
+
+## 5. Data strategy — existing dataset only
+
+Constraint (agreed 2026-07-11): use only data already in marts plus
+fields already present in the `raw` schema extracts we pull today.
+No new external sources.
+
+**Gaps in the mockup, resolved within this constraint:**
+
+| Mockup element | Resolution |
+|---|---|
+| England average for disadvantaged pupils | Compute from our own data: `stg_ees_ks2` already pivots the Disadvantaged breakdown per school; aggregate it (weighted by eligible pupils) into `fact_ks2_national_averages` or compute in the API. Label it "England average (state schools)". |
+| England context for FSM / EAL / SEN chips | Compute dataset-wide medians per phase, same pattern as `/api/national-averages` does for KS4. |
+| "Much larger than average" size label | Dataset median pupils-on-roll per phase. |
+| Ofsted link | We don't have deep links to the latest report, so always link to the school's Ofsted provider page, `https://reports.ofsted.gov.uk/provider/21/{urn}`, derived from URN (label it "the school's Ofsted page", not "the report"). |
+
+**Raw fields we already pull but don't store — promote to marts (one
+dbt/pipeline PR, no tap changes):**
+
+- `raw.ees_admissions`: 2nd/3rd preference applications and offers,
+  total-preference counts, cross-LA applications and offers → richer
+  "Getting a place" (e.g. "offers reached 2nd-choice families",
+  competition from outside the borough).
+- `raw.ees_ks2_attainment`: progress-measure confidence intervals and
+  "working towards" % → lets the Above/Average/Below progress chips be
+  statistically honest (band by CI overlap with 0, mirroring DfE
+  methodology) instead of thresholding the point estimate.
+- `raw.ees_ks4_performance` / `ees_ks4_info`: `progress8_banding`
+  (DfE's own plain-English "well above average … well below average"
+  label — exactly the chip we want for secondary), EBacc entry/APS,
+  grade-5+ English & maths, `attainment8_diffn`/`progress8_diffn`
+  (disadvantage gaps) → the secondary-phase version of the Academics
+  section.
+- `raw.ees_census`: young-carer % and the ethnicity breakdown →
+  optional "Who goes there" enrichment; hold for a later iteration
+  (presentation needs care), but the data requires no new extract.
+- `raw.ofsted_inspections` / tap-uk-ofsted: the `rc_*` report-card
+  columns exist in staging/marts but are stubbed `null` — the tap has a
+  TODO to map the report-card column names from the Ofsted MI file
+  (same monthly extract we already download; inspections from Nov 2025
+  onward carry them). This is the one promotion that needs a small tap
+  schema addition, and it's a prerequisite for the new-framework Ofsted
+  display above.
+
+Explicitly out (not in any current extract): school-level phonics,
+workforce/teacher data, per-school attendance beyond the KS2 test-day
+absence fields, Ofsted report-card documents themselves.
+
+## 6. API changes
+
+Extend `GET /api/compare` response per URN with the same supplementary
+blocks the detail endpoint already builds (`get_supplementary_data`):
+`ofsted`, `census`, `admissions` (+ `admissions_history`), `deprivation`,
+plus a top-level `national_averages` block for the latest year. Reuse the
+existing function; no new tables. Response stays backward-compatible
+(additive fields only). Add derived helper fields server-side or compute
+chips client-side from `national_averages` (client-side preferred — no
+schema churn).
+
+## 7. Accessibility & comprehension devices
+
+- Verdict chips are text + colour + position (never colour alone).
+- Every acronym has a tooltip using existing `MetricTooltip`.
+- "How to read this" one-liner at the top of each section.
+- Chart palette: coral `#e07256`, teal `#00949b`, purple `#8664c9`
+  (validated: lightness band, chroma, CVD separation, contrast — the
+  current `--chart-2/-4` tokens fail chroma/contrast checks and should
+  be nudged to these).
+- Numbers rounded to whole percents; England tick labelled on first use.
+
+## 8. Expert-review requirements
+
+An adversarial review by an education-data expert (full findings in
+`2026-07-11-compare-screen-expert-review.md`) was applied to the
+mockups on 2026-07-12. The following are binding requirements for
+implementation, beyond what the mockups can show:
+
+1. **Chart truthfulness:** KS2 tests were cancelled 2019/20–2020/21
+   only. **2021/22 school-level figures are a permanent source gap** —
+   DfE stated it would not publish KS2 2021/22 in performance tables
+   (verified 2026-07-12 against EES, the CSP download service, and
+   DfE release notes; see `# TASK 6 VERIFICATION` in
+   `pipeline/scripts/diagnose_compare_gaps.py`). The chart's England-
+   only 2021/22 point with broken school lines is therefore the
+   correct permanent rendering; copy should say "DfE didn't publish
+   school-level figures for 2021/22", not "not in our dataset yet".
+   The 2015/16 national figure and the GPS/science/scaled-score
+   England averages ARE loadable (mapping already correct; refreshed
+   raw extract backfills them). Never render missing years as if time
+   were continuous.
+2. **Report-card summaries** count graded areas only — safeguarding is
+   a separate binary flag, never included in rating counts.
+3. **Admissions:** use the real preference-breakdown fields from
+   `raw.ees_admissions`; never derive "lower-preference offers" as
+   places − first-preference offers. Frame total applications as
+   "named on N forms" (any rank), lead with first-preference success,
+   and standardise at-a-glance chips on that one metric. Explain the
+   equal-preference rule; caveat offers vs final intake (waiting
+   lists/appeals); condition "distance decides" on the school's actual
+   oversubscription criteria where we have the admissions-policy field.
+4. **Ofsted:** overall grades ended September 2024 (report cards from
+   November 2025); the interim regime must be renderable. Distinguish
+   graded (s5) vs ungraded (s8) inspections and surface carried-forward
+   grades as such; "we don't hold the detail" is a statement about our
+   dataset, never about the inspection. Verify every scale/area label
+   against Ofsted's final published toolkit before launch (e.g. "Needs
+   attention" vs "Attention needed"; "Personal development and
+   well-being" vs the identically-named legacy judgement). Check
+   whether a school's latest inspection is merely its latest *graded*
+   one. Confirm Early years provision subgrades flow through the
+   pipeline for schools with nurseries.
+5. **Subgroup honesty:** disadvantaged-pupil percentages carry cohort
+   sizes and follow the DfE suppression rule (≤5 pupils suppressed);
+   state the rule verbatim in the footer.
+6. **Benchmark provenance:** official DfE figures and
+   dataset-computed benchmarks must be labelled distinctly and
+   consistently everywhere (a computed median is a "benchmark",
+   not an "England average").
+7. **Copy details:** "Latest Ofsted inspection" (not "Ofsted rating");
+   "EHC plans"; SEN-support benchmark ≈14%; high SEN share may
+   indicate resourced provision (say so neutrally); "at or above
+   capacity" rather than "full" (capacity data is often stale);
+   disambiguate Ofsted's "Expected standard" from the KS2 measure;
+   give official terms ("first preference") alongside plain English.
+   Writing has no "higher standard" — its TA outcome is "greater
+   depth (GDS)"; never list writing under a higher-standard group.
+   Science and writing are teacher-assessed and must be labelled as
+   such (no KS2 science test since 2009). House style for benchmark
+   provenance: official DfE figures say "England average"; computed
+   figures say "state-school average (computed from our dataset)" —
+   applied to every chip, tooltip, header note and section intro.
+   EAL uses the census wording: first language known or believed to
+   be other than English. If IDACI ships, caveat that it describes
+   pupils' home neighbourhoods, not the school.
+
+## 9. Rollout
+
+1. **PR 1 (backend):** extend `/api/compare` + tests.
+2. **PR 2 (frontend):** new compare layout behind the existing route;
+   e2e journey updated in the same PR (promotion gate).
+3. **Fix separately:** missing third series on the current chart.
+
+## 10. Open questions for review
+
+- Max schools: keep 10 in API but cap visible columns at 4 with scroll?
+- Should distance-from-home appear when the user searched by postcode
+  (data exists via `dim_location`)?
+- Keep finance out of v1? (Recommended: yes, out.)
@@ -0,0 +1,642 @@
+<title>Compare screen — proposed redesign</title>
+<style>
+  :root {
+    --bg: #faf7f2;
+    --bg-2: #f3ede4;
+    --card: #ffffff;
+    --ink: #1a1612;
+    --ink-2: #5c564d;
+    --ink-3: #6d685f;
+    --border: #e5dfd5;
+    --accent: #b04a2e;
+    --accent-bg: rgba(224, 114, 86, 0.12);
+    /* Validated series palette (passes lightness / chroma / CVD / contrast) */
+    --s1: #e07256; --s1-text: #b04a2e;
+    --s2: #00949b; --s2-text: #006a70;
+    --s3: #8664c9; --s3-text: #6a4bab;
+    --eng: #6d685f;
+    --good-bg: #e3efe6; --good-text: #1a6b34;
+    --warn-bg: #f6ecd4; --warn-text: #7a5d00;
+    --bad-bg: #f7e3de;  --bad-text: #a03a20;
+    --neutral-bg: #efeae1; --neutral-text: #5c564d;
+    --shadow: 0 2px 8px rgba(26, 22, 18, 0.06);
+    --display: 'Playfair Display', Georgia, 'Times New Roman', serif;
+    --body: 'DM Sans', -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
+  }
+  @media (prefers-color-scheme: dark) {
+    :root {
+      --bg: #16130f; --bg-2: #201c16; --card: #241f19;
+      --ink: #f2ede4; --ink-2: #bdb5a8; --ink-3: #9a927f;
+      --border: #3a342b; --accent: #f08b6e; --accent-bg: rgba(224,114,86,0.16);
+      --s1: #f08b6e; --s1-text: #f4a58e;
+      --s2: #2fb8ae; --s2-text: #5fd0c8;
+      --s3: #a98fe0; --s3-text: #c0abec;
+      --eng: #9a927f;
+      --good-bg: #1e3325; --good-text: #7fd39a;
+      --warn-bg: #38301a; --warn-text: #e4c268;
+      --bad-bg: #3d221b;  --bad-text: #f0977f;
+      --neutral-bg: #2b2620; --neutral-text: #bdb5a8;
+      --shadow: 0 2px 8px rgba(0,0,0,0.35);
+    }
+  }
+  :root[data-theme="dark"] {
+    --bg: #16130f; --bg-2: #201c16; --card: #241f19;
+    --ink: #f2ede4; --ink-2: #bdb5a8; --ink-3: #9a927f;
+    --border: #3a342b; --accent: #f08b6e; --accent-bg: rgba(224,114,86,0.16);
+    --s1: #f08b6e; --s1-text: #f4a58e;
+    --s2: #2fb8ae; --s2-text: #5fd0c8;
+    --s3: #a98fe0; --s3-text: #c0abec;
+    --eng: #9a927f;
+    --good-bg: #1e3325; --good-text: #7fd39a;
+    --warn-bg: #38301a; --warn-text: #e4c268;
+    --bad-bg: #3d221b;  --bad-text: #f0977f;
+    --neutral-bg: #2b2620; --neutral-text: #bdb5a8;
+    --shadow: 0 2px 8px rgba(0,0,0,0.35);
+  }
+  :root[data-theme="light"] {
+    --bg: #faf7f2; --bg-2: #f3ede4; --card: #ffffff;
+    --ink: #1a1612; --ink-2: #5c564d; --ink-3: #6d685f;
+    --border: #e5dfd5; --accent: #b04a2e; --accent-bg: rgba(224,114,86,0.12);
+    --s1: #e07256; --s1-text: #b04a2e;
+    --s2: #00949b; --s2-text: #006a70;
+    --s3: #8664c9; --s3-text: #6a4bab;
+    --eng: #6d685f;
+    --good-bg: #e3efe6; --good-text: #1a6b34;
+    --warn-bg: #f6ecd4; --warn-text: #7a5d00;
+    --bad-bg: #f7e3de;  --bad-text: #a03a20;
+    --neutral-bg: #efeae1; --neutral-text: #5c564d;
+    --shadow: 0 2px 8px rgba(26, 22, 18, 0.06);
+  }
+
+  body { background: var(--bg); color: var(--ink); font-family: var(--body); line-height: 1.5; }
+  .wrap { max-width: 1100px; margin: 0 auto; padding: 2rem 1.25rem 5rem; }
+
+  .mock-note {
+    background: var(--accent-bg); border: 1px solid var(--border); border-radius: 8px;
+    padding: 0.6rem 1rem; font-size: 0.85rem; color: var(--ink-2); margin-bottom: 2rem;
+  }
+  .mock-note strong { color: var(--accent); }
+
+  h1 { font-family: var(--display); font-size: 2.4rem; font-weight: 700; margin: 0 0 0.25rem; text-wrap: balance; }
+  .sub { color: var(--ink-2); margin: 0 0 2rem; max-width: 60ch; }
+
+  h2.section-title {
+    font-family: var(--display); font-size: 1.45rem; font-weight: 700;
+    margin: 0; padding-left: 0.75rem; border-left: 3px solid var(--accent);
+  }
+  .how { font-size: 0.85rem; color: var(--ink-3); margin: 0.35rem 0 0 0.95rem; max-width: 70ch; }
+  section.block { margin-top: 3rem; }
+
+  /* ---- Sticky school header ---- */
+  .school-bar {
+    position: sticky; top: 0; z-index: 10;
+    background: var(--bg); padding: 0.75rem 0; border-bottom: 1px solid var(--border);
+    display: grid; grid-template-columns: repeat(3, 1fr) auto; gap: 0.75rem; align-items: stretch;
+  }
+  .school-chip {
+    background: var(--card); border: 1px solid var(--border); border-radius: 8px;
+    box-shadow: var(--shadow); padding: 0.55rem 0.75rem; display: flex; gap: 0.55rem; align-items: center;
+    border-top: 3px solid var(--chip);
+  }
+  .school-chip .dot { width: 11px; height: 11px; border-radius: 50%; background: var(--chip); flex: none; }
+  .school-chip .nm { font-weight: 600; font-size: 0.92rem; line-height: 1.25; }
+  .school-chip .la { font-size: 0.78rem; color: var(--ink-3); }
+  .school-chip .x {
+    margin-left: auto; border: none; background: var(--bg-2); color: var(--ink-3);
+    border-radius: 50%; width: 22px; height: 22px; cursor: pointer; flex: none; font-size: 0.9rem;
+  }
+  .add-school {
+    border: 1.5px dashed var(--border); border-radius: 8px; background: none;
+    color: var(--accent); font-weight: 600; padding: 0 1rem; cursor: pointer; font-family: inherit; font-size: 0.9rem;
+  }
+
+  /* ---- Comparison grid rows ---- */
+  .grid { display: grid; grid-template-columns: 200px repeat(3, 1fr); gap: 0 0.75rem; margin-top: 1.25rem; }
+  .grid .rowlabel {
+    font-size: 0.85rem; font-weight: 600; color: var(--ink-2); padding: 0.85rem 0.5rem 0.85rem 0;
+    border-bottom: 1px solid var(--border); display: flex; align-items: center; gap: 0.35rem;
+  }
+  .grid .cell { padding: 0.85rem 0.25rem; border-bottom: 1px solid var(--border); font-size: 0.95rem; }
+  .grid .cell .big { font-size: 1.35rem; font-weight: 700; font-variant-numeric: tabular-nums; }
+  .grid .cell .small { display: block; font-size: 0.8rem; color: var(--ink-3); margin-top: 0.1rem; }
+
+  .help {
+    display: inline-flex; width: 15px; height: 15px; border-radius: 50%;
+    border: 1px solid var(--ink-3); color: var(--ink-3); font-size: 0.65rem;
+    align-items: center; justify-content: center; cursor: help; flex: none;
+  }
+
+  .chip {
+    display: inline-block; font-size: 0.75rem; font-weight: 600; border-radius: 999px;
+    padding: 0.15rem 0.6rem; white-space: nowrap;
+  }
+  .chip.good { background: var(--good-bg); color: var(--good-text); }
+  .chip.warn { background: var(--warn-bg); color: var(--warn-text); }
+  .chip.bad  { background: var(--bad-bg); color: var(--bad-text); }
+  .chip.neutral { background: var(--neutral-bg); color: var(--neutral-text); }
+
+  .ofsted-badge {
+    display: inline-block; font-weight: 700; border-radius: 6px; padding: 0.25rem 0.7rem; font-size: 0.9rem;
+  }
+  /* New-framework report card */
+  .rc-list { display: flex; flex-direction: column; gap: 0.3rem; margin-top: 0.2rem; }
+  .rc-row { display: flex; justify-content: space-between; align-items: center; gap: 0.5rem; font-size: 0.8rem; }
+  .rc-row .a { color: var(--ink-2); }
+  .illus {
+    display: inline-block; font-size: 0.7rem; font-weight: 600; letter-spacing: 0.03em;
+    color: var(--accent); border: 1px dashed var(--accent); border-radius: 4px; padding: 0.05rem 0.4rem;
+  }
+  .ofsted-1 { background: var(--good-bg); color: var(--good-text); }
+  .ofsted-2 { background: #e7f0e3; color: #3c6b2f; }
+  :root[data-theme="dark"] .ofsted-2 { background:#25321f; color:#a5cf94; }
+  @media (prefers-color-scheme: dark) { .ofsted-2 { background:#25321f; color:#a5cf94; } }
+
+  /* ---- Dot strips (signature element) ---- */
+  .strip-row { margin: 1.1rem 0 1.6rem; }
+  .strip-head { display: flex; justify-content: space-between; align-items: baseline; gap: 1rem; flex-wrap: wrap; }
+  .strip-head .t { font-weight: 600; font-size: 0.95rem; }
+  .strip-head .eng-note { font-size: 0.8rem; color: var(--ink-3); }
+  .strip { position: relative; height: 34px; margin-top: 0.45rem; }
+  .strip .track { position: absolute; left: 0; right: 0; top: 15px; height: 4px; border-radius: 2px; background: var(--bg-2); }
+  .strip .eng-tick { position: absolute; top: 4px; width: 2px; height: 26px; background: var(--eng); }
+  .strip .eng-lbl { position: absolute; top: -14px; transform: translateX(-50%); font-size: 0.7rem; color: var(--ink-3); white-space: nowrap; }
+  .strip .pt {
+    position: absolute; top: 9px; width: 16px; height: 16px; border-radius: 50%;
+    transform: translateX(-50%); border: 2px solid var(--card); box-shadow: 0 0 0 1px rgba(0,0,0,0.08);
+  }
+  .strip .pt-lbl { position: absolute; top: 27px; transform: translateX(-50%); font-size: 0.72rem; font-weight: 600; font-variant-numeric: tabular-nums; }
+
+  details.more-measures { margin-top: 0.5rem; border-top: 1px solid var(--border); padding-top: 0.75rem; }
+  details.more-measures summary { cursor: pointer; font-weight: 600; font-size: 0.88rem; color: var(--accent); }
+  .strip-note { font-size: 0.78rem; color: var(--ink-3); margin: 0.5rem 0 0; }
+  .metric-picker { display: flex; align-items: center; gap: 0.6rem; margin-bottom: 1rem; flex-wrap: wrap; }
+  .metric-picker label { font-size: 0.85rem; font-weight: 600; color: var(--ink-2); }
+  .metric-picker select {
+    font-family: inherit; font-size: 0.9rem; padding: 0.4rem 0.6rem; border-radius: 8px;
+    border: 1px solid var(--border); background: var(--card); color: var(--ink); max-width: 100%;
+  }
+  .picker-note { font-size: 0.78rem; color: var(--ink-3); }
+  .legend { display: flex; gap: 1.1rem; flex-wrap: wrap; font-size: 0.82rem; color: var(--ink-2); margin: 0.75rem 0 0; }
+  .legend .li { display: inline-flex; align-items: center; gap: 0.4rem; }
+  .legend .sw { width: 10px; height: 10px; border-radius: 50%; }
+  .legend .engsw { width: 2px; height: 12px; background: var(--eng); }
+
+  .card {
+    background: var(--card); border: 1px solid var(--border); border-radius: 16px;
+    box-shadow: var(--shadow); padding: 1.25rem 1.5rem; margin-top: 1rem;
+  }
+
+  /* ---- Sparklines & chart ---- */
+  .spark { display: block; }
+  .chart-wrap { overflow-x: auto; }
+  .covid { fill: var(--bg-2); }
+  .covid-lbl { font-size: 0.7rem; fill: var(--ink-3); }
+
+  .barmini { height: 8px; border-radius: 4px; background: var(--bg-2); overflow: hidden; margin-top: 0.3rem; max-width: 140px; }
+  .barmini > i { display: block; height: 100%; border-radius: 4px; }
+
+  details.explore { margin-top: 1rem; }
+  details.explore summary {
+    cursor: pointer; font-weight: 600; color: var(--accent);
+    padding: 0.85rem 1.1rem; background: var(--card); border: 1px solid var(--border); border-radius: 8px;
+  }
+  details.explore[open] summary { border-radius: 8px 8px 0 0; }
+  details.explore .inner { border: 1px solid var(--border); border-top: none; border-radius: 0 0 8px 8px; background: var(--card); padding: 1.25rem 1.5rem; }
+
+  .footnote { font-size: 0.78rem; color: var(--ink-3); margin-top: 2.5rem; border-top: 1px solid var(--border); padding-top: 1rem; max-width: 75ch; }
+
+  @media (max-width: 760px) {
+    .school-bar { grid-template-columns: 1fr; }
+    .grid { grid-template-columns: 1fr; }
+    .grid .rowlabel { border-bottom: none; padding-bottom: 0.15rem; background: var(--bg-2); border-radius: 6px; padding: 0.4rem 0.6rem; margin-top: 0.8rem; }
+    .grid .cell { border-bottom: none; padding: 0.4rem 0.6rem; }
+    .grid .cell::before { content: attr(data-school); display: block; font-size: 0.72rem; font-weight: 600; color: var(--sc, var(--ink-3)); }
+  }
+</style>
+
+<div class="wrap">
+  <p class="mock-note"><strong>Mockup — proposed redesign of /compare.</strong> All figures are live production data for three real schools (2024/25 results, 2026/27 admissions round). England averages for test results are official DfE figures; other benchmarks are state-school averages computed from our dataset.</p>
+
+  <h1>Compare schools</h1>
+  <p class="sub">Three schools side by side — inspection results, academics, admissions and community, each anchored against the England average so you can tell at a glance what's typical and what stands out.</p>
+
+  <div class="school-bar" aria-label="Schools in this comparison">
+    <div class="school-chip" style="--chip: var(--s1)">
+      <span class="dot"></span>
+      <span><span class="nm">Barclay Primary School</span><br><span class="la">Waltham Forest · Academy</span></span>
+      <button class="x" aria-label="Remove Barclay Primary School">×</button>
+    </div>
+    <div class="school-chip" style="--chip: var(--s2)">
+      <span class="dot"></span>
+      <span><span class="nm">Elmhurst Primary School</span><br><span class="la">Newham · Academy</span></span>
+      <button class="x" aria-label="Remove Elmhurst Primary School">×</button>
+    </div>
+    <div class="school-chip" style="--chip: var(--s3)">
+      <span class="dot"></span>
+      <span><span class="nm">Plumcroft Primary School</span><br><span class="la">Greenwich · Community school</span></span>
+      <button class="x" aria-label="Remove Plumcroft Primary School">×</button>
+    </div>
+    <button class="add-school">+ Add school</button>
+  </div>
+
+  <!-- ============ AT A GLANCE ============ -->
+  <section class="block" style="margin-top:2rem">
+    <h2 class="section-title">At a glance</h2>
+    <p class="how">The short version — each row below is explained in its own section further down.</p>
+    <div class="grid">
+      <div class="rowlabel">Latest Ofsted inspection</div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)"><span class="ofsted-badge ofsted-1">Outstanding</span><span class="small">Inspected Oct 2021</span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)"><span class="ofsted-badge ofsted-1">Outstanding</span><span class="small">Inspected Oct 2021</span></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">
+        <strong style="font-size:0.9rem">Report card</strong> <span class="illus">illustrative</span>
+        <div style="display:flex;gap:0.3rem;flex-wrap:wrap;margin-top:0.3rem">
+          <span class="chip good">4 areas Strong standard</span>
+          <span class="chip neutral">2 areas Expected standard</span>
+          <span class="chip warn">Attendance &amp; behaviour: Attention needed</span>
+        </div>
+        <span class="small">Safeguarding met · Nov 2025</span>
+      </div>
+
+      <div class="rowlabel">Children reaching the expected standard <span class="help" title="% of Year 6 pupils reaching the expected standard in reading, writing and maths (2024/25). England average: 62%.">?</span></div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)"><span class="big" style="color:var(--s1-text)">87%</span> <span class="chip good">Above England average</span><span class="small">England average 62%</span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)"><span class="big" style="color:var(--s2-text)">92%</span> <span class="chip good">Above England average</span><span class="small">England average 62%</span></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)"><span class="big" style="color:var(--s3-text)">79%</span> <span class="chip good">Above England average</span><span class="small">England average 62%</span></div>
+
+      <div class="rowlabel">Getting a place</div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)"><span class="chip good">97% of first choices offered</span><span class="small">Named on 457 forms · 180 places</span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)"><span class="chip warn">73% of first choices offered</span><span class="small">Named on 342 forms · 120 places</span></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)"><span class="chip good">All first choices offered</span><span class="small">Named on 185 forms · 80 places</span></div>
+
+      <div class="rowlabel">Size</div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)">1,273 pupils<span class="small">Much larger than average</span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)">980 pupils<span class="small">Much larger than average</span></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">1,056 pupils<span class="small">Much larger than average</span></div>
+    </div>
+  </section>
+
+  <!-- ============ OFSTED ============ -->
+  <section class="block">
+    <h2 class="section-title">Ofsted inspection</h2>
+    <p class="how">Ofsted is the schools inspectorate. It stopped giving a single overall grade in <strong>September 2024</strong>; inspections between then and November 2025 kept the area-by-area judgements without an overall grade, and from <strong>November 2025</strong> new inspections produce a <strong>report card</strong> rating each area of school life on a five-point scale (Exceptional · Strong standard · Expected standard · Attention needed · Urgent improvement). A report card and an older overall grade aren't directly comparable — Plumcroft's report card below is an <em>illustrative example</em> of the new format, as no school in our dataset has one yet. (Ofsted's "Expected standard" rating is unrelated to the KS2 "expected standard" test measure further down this page.)</p>
+    <div class="grid">
+      <div class="rowlabel">Result</div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)"><span class="ofsted-badge ofsted-1">Outstanding</span><span class="small">Overall grade (older-style inspection)</span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)"><span class="ofsted-badge ofsted-1">Outstanding</span><span class="small">Overall grade (older-style inspection)</span></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)"><strong>Report card</strong> <span class="illus">illustrative</span><span class="small">New-style inspection — no overall grade is given</span></div>
+
+      <div class="rowlabel">Inspected</div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)">7 Oct 2021 <span class="chip neutral">4+ years ago</span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)">6 Oct 2021 <span class="chip neutral">4+ years ago</span></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">14 Nov 2025</div>
+
+      <div class="rowlabel">Judgement detail <span class="help" title="Older-style inspections: one rating per judgement area, where published. New-style inspections: the full report card, one rating per area of school life.">?</span></div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)"><span class="small">We don't hold area-by-area detail for this inspection — see Barclay's Ofsted page for the full report.</span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)">
+        <div class="rc-list">
+          <div class="rc-row"><span class="a">Quality of education</span><span class="chip good">Outstanding</span></div>
+          <div class="rc-row"><span class="a">Behaviour &amp; attitudes</span><span class="chip good">Outstanding</span></div>
+          <div class="rc-row"><span class="a">Personal development</span><span class="chip good">Outstanding</span></div>
+          <div class="rc-row"><span class="a">Leadership &amp; management</span><span class="chip good">Outstanding</span></div>
+        </div>
+      </div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">
+        <div class="rc-list">
+          <div class="rc-row"><span class="a">Achievement</span><span class="chip good">Strong standard</span></div>
+          <div class="rc-row"><span class="a">Curriculum &amp; teaching</span><span class="chip good">Strong standard</span></div>
+          <div class="rc-row"><span class="a">Attendance &amp; behaviour</span><span class="chip warn">Attention needed</span></div>
+          <div class="rc-row"><span class="a">Personal development</span><span class="chip good">Strong standard</span></div>
+          <div class="rc-row"><span class="a">Inclusion</span><span class="chip neutral">Expected standard</span></div>
+          <div class="rc-row"><span class="a">Leadership &amp; governance</span><span class="chip good">Strong standard</span></div>
+          <div class="rc-row"><span class="a">Early years</span><span class="chip neutral">Expected standard</span></div>
+          <div class="rc-row"><span class="a">Safeguarding</span><span class="chip good">Met</span></div>
+        </div>
+      </div>
+
+      <div class="rowlabel">Ofsted page <span class="help" title="Links to the school's page on ofsted.gov.uk, where all its inspection reports are listed.">?</span></div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)"><a href="https://reports.ofsted.gov.uk/provider/21/138690" style="color:var(--accent)">Barclay's Ofsted page →</a></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)"><a href="https://reports.ofsted.gov.uk/provider/21/145362" style="color:var(--accent)">Elmhurst's Ofsted page →</a></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)"><a href="https://reports.ofsted.gov.uk/provider/21/100140" style="color:var(--accent)">Plumcroft's Ofsted page →</a></div>
+    </div>
+  </section>
+
+  <!-- ============ ACADEMICS ============ -->
+  <section class="block">
+    <h2 class="section-title">How children do academically</h2>
+    <p class="how">Results from national tests and teacher assessments at the end of Year 6 (2024/25) — writing is assessed by teachers, not tested. Each line runs from 0–100%; the grey tick marks the England average, so dots to its right are above average.</p>
+    <div class="card">
+      <div id="strips"></div>
+      <details class="more-measures">
+        <summary>More measures — grammar, punctuation &amp; spelling, science, average scaled scores</summary>
+        <div id="strips-more"></div>
+        <p class="strip-note">The strips show the 100–120 window of the full 80–120 scaled-score range; 100 is the expected standard, and the strip widens if a school averages below it. England ticks for grammar, punctuation &amp; spelling and science aren't in our dataset yet, and the scaled-score England ticks are indicative — official DfE figures for all of these will be loaded before launch.</p>
+      </details>
+      <div class="legend" id="strip-legend"></div>
+    </div>
+
+    <div class="grid">
+      <div class="rowlabel">Trend, 2015/16 to 2024/25 <span class="help" title="% reaching the expected standard in reading, writing and maths each year. Tests were cancelled in 2019/20 and 2020/21 (COVID); 2021/22 school figures aren't in our dataset yet — the line breaks over those years.">?</span></div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)"><svg class="spark" data-series="52,76,65,87,87,75,87" data-color="s1" width="150" height="40" role="img" aria-label="Barclay trend: variable, most recently 87%"></svg><span class="small">Variable, recently 87%</span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)"><svg class="spark" data-series="80,81,86,88,88,88,92" data-color="s2" width="150" height="40" role="img" aria-label="Elmhurst trend: 80% rising to 92%"></svg><span class="small">Consistently high</span></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)"><svg class="spark" data-series="58,64,57,69,62,72,79" data-color="s3" width="150" height="40" role="img" aria-label="Plumcroft trend: 58% rising to 79%"></svg><span class="small">Improving since 2022/23</span></div>
+
+      <div class="rowlabel">Children from lower-income families <span class="help" title="% of disadvantaged pupils (eligible for free school meals in the last 6 years, or looked after by the local authority) reaching the expected standard. State-school average: 46% (computed from our dataset). Based on smaller pupil groups, so a single pupil can move a school's figure noticeably.">?</span></div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)"><span class="big" style="font-size:1.1rem">86%</span> <span class="chip good">Well above the 46% state-school average</span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)"><span class="big" style="font-size:1.1rem">93%</span> <span class="chip good">Well above the 46% state-school average</span></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)"><span class="big" style="font-size:1.1rem">72%</span> <span class="chip good">Above the 46% state-school average</span></div>
+    </div>
+  </section>
+
+  <!-- ============ ADMISSIONS ============ -->
+  <section class="block">
+    <h2 class="section-title">Getting a place</h2>
+    <p class="how">From the most recent admissions round (September 2026 entry). "First choice" means families who ranked the school top of their application form — officially a "first preference". Schools never see your ranking: places are decided only by the school's admission criteria, so listing a school lower down never hurts your chances. These are National Offer Day offers — waiting lists and appeals can change the final intake.</p>
+    <div class="grid">
+      <div class="rowlabel">Interest in the school <span class="help" title="How many application forms named the school at any preference rank — not the number of families competing head-to-head for a place.">?</span></div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)">Named on <span class="big" style="font-size:1.1rem">457</span> forms · <strong>180</strong> places</div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)">Named on <span class="big" style="font-size:1.1rem">342</span> forms · <strong>120</strong> places</div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">Named on <span class="big" style="font-size:1.1rem">185</span> forms · <strong>80</strong> places</div>
+
+      <div class="rowlabel">First-choice families offered a place</div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)"><strong>97%</strong><span class="barmini"><i style="width:97%;background:var(--s1)"></i></span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)"><strong>73%</strong> <span class="chip warn">Over 1 in 4 first choices missed out</span><span class="barmini"><i style="width:73%;background:var(--s2)"></i></span></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)"><strong>100%</strong><span class="barmini"><i style="width:100%;background:var(--s3)"></i></span></div>
+
+      <div class="rowlabel">What this means</div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)"><span class="small">Nearly every family who put Barclay first got a place.</span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)"><span class="small">More first-choice applications than places — check the school's admission criteria (for most non-faith primaries, distance decides).</span></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)"><span class="small">Every family who put Plumcroft first got a place.</span></div>
+    </div>
+  </section>
+
+  <!-- ============ COMMUNITY ============ -->
+  <section class="block">
+    <h2 class="section-title">Who goes there</h2>
+    <p class="how">The school's community, from the latest school census (2025/26). England averages are shown for context — there's no "right" number here.</p>
+    <div class="grid">
+      <div class="rowlabel">Pupils on roll</div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)">1,273 <span class="small">1,260 places — at or above capacity</span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)">980 <span class="small">of 996 places (98% full)</span></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">1,056 <span class="small">1,050 places — at or above capacity</span></div>
+
+      <div class="rowlabel">Girls / boys</div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)">51% / 49%</div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)">48% / 52%</div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">51% / 49%</div>
+
+      <div class="rowlabel">Free school meals <span class="help" title="% of pupils eligible for free school meals — a common measure of how many pupils come from lower-income families. State-school average: 25% (computed from our dataset).">?</span></div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)">26% <span class="chip neutral">About the state-school average</span></div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)">25% <span class="chip neutral">About the state-school average</span></div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">30% <span class="chip neutral">A little above average</span></div>
+
+      <div class="rowlabel">English as an additional language <span class="help" title="% of pupils whose first language is known or believed to be other than English. State-school average: 22% (computed from our dataset).">?</span></div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)">62%</div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)">84%</div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">20%</div>
+
+      <div class="rowlabel">Extra learning support (SEN) <span class="help" title="% of pupils receiving SEN support (not including EHC plans). State-school average: 14% (computed from our dataset). A high figure can mean the school hosts specialist provision — often a strength, not a warning sign.">?</span></div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)">6%</div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)">8%</div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">28% <span class="chip neutral">Well above average</span></div>
+
+      <div class="rowlabel">Faith character</div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)">None</div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)">None</div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">None</div>
+
+      <div class="rowlabel">Ages · nursery</div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)">3–11 · has a nursery</div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)">3–11 · has a nursery</div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">3–11 · has a nursery</div>
+
+      <div class="rowlabel">Run by</div>
+      <div class="cell" data-school="Barclay" style="--sc:var(--s1-text)">Lion Academy Trust</div>
+      <div class="cell" data-school="Elmhurst" style="--sc:var(--s2-text)">New Vision Trust</div>
+      <div class="cell" data-school="Plumcroft" style="--sc:var(--s3-text)">Greenwich council</div>
+    </div>
+  </section>
+
+  <!-- ============ EXPLORE TRENDS ============ -->
+  <section class="block">
+    <h2 class="section-title">Explore trends</h2>
+    <p class="how">The full year-by-year explorer — every measure from the current compare page lives on here, grouped, each with its England-average line. Three measures are wired up in this mockup; the rest are shown to convey the catalogue.</p>
+    <details class="explore" open>
+      <summary>Year-by-year trends, 2015/16 to 2024/25</summary>
+      <div class="inner chart-wrap">
+        <div class="metric-picker">
+          <label for="metric-select">Measure:</label>
+          <select id="metric-select">
+            <optgroup label="Expected standard">
+              <option value="rwm" selected>Reading, writing &amp; maths (combined)</option>
+              <option value="reading">Reading</option>
+              <option value="maths">Maths</option>
+              <option disabled>Writing (teacher assessment)</option>
+              <option disabled>Grammar, punctuation &amp; spelling</option>
+              <option disabled>Science</option>
+            </optgroup>
+            <optgroup label="Higher standard">
+              <option disabled>Reading, writing &amp; maths (combined)</option>
+              <option disabled>Reading · Maths · GPS</option>
+              <option disabled>Writing — greater depth (teacher assessment)</option>
+            </optgroup>
+            <optgroup label="Average scaled scores">
+              <option disabled>Reading · Maths · GPS</option>
+            </optgroup>
+            <optgroup label="Equity">
+              <option disabled>Disadvantaged pupils — expected standard</option>
+            </optgroup>
+            <optgroup label="School context">
+              <option disabled>Free school meals % · EAL % · SEN support %</option>
+            </optgroup>
+          </select>
+          <span class="picker-note">School lines break where a year isn't in our dataset.</span>
+        </div>
+        <svg id="trendchart" width="880" height="300" role="img" aria-label="Line chart: selected measure by year for three schools and England average"></svg>
+        <div class="legend" id="trend-legend"></div>
+      </div>
+    </details>
+  </section>
+
+  <p class="footnote">
+    Sources: DfE Compare School Performance (KS2 results), Ofsted inspection outcomes, DfE school admissions data, school census — all from datasets SchoolCompare already collects. England averages for test results are the official DfE national figures; benchmarks for free school meals, language, SEN, school size and disadvantaged pupils' results are computed across all state schools in our dataset. Following DfE practice, figures based on 5 or fewer pupils are suppressed and shown as "no data". This is a static mockup: tooltips and "Add school" are illustrative, and Plumcroft's Ofsted report card is a made-up example of the November 2025 format (its real latest inspection is Good, June 2023) — no school in our dataset has a report card yet.
+  </p>
+</div>
+
+<script>
+(function () {
+  const css = (v) => getComputedStyle(document.documentElement).getPropertyValue(v).trim();
+
+  const schools = [
+    { name: 'Barclay',   color: () => css('--s1'), text: () => css('--s1-text') },
+    { name: 'Elmhurst',  color: () => css('--s2'), text: () => css('--s2-text') },
+    { name: 'Plumcroft', color: () => css('--s3'), text: () => css('--s3-text') },
+  ];
+
+  /* ---- Dot strips ---- */
+  const strips = [
+    { label: 'Reading, writing & maths — expected standard', eng: 62, vals: [87, 92, 79] },
+    { label: 'Reading', eng: 75, vals: [91, 92, 87] },
+    { label: 'Writing', eng: 72, vals: [94, 92, 83] },
+    { label: 'Maths', eng: 74, vals: [91, 95, 84] },
+    { label: 'Working at a higher standard than expected', eng: 8, vals: [22, 27, 12], tip: 'A high score in the reading and maths tests plus \u201cgreater depth\u201d in teacher-assessed writing.' },
+  ];
+
+  // Generalised strip renderer: any domain (percentages or scaled scores),
+  // England tick optional (omitted when the benchmark isn't in our dataset).
+  function renderStrips(list, el, firstNote) {
+    list.forEach((s, si) => {
+      const min = s.min ?? 0, max = s.max ?? 100, unit = s.unit ?? '%';
+      const pos = v => (v - min) / (max - min) * 100;
+      const row = document.createElement('div');
+      row.className = 'strip-row';
+      let pts = '';
+      const sorted = s.vals.map((v, i) => ({ v, i })).sort((a, b) => a.v - b.v);
+      let lastBelow = -Infinity;
+      const nudge = (max - min) * 0.04;
+      sorted.forEach(({ v, i }) => {
+        const above = (v - lastBelow) < nudge;
+        if (!above) lastBelow = v;
+        pts += `<span class="pt" style="left:${pos(v)}%;background:${schools[i].color()}" title="${schools[i].name}: ${v}${unit}"></span>`
+             + `<span class="pt-lbl" style="left:${pos(v)}%;color:${schools[i].text()};${above ? 'top:-6px' : ''}">${v}</span>`;
+      });
+      const eng = s.eng != null
+        ? `<span class="eng-tick" style="left:${pos(s.eng)}%"></span><span class="eng-lbl" style="left:${pos(s.eng)}%">England ${s.eng}${unit}</span>`
+        : '';
+      row.innerHTML = `
+        <div class="strip-head"><span class="t"${s.tip ? ` title="${s.tip}"` : ''}>${s.label}</span>
+          ${si === 0 && firstNote ? `<span class="eng-note">${firstNote}</span>` : ''}</div>
+        <div class="strip" role="img" aria-label="${s.label}: ${s.eng != null ? 'England average ' + s.eng + unit + ', ' : ''}${s.vals.map((v, i) => schools[i].name + ' ' + v + unit).join(', ')}">
+          <div class="track"></div>
+          ${eng}
+          ${pts}
+        </div>`;
+      el.appendChild(row);
+    });
+  }
+  renderStrips(strips, document.getElementById('strips'), '│ grey tick = England average');
+  renderStrips([
+    { label: 'Grammar, punctuation & spelling — expected standard', eng: null, vals: [86, 94, 82] },
+    { label: 'Science — expected standard (teacher-assessed)', eng: null, vals: [95, 91, 83], tip: 'Teacher-assessed, like writing — there has been no KS2 science test since 2009, so comparisons are indicative.' },
+    { label: 'Average scaled score — reading', eng: 106, vals: [107, 110, 109], min: 100, max: 120, unit: '' },
+    { label: 'Average scaled score — maths', eng: 105, vals: [108, 113, 108], min: 100, max: 120, unit: '' },
+    { label: 'Average scaled score — grammar, punctuation & spelling', eng: 105, vals: [107, 114, 109], min: 100, max: 120, unit: '' },
+  ], document.getElementById('strips-more'), null);
+  document.getElementById('strip-legend').innerHTML =
+    schools.map(s => `<span class="li"><span class="sw" style="background:${s.color()}"></span>${s.name}</span>`).join('')
+    + '<span class="li"><span class="engsw"></span>England average</span>';
+
+  /* ---- Sparklines (x honours real time: values are 15/16–18/19 then 22/23–24/25) ---- */
+  document.querySelectorAll('svg.spark').forEach(svg => {
+    const vals = svg.dataset.series.split(',').map(Number);
+    const color = css('--' + svg.dataset.color);
+    const w = +svg.getAttribute('width'), h = +svg.getAttribute('height');
+    const min = 40, max = 100;
+    const sslots = [0,1,2,3,7,8,9];
+    const x = i => 4 + sslots[i] * (w - 8) / 9;
+    const y = v => h - 6 - (v - min) * (h - 12) / (max - min);
+    const seg = idx => idx.map((i, k) => (k ? 'L' : 'M') + x(i).toFixed(1) + ' ' + y(vals[i]).toFixed(1)).join(' ');
+    svg.innerHTML = `<path d="${seg([0,1,2,3])}" fill="none" stroke="${color}" stroke-width="2" stroke-linecap="round"/>`
+      + `<path d="${seg([4,5,6])}" fill="none" stroke="${color}" stroke-width="2" stroke-linecap="round"/>`
+      + `<circle cx="${x(6)}" cy="${y(vals[6])}" r="3.5" fill="${color}"/>`;
+  });
+
+  /* ---- Trend chart (metric-driven) ----
+     Tests were cancelled 2019/20-2020/21; lines always break across that band.
+     Nulls elsewhere are dataset gaps (no school-level 2021/22 rows; no
+     subject-level 2022/23 rows) and break the lines honestly. England figures
+     are official DfE (fact_ks2_national_averages); 2015/16 not loaded yet. */
+  const years = ['2015/16','2016/17','2017/18','2018/19','2021/22','2022/23','2023/24','2024/25'];
+  const METRICS = {
+    rwm: {
+      label: 'Reading, writing & maths - expected standard',
+      school: { Barclay: [52,76,65,87,null,87,75,87], Elmhurst: [80,81,86,88,null,88,88,92], Plumcroft: [58,64,57,69,null,62,72,79] },
+      england: [null,61.1,64.3,64.9,58.7,59.5,60.6,62.1],
+    },
+    reading: {
+      label: 'Reading - expected standard',
+      school: { Barclay: [57,84,76,87,null,null,79,91], Elmhurst: [88,91,92,91,null,null,92,92], Plumcroft: [59,68,72,79,null,null,82,87] },
+      england: [null,71.6,75.3,73.2,74.6,72.8,74.4,75.0],
+    },
+    maths: {
+      label: 'Maths - expected standard',
+      school: { Barclay: [81,82,74,90,null,null,88,91], Elmhurst: [96,89,97,97,null,null,96,95], Plumcroft: [80,80,69,90,null,null,84,84] },
+      england: [null,74.8,75.5,78.7,71.5,73.0,73.2,74.0],
+    },
+  };
+  const schoolColor = { Barclay: () => css('--s1'), Elmhurst: () => css('--s2'), Plumcroft: () => css('--s3') };
+
+  const svg = document.getElementById('trendchart');
+  const W = 880, H = 300, L = 44, R = 48, T = 18, B = 40;
+  // x positions honour real time: 2019/20 and 2020/21 (cancelled tests) sit between slots 3 and 6
+  const slots = [0,1,2,3,6,7,8,9]; const maxSlot = 9;
+  const X = i => L + slots[i] * (W - L - R) / maxSlot;
+  const Y = v => T + (100 - v) * (H - T - B) / 60; // domain 40..100
+
+  // Contiguous non-null runs, additionally split across the covid band (between indices 3 and 4)
+  function runs(vals) {
+    const out = []; let cur = [];
+    vals.forEach((v, i) => {
+      if (v == null) { if (cur.length) out.push(cur); cur = []; return; }
+      if (i === 4 && cur.length && cur[cur.length - 1] === 3) { out.push(cur); cur = []; }
+      cur.push(i);
+    });
+    if (cur.length) out.push(cur);
+    return out;
+  }
+
+  function renderChart(key) {
+    const m = METRICS[key];
+    const ink3 = css('--ink-3'), border = css('--border');
+    let g = '';
+    const bx1 = X(3) + 14, bx2 = X(4) - 14;
+    g += `<rect class="covid" x="${bx1}" y="${T}" width="${bx2 - bx1}" height="${H - T - B}" rx="4"/>`;
+    g += `<text class="covid-lbl" x="${(bx1 + bx2) / 2}" y="${T + 16}" text-anchor="middle">tests cancelled</text>`;
+    g += `<text class="covid-lbl" x="${(bx1 + bx2) / 2}" y="${T + 30}" text-anchor="middle">2019/20-2020/21</text>`;
+    for (let v = 40; v <= 100; v += 20) {
+      g += `<line x1="${L}" y1="${Y(v)}" x2="${W - R}" y2="${Y(v)}" stroke="${border}" stroke-width="1"/>`;
+      g += `<text x="${L - 8}" y="${Y(v) + 4}" text-anchor="end" font-size="11" fill="${ink3}">${v}%</text>`;
+    }
+    years.forEach((yr, i) => {
+      g += `<text x="${X(i)}" y="${H - B + 20}" text-anchor="middle" font-size="11" fill="${ink3}">${yr}</text>`;
+    });
+    const path = (vals, idx) => idx.map((i, k) => (k ? 'L' : 'M') + X(i) + ' ' + Y(vals[i])).join(' ');
+    runs(m.england).forEach(idx => {
+      if (idx.length > 1) g += `<path d="${path(m.england, idx)}" fill="none" stroke="${ink3}" stroke-width="1.5" stroke-dasharray="5 4"/>`;
+      else g += `<circle cx="${X(idx[0])}" cy="${Y(m.england[idx[0]])}" r="2.5" fill="${ink3}"><title>England ${years[idx[0]]}: ${Math.round(m.england[idx[0]])}%</title></circle>`;
+    });
+    Object.entries(m.school).forEach(([name, vals]) => {
+      const color = schoolColor[name]();
+      runs(vals).forEach(idx => {
+        if (idx.length > 1) g += `<path d="${path(vals, idx)}" fill="none" stroke="${color}" stroke-width="2" stroke-linecap="round"/>`;
+      });
+      vals.forEach((v, i) => {
+        if (v == null) return;
+        g += `<circle cx="${X(i)}" cy="${Y(v)}" r="3.5" fill="${color}" stroke="${css('--card')}" stroke-width="1.5"><title>${name} ${years[i]}: ${v}%</title></circle>`;
+      });
+    });
+    // End labels, pushed apart when schools finish close together
+    const ends = Object.entries(m.school)
+      .map(([name, vals]) => ({ v: vals[vals.length - 1], i: vals.length - 1 }))
+      .filter(e => e.v != null)
+      .sort((a, b) => a.v - b.v);
+    let prevY = Infinity;
+    ends.forEach(e => {
+      let y = Y(e.v) + 4;
+      if (prevY - y < 13) y = prevY - 13;
+      prevY = y;
+      g += `<text x="${X(e.i) + 8}" y="${y}" font-size="11" font-weight="600" fill="${ink3}">${e.v}%</text>`;
+    });
+    svg.innerHTML = g;
+    svg.setAttribute('aria-label', `Line chart: ${m.label} by year for three schools and England average`);
+    document.getElementById('trend-legend').innerHTML =
+      Object.keys(m.school).map(name => `<span class="li"><span class="sw" style="background:${schoolColor[name]()}"></span>${name}</span>`).join('')
+      + `<span class="li"><span class="sw" style="background:none;border-top:2px dashed ${ink3};border-radius:0;height:0"></span>England average</span>`;
+  }
+  renderChart('rwm');
+  document.getElementById('metric-select').addEventListener('change', e => renderChart(e.target.value));
+
+  // Re-render on theme change so series colors pick up dark-mode tokens
+  const rerender = () => location.reload();
+  new MutationObserver(muts => { if (muts.some(m => m.attributeName === 'data-theme')) rerender(); })
+    .observe(document.documentElement, { attributes: true });
+})();
+</script>
@@ -0,0 +1,437 @@
+<title>Compare screen — mobile mockup</title>
+<style>
+  :root {
+    --bg: #faf7f2; --bg-2: #f3ede4; --card: #ffffff;
+    --ink: #1a1612; --ink-2: #5c564d; --ink-3: #6d685f;
+    --border: #e5dfd5; --accent: #b04a2e; --accent-bg: rgba(224,114,86,0.12);
+    --s1: #e07256; --s1-text: #b04a2e;
+    --s2: #00949b; --s2-text: #006a70;
+    --s3: #8664c9; --s3-text: #6a4bab;
+    --eng: #6d685f;
+    --good-bg: #e3efe6; --good-text: #1a6b34;
+    --warn-bg: #f6ecd4; --warn-text: #7a5d00;
+    --neutral-bg: #efeae1; --neutral-text: #5c564d;
+    --shadow: 0 2px 8px rgba(26,22,18,0.06);
+    --display: 'Playfair Display', Georgia, 'Times New Roman', serif;
+    --body: 'DM Sans', -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
+  }
+  @media (prefers-color-scheme: dark) {
+    :root {
+      --bg: #16130f; --bg-2: #201c16; --card: #241f19;
+      --ink: #f2ede4; --ink-2: #bdb5a8; --ink-3: #9a927f;
+      --border: #3a342b; --accent: #f08b6e; --accent-bg: rgba(224,114,86,0.16);
+      --s1: #f08b6e; --s1-text: #f4a58e;
+      --s2: #2fb8ae; --s2-text: #5fd0c8;
+      --s3: #a98fe0; --s3-text: #c0abec;
+      --eng: #9a927f;
+      --good-bg: #1e3325; --good-text: #7fd39a;
+      --warn-bg: #38301a; --warn-text: #e4c268;
+      --neutral-bg: #2b2620; --neutral-text: #bdb5a8;
+      --shadow: 0 2px 8px rgba(0,0,0,0.35);
+    }
+  }
+  :root[data-theme="dark"] {
+    --bg: #16130f; --bg-2: #201c16; --card: #241f19;
+    --ink: #f2ede4; --ink-2: #bdb5a8; --ink-3: #9a927f;
+    --border: #3a342b; --accent: #f08b6e; --accent-bg: rgba(224,114,86,0.16);
+    --s1: #f08b6e; --s1-text: #f4a58e;
+    --s2: #2fb8ae; --s2-text: #5fd0c8;
+    --s3: #a98fe0; --s3-text: #c0abec;
+    --eng: #9a927f;
+    --good-bg: #1e3325; --good-text: #7fd39a;
+    --warn-bg: #38301a; --warn-text: #e4c268;
+    --neutral-bg: #2b2620; --neutral-text: #bdb5a8;
+    --shadow: 0 2px 8px rgba(0,0,0,0.35);
+  }
+  :root[data-theme="light"] {
+    --bg: #faf7f2; --bg-2: #f3ede4; --card: #ffffff;
+    --ink: #1a1612; --ink-2: #5c564d; --ink-3: #6d685f;
+    --border: #e5dfd5; --accent: #b04a2e; --accent-bg: rgba(224,114,86,0.12);
+    --s1: #e07256; --s1-text: #b04a2e;
+    --s2: #00949b; --s2-text: #006a70;
+    --s3: #8664c9; --s3-text: #6a4bab;
+    --eng: #6d685f;
+    --good-bg: #e3efe6; --good-text: #1a6b34;
+    --warn-bg: #f6ecd4; --warn-text: #7a5d00;
+    --neutral-bg: #efeae1; --neutral-text: #5c564d;
+    --shadow: 0 2px 8px rgba(26,22,18,0.06);
+  }
+
+  body { background: var(--bg-2); color: var(--ink); font-family: var(--body); line-height: 1.45; }
+
+  /* Phone canvas: true mobile width, framed on larger screens */
+  .phone { max-width: 400px; margin: 0 auto; background: var(--bg); min-height: 100vh; }
+  @media (min-width: 480px) {
+    .phone { margin: 1.5rem auto; border: 1px solid var(--border); border-radius: 24px; overflow: hidden; box-shadow: var(--shadow); }
+  }
+  .inner { padding: 1rem 0.9rem 3rem; }
+
+  .mock-note {
+    background: var(--accent-bg); border: 1px solid var(--border); border-radius: 8px;
+    padding: 0.5rem 0.75rem; font-size: 0.78rem; color: var(--ink-2); margin-bottom: 1rem;
+  }
+  .mock-note strong { color: var(--accent); }
+
+  h1 { font-family: var(--display); font-size: 1.7rem; font-weight: 700; margin: 0 0 0.2rem; }
+  .sub { color: var(--ink-2); margin: 0 0 1rem; font-size: 0.88rem; }
+
+  /* Sticky school chip bar — horizontal scroll */
+  .chipbar {
+    position: sticky; top: 0; z-index: 10; background: var(--bg);
+    display: flex; gap: 0.5rem; overflow-x: auto; padding: 0.6rem 0.9rem;
+    border-bottom: 1px solid var(--border); margin: 0 -0.9rem 1rem; -webkit-overflow-scrolling: touch;
+  }
+  .chipbar::-webkit-scrollbar { display: none; }
+  .schip {
+    flex: none; display: inline-flex; align-items: center; gap: 0.4rem;
+    background: var(--card); border: 1px solid var(--border); border-radius: 999px;
+    padding: 0.35rem 0.7rem; font-size: 0.8rem; font-weight: 600; white-space: nowrap;
+  }
+  .schip .dot { width: 9px; height: 9px; border-radius: 50%; }
+  .schip .x { border: none; background: var(--bg-2); color: var(--ink-3); border-radius: 50%; width: 17px; height: 17px; font-size: 0.7rem; line-height: 1; }
+  .schip.add { color: var(--accent); border-style: dashed; }
+
+  h2.section-title {
+    font-family: var(--display); font-size: 1.2rem; font-weight: 700;
+    margin: 1.6rem 0 0; padding-left: 0.6rem; border-left: 3px solid var(--accent);
+  }
+  .how { font-size: 0.78rem; color: var(--ink-3); margin: 0.3rem 0 0.75rem 0.8rem; }
+
+  /* Measure-first block: one measure, all schools under it */
+  .measure { background: var(--card); border: 1px solid var(--border); border-radius: 12px; padding: 0.75rem 0.85rem; margin-bottom: 0.6rem; box-shadow: var(--shadow); }
+  .measure .mt { font-size: 0.85rem; font-weight: 600; display: flex; align-items: center; gap: 0.35rem; }
+  .measure .mh { font-size: 0.75rem; color: var(--ink-3); margin-top: 0.05rem; }
+  .srow { display: flex; align-items: center; gap: 0.5rem; padding: 0.45rem 0; border-top: 1px solid var(--border); margin-top: 0.45rem; flex-wrap: wrap; }
+  .srow:first-of-type { border-top: none; }
+  .srow .dot { width: 9px; height: 9px; border-radius: 50%; flex: none; }
+  .srow .sn { font-size: 0.8rem; font-weight: 600; color: var(--ink-2); width: 4.6rem; flex: none; }
+  .srow .val { font-weight: 700; font-variant-numeric: tabular-nums; font-size: 0.95rem; }
+  .srow .note { font-size: 0.74rem; color: var(--ink-3); flex-basis: 100%; padding-left: 1.1rem; margin-top: -0.15rem; }
+
+  .chip { display: inline-block; font-size: 0.68rem; font-weight: 600; border-radius: 999px; padding: 0.12rem 0.5rem; white-space: nowrap; }
+  .chip.good { background: var(--good-bg); color: var(--good-text); }
+  .chip.warn { background: var(--warn-bg); color: var(--warn-text); }
+  .chip.neutral { background: var(--neutral-bg); color: var(--neutral-text); }
+  .ofsted-badge { display: inline-block; font-weight: 700; border-radius: 6px; padding: 0.14rem 0.5rem; font-size: 0.78rem; }
+  .ofsted-1 { background: var(--good-bg); color: var(--good-text); }
+  .illus { display: inline-block; font-size: 0.62rem; font-weight: 600; color: var(--accent); border: 1px dashed var(--accent); border-radius: 4px; padding: 0 0.3rem; }
+  .help { display: inline-flex; width: 14px; height: 14px; border-radius: 50%; border: 1px solid var(--ink-3); color: var(--ink-3); font-size: 0.6rem; align-items: center; justify-content: center; flex: none; }
+
+  /* Dot strips */
+  .strip-row { margin: 0.9rem 0 1.3rem; }
+  .strip-row .t { font-weight: 600; font-size: 0.82rem; }
+  .strip { position: relative; height: 32px; margin-top: 0.4rem; }
+  .strip .track { position: absolute; left: 0; right: 0; top: 14px; height: 4px; border-radius: 2px; background: var(--bg-2); }
+  .strip .eng-tick { position: absolute; top: 4px; width: 2px; height: 24px; background: var(--eng); }
+  .strip .eng-lbl { position: absolute; top: -12px; transform: translateX(-50%); font-size: 0.62rem; color: var(--ink-3); white-space: nowrap; }
+  .strip .pt { position: absolute; top: 9px; width: 14px; height: 14px; border-radius: 50%; transform: translateX(-50%); border: 2px solid var(--card); box-shadow: 0 0 0 1px rgba(0,0,0,0.08); }
+  .strip .pt-lbl { position: absolute; top: 25px; transform: translateX(-50%); font-size: 0.64rem; font-weight: 600; }
+  .legend { display: flex; gap: 0.8rem; flex-wrap: wrap; font-size: 0.72rem; color: var(--ink-2); margin-top: 0.4rem; }
+  .legend .li { display: inline-flex; align-items: center; gap: 0.3rem; }
+  .legend .sw { width: 9px; height: 9px; border-radius: 50%; }
+  .legend .engsw { width: 2px; height: 11px; background: var(--eng); }
+
+  .rc-list { display: flex; flex-direction: column; gap: 0.25rem; width: 100%; padding-left: 1.1rem; }
+  .rc-row { display: flex; justify-content: space-between; align-items: center; font-size: 0.74rem; }
+  .rc-row .a { color: var(--ink-2); }
+
+  details.more-measures { margin-bottom: 0.6rem; }
+  details.more-measures summary { cursor: pointer; font-weight: 600; font-size: 0.82rem; color: var(--accent); padding: 0.2rem 0.2rem 0.5rem; }
+  .strip-note { font-size: 0.72rem; color: var(--ink-3); margin: 0.4rem 0.2rem 0; }
+  .metric-picker { margin-bottom: 0.6rem; }
+  .metric-picker select { width: 100%; font-family: inherit; font-size: 0.85rem; padding: 0.45rem 0.6rem; border-radius: 8px; border: 1px solid var(--border); background: var(--card); color: var(--ink); }
+  .chart-wrap { overflow-x: auto; -webkit-overflow-scrolling: touch; background: var(--card); border: 1px solid var(--border); border-radius: 12px; padding: 0.75rem; }
+  .swipe-hint { font-size: 0.7rem; color: var(--ink-3); text-align: center; margin-top: 0.3rem; }
+  .covid { fill: var(--bg-2); }
+  .covid-lbl { font-size: 0.6rem; fill: var(--ink-3); }
+
+  .footnote { font-size: 0.7rem; color: var(--ink-3); margin-top: 2rem; border-top: 1px solid var(--border); padding-top: 0.8rem; }
+</style>
+
+<div class="phone"><div class="inner">
+  <p class="mock-note"><strong>Mobile mockup — proposed /compare.</strong> Mobile-first layout: measures stack vertically with all schools under each, so nothing needs horizontal swiping. Same live data as the desktop mockup.</p>
+
+  <h1>Compare schools</h1>
+  <p class="sub">Anchored against the England average — the grey tick — so you can tell what's typical at a glance.</p>
+
+  <div class="chipbar" aria-label="Schools in this comparison">
+    <span class="schip"><span class="dot" style="background:var(--s1)"></span>Barclay <button class="x" aria-label="Remove Barclay">×</button></span>
+    <span class="schip"><span class="dot" style="background:var(--s2)"></span>Elmhurst <button class="x" aria-label="Remove Elmhurst">×</button></span>
+    <span class="schip"><span class="dot" style="background:var(--s3)"></span>Plumcroft <button class="x" aria-label="Remove Plumcroft">×</button></span>
+    <span class="schip add">+ Add</span>
+  </div>
+
+  <h2 class="section-title">At a glance</h2>
+  <p class="how">The short version — each measure is explained in its own section below.</p>
+
+  <div class="measure">
+    <div class="mt">Latest Ofsted inspection</div>
+    <div class="srow"><span class="dot" style="background:var(--s1)"></span><span class="sn">Barclay</span><span class="ofsted-badge ofsted-1">Outstanding</span><span class="note">Older-style inspection, Oct 2021</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s2)"></span><span class="sn">Elmhurst</span><span class="ofsted-badge ofsted-1">Outstanding</span><span class="note">Older-style inspection, Oct 2021</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s3)"></span><span class="sn">Plumcroft</span><span><span class="chip good">4 areas Strong standard</span> <span class="chip neutral">2 areas Expected</span> <span class="chip warn">Attendance &amp; behaviour: Attention needed</span> <span class="illus">illustrative</span></span><span class="note">New-style report card, Nov 2025 · safeguarding met · full detail in the Ofsted section below</span></div>
+  </div>
+
+  <div class="measure">
+    <div class="mt">Children reaching the expected standard <span class="help" title="% of Year 6 pupils reaching the expected standard in reading, writing and maths (2024/25).">?</span></div>
+    <div class="mh">England average: 62%</div>
+    <div class="srow"><span class="dot" style="background:var(--s1)"></span><span class="sn">Barclay</span><span class="val" style="color:var(--s1-text)">87%</span> <span class="chip good">Above average</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s2)"></span><span class="sn">Elmhurst</span><span class="val" style="color:var(--s2-text)">92%</span> <span class="chip good">Above average</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s3)"></span><span class="sn">Plumcroft</span><span class="val" style="color:var(--s3-text)">79%</span> <span class="chip good">Above average</span></div>
+  </div>
+
+  <div class="measure">
+    <div class="mt">Getting a place</div>
+    <div class="srow"><span class="dot" style="background:var(--s1)"></span><span class="sn">Barclay</span><span class="chip good">97% of first choices offered</span><span class="note">Named on 457 forms · 180 places</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s2)"></span><span class="sn">Elmhurst</span><span class="chip warn">73% of first choices offered</span><span class="note">Named on 342 forms · 120 places</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s3)"></span><span class="sn">Plumcroft</span><span class="chip good">All first choices offered</span><span class="note">Named on 185 forms · 80 places</span></div>
+  </div>
+
+  <h2 class="section-title">Ofsted inspection</h2>
+  <p class="how">Ofsted stopped giving a single overall grade in September 2024 (inspections until November 2025 kept the area-by-area judgements); from November 2025 new inspections produce a report card rating each area of school life (Exceptional · Strong standard · Expected standard · Attention needed · Urgent improvement). A report card and an older grade aren't directly comparable. Ofsted's "Expected standard" rating is unrelated to the KS2 test measure below.</p>
+
+  <div class="measure">
+    <div class="mt">Latest inspection</div>
+    <div class="srow"><span class="dot" style="background:var(--s1)"></span><span class="sn">Barclay</span><span class="ofsted-badge ofsted-1">Outstanding</span><span class="chip neutral">4+ years ago</span><span class="note">7 Oct 2021 · we don't hold area-by-area detail for this inspection · <a href="https://reports.ofsted.gov.uk/provider/21/138690" style="color:var(--accent)">Ofsted page →</a></span></div>
+    <div class="srow" style="align-items:flex-start"><span class="dot" style="background:var(--s2);margin-top:4px"></span><span class="sn">Elmhurst</span><span><span class="ofsted-badge ofsted-1">Outstanding</span> <span class="chip neutral">4+ years ago</span> <span style="font-size:0.72rem;color:var(--ink-3)">6 Oct 2021</span></span>
+      <div class="rc-list">
+        <div class="rc-row"><span class="a">Quality of education</span><span class="chip good">Outstanding</span></div>
+        <div class="rc-row"><span class="a">Behaviour &amp; attitudes</span><span class="chip good">Outstanding</span></div>
+        <div class="rc-row"><span class="a">Personal development</span><span class="chip good">Outstanding</span></div>
+        <div class="rc-row"><span class="a">Leadership &amp; management</span><span class="chip good">Outstanding</span></div>
+      </div>
+      <span class="note"><a href="https://reports.ofsted.gov.uk/provider/21/145362" style="color:var(--accent)">Ofsted page →</a></span>
+    </div>
+    <div class="srow" style="align-items:flex-start"><span class="dot" style="background:var(--s3);margin-top:4px"></span><span class="sn">Plumcroft</span><span><strong style="font-size:0.85rem">Report card</strong> <span class="illus">illustrative</span> <span style="font-size:0.72rem;color:var(--ink-3)">14 Nov 2025</span></span>
+      <div class="rc-list">
+        <div class="rc-row"><span class="a">Achievement</span><span class="chip good">Strong standard</span></div>
+        <div class="rc-row"><span class="a">Curriculum &amp; teaching</span><span class="chip good">Strong standard</span></div>
+        <div class="rc-row"><span class="a">Attendance &amp; behaviour</span><span class="chip warn">Attention needed</span></div>
+        <div class="rc-row"><span class="a">Personal development</span><span class="chip good">Strong standard</span></div>
+        <div class="rc-row"><span class="a">Inclusion</span><span class="chip neutral">Expected standard</span></div>
+        <div class="rc-row"><span class="a">Leadership &amp; governance</span><span class="chip good">Strong standard</span></div>
+        <div class="rc-row"><span class="a">Early years</span><span class="chip neutral">Expected standard</span></div>
+        <div class="rc-row"><span class="a">Safeguarding</span><span class="chip good">Met</span></div>
+      </div>
+      <span class="note"><a href="https://reports.ofsted.gov.uk/provider/21/100140" style="color:var(--accent)">Ofsted page →</a></span>
+    </div>
+  </div>
+
+  <h2 class="section-title">How children do academically</h2>
+  <p class="how">End of Year 6 national tests and teacher assessments (2024/25) — writing is teacher-assessed. Each line runs 0–100%; the grey tick is the England average.</p>
+  <div class="measure" id="strips"></div>
+  <details class="more-measures">
+    <summary>More measures — grammar, punctuation &amp; spelling, science, scaled scores</summary>
+    <div class="measure" id="strips-more" style="margin-top:0.5rem"></div>
+    <p class="strip-note">Strips show the 100–120 window of the full 80–120 scaled-score range; 100 is the expected standard (the strip widens if a school averages below it). England ticks for GPS and science aren't in our dataset yet, and the scaled-score ticks are indicative — official DfE figures will be loaded before launch.</p>
+  </details>
+  <div class="legend" id="strip-legend" style="padding:0 0.2rem 0"></div>
+
+  <div class="measure" style="margin-top:0.9rem">
+    <div class="mt">Children from lower-income families <span class="help" title="% of disadvantaged pupils (free school meals in the last 6 years, or looked after by the local authority) reaching the expected standard. State-school average: 46% (computed from our dataset). Small pupil groups — single pupils can move a school's figure noticeably.">?</span></div>
+    <div class="mh">State-school average: 46%</div>
+    <div class="srow"><span class="dot" style="background:var(--s1)"></span><span class="sn">Barclay</span><span class="val">86%</span> <span class="chip good">Well above average</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s2)"></span><span class="sn">Elmhurst</span><span class="val">93%</span> <span class="chip good">Well above average</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s3)"></span><span class="sn">Plumcroft</span><span class="val">72%</span> <span class="chip good">Above average</span></div>
+  </div>
+
+  <h2 class="section-title">Getting a place</h2>
+  <p class="how">September 2026 entry. "First choice" = families who ranked the school top of their form (officially a "first preference"). Schools never see your ranking — places go by the admission criteria alone. Figures are National Offer Day offers; waiting lists and appeals can change the final intake.</p>
+  <div class="measure">
+    <div class="mt">First-choice families offered a place</div>
+    <div class="srow"><span class="dot" style="background:var(--s1)"></span><span class="sn">Barclay</span><span class="val">97%</span><span class="note">Named on 457 forms · 180 places</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s2)"></span><span class="sn">Elmhurst</span><span class="val">73%</span> <span class="chip warn">Over 1 in 4 missed out</span><span class="note">Named on 342 forms · 120 places — check the school's admission criteria (for most non-faith primaries, distance decides)</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s3)"></span><span class="sn">Plumcroft</span><span class="val">100%</span><span class="note">Named on 185 forms · 80 places · every first choice offered</span></div>
+  </div>
+
+  <h2 class="section-title">Who goes there</h2>
+  <p class="how">From the latest school census (2025/26). No "right" numbers here — just context.</p>
+  <div class="measure">
+    <div class="mt">Pupils on roll</div>
+    <div class="srow"><span class="dot" style="background:var(--s1)"></span><span class="sn">Barclay</span><span class="val">1,273</span><span class="note">At or above capacity · much larger than average · girls 51% / boys 49%</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s2)"></span><span class="sn">Elmhurst</span><span class="val">980</span><span class="note">98% full · much larger than average · girls 48% / boys 52%</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s3)"></span><span class="sn">Plumcroft</span><span class="val">1,056</span><span class="note">At or above capacity · much larger than average · girls 51% / boys 49%</span></div>
+  </div>
+  <div class="measure">
+    <div class="mt">Free school meals <span class="help" title="% eligible for free school meals. State-school average: 25% (computed from our dataset).">?</span></div>
+    <div class="mh">State-school average: 25% (our dataset)</div>
+    <div class="srow"><span class="dot" style="background:var(--s1)"></span><span class="sn">Barclay</span><span class="val">26%</span> <span class="chip neutral">About average</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s2)"></span><span class="sn">Elmhurst</span><span class="val">25%</span> <span class="chip neutral">About average</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s3)"></span><span class="sn">Plumcroft</span><span class="val">30%</span> <span class="chip neutral">A little above</span></div>
+  </div>
+  <div class="measure">
+    <div class="mt">English as an additional language · extra learning support (SEN) <span class="help" title="SEN = pupils receiving SEN support, not including EHC plans. State-school average: ≈14% (computed from our dataset). A high figure can mean the school hosts specialist provision — often a strength, not a warning sign.">?</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s1)"></span><span class="sn">Barclay</span><span style="font-size:0.85rem">EAL 62% · SEN 6%</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s2)"></span><span class="sn">Elmhurst</span><span style="font-size:0.85rem">EAL 84% · SEN 8%</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s3)"></span><span class="sn">Plumcroft</span><span style="font-size:0.85rem">EAL 20% · SEN 28% <span class="chip neutral">SEN well above avg</span></span></div>
+  </div>
+  <div class="measure">
+    <div class="mt">Basics</div>
+    <div class="srow"><span class="dot" style="background:var(--s1)"></span><span class="sn">Barclay</span><span style="font-size:0.85rem">Ages 3–11 · nursery · no faith · Lion Academy Trust</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s2)"></span><span class="sn">Elmhurst</span><span style="font-size:0.85rem">Ages 3–11 · nursery · no faith · New Vision Trust</span></div>
+    <div class="srow"><span class="dot" style="background:var(--s3)"></span><span class="sn">Plumcroft</span><span style="font-size:0.85rem">Ages 3–11 · nursery · no faith · Greenwich council</span></div>
+  </div>
+
+  <h2 class="section-title">Explore trends</h2>
+  <p class="how">Every measure from the current compare page lives on here, grouped. Three are wired up in this mockup. School lines break where a year isn't in our dataset.</p>
+  <div class="metric-picker">
+    <select id="metric-select" aria-label="Measure">
+      <optgroup label="Expected standard">
+        <option value="rwm" selected>Reading, writing &amp; maths (combined)</option>
+        <option value="reading">Reading</option>
+        <option value="maths">Maths</option>
+        <option disabled>Writing (TA) · GPS · Science (TA)</option>
+      </optgroup>
+      <optgroup label="Higher standard"><option disabled>RWM · Reading · Maths · GPS</option><option disabled>Writing — greater depth (TA)</option></optgroup>
+      <optgroup label="Average scaled scores"><option disabled>Reading · Maths · GPS</option></optgroup>
+      <optgroup label="Equity"><option disabled>Disadvantaged pupils — expected standard</option></optgroup>
+      <optgroup label="School context"><option disabled>FSM % · EAL % · SEN support %</option></optgroup>
+    </select>
+  </div>
+  <div class="chart-wrap">
+    <svg id="trendchart" width="620" height="240" role="img" aria-label="Line chart: selected measure by year for three schools and England average"></svg>
+    <div class="legend" id="trend-legend"></div>
+  </div>
+  <p class="swipe-hint">← swipe the chart →</p>
+
+  <p class="footnote">
+    Sources: DfE Compare School Performance, Ofsted inspection outcomes, DfE admissions data, school census — all from datasets SchoolCompare already collects. England averages for test results are official DfE figures; FSM, language, SEN, size and disadvantaged-pupil benchmarks are computed across state schools in our dataset. Plumcroft's Ofsted report card is a made-up example of the November 2025 format (its real latest inspection is Good, June 2023). Following DfE practice, figures based on 5 or fewer pupils are suppressed and shown as "no data". Static mockup — tooltips and "+ Add" are illustrative.
+  </p>
+</div></div>
+
+<script>
+(function () {
+  const css = (v) => getComputedStyle(document.documentElement).getPropertyValue(v).trim();
+  const schools = [
+    { name: 'Barclay',   color: () => css('--s1'), text: () => css('--s1-text') },
+    { name: 'Elmhurst',  color: () => css('--s2'), text: () => css('--s2-text') },
+    { name: 'Plumcroft', color: () => css('--s3'), text: () => css('--s3-text') },
+  ];
+
+  const strips = [
+    { label: 'Reading, writing & maths', eng: 62, vals: [87, 92, 79] },
+    { label: 'Reading', eng: 75, vals: [91, 92, 87] },
+    { label: 'Writing', eng: 72, vals: [94, 92, 83] },
+    { label: 'Maths', eng: 74, vals: [91, 95, 84] },
+    { label: 'Higher standard', eng: 8, vals: [22, 27, 12], tip: 'A high score in the reading and maths tests plus \u201cgreater depth\u201d in teacher-assessed writing.' },
+  ];
+  function renderStrips(list, el) {
+    list.forEach((s) => {
+      const min = s.min ?? 0, max = s.max ?? 100, unit = s.unit ?? '%';
+      const pos = v => (v - min) / (max - min) * 100;
+      const row = document.createElement('div');
+      row.className = 'strip-row';
+      let pts = '';
+      const sorted = s.vals.map((v, i) => ({ v, i })).sort((a, b) => a.v - b.v);
+      let lastBelow = -Infinity;
+      const nudge = (max - min) * 0.08;
+      sorted.forEach(({ v, i }) => {
+        const above = (v - lastBelow) < nudge;
+        if (!above) lastBelow = v;
+        pts += `<span class="pt" style="left:${pos(v)}%;background:${schools[i].color()}" title="${schools[i].name}: ${v}${unit}"></span>`
+             + `<span class="pt-lbl" style="left:${pos(v)}%;color:${schools[i].text()};${above ? 'top:-6px' : ''}">${v}</span>`;
+      });
+      const eng = s.eng != null
+        ? `<span class="eng-tick" style="left:${pos(s.eng)}%"></span><span class="eng-lbl" style="left:${pos(s.eng)}%">Eng ${s.eng}${unit}</span>`
+        : '';
+      row.innerHTML = `
+        <div class="t"${s.tip ? ` title="${s.tip}"` : ''}>${s.label}</div>
+        <div class="strip" role="img" aria-label="${s.label}: ${s.eng != null ? 'England average ' + s.eng + unit + ', ' : ''}${s.vals.map((v, i) => schools[i].name + ' ' + v + unit).join(', ')}">
+          <div class="track"></div>
+          ${eng}
+          ${pts}
+        </div>`;
+      el.appendChild(row);
+    });
+  }
+  renderStrips(strips, document.getElementById('strips'));
+  renderStrips([
+    { label: 'Grammar, punctuation & spelling', eng: null, vals: [86, 94, 82] },
+    { label: 'Science (teacher-assessed)', eng: null, vals: [95, 91, 83], tip: 'Teacher-assessed, like writing — no KS2 science test since 2009; comparisons are indicative.' },
+    { label: 'Avg scaled score — reading', eng: 106, vals: [107, 110, 109], min: 100, max: 120, unit: '' },
+    { label: 'Avg scaled score — maths', eng: 105, vals: [108, 113, 108], min: 100, max: 120, unit: '' },
+    { label: 'Avg scaled score — GPS', eng: 105, vals: [107, 114, 109], min: 100, max: 120, unit: '' },
+  ], document.getElementById('strips-more'));
+  document.getElementById('strip-legend').innerHTML =
+    schools.map(s => `<span class="li"><span class="sw" style="background:${s.color()}"></span>${s.name}</span>`).join('')
+    + '<span class="li"><span class="engsw"></span>England average</span>';
+
+  /* Metric-driven trend chart. Lines always break across the covid band
+     (2019/20-2020/21, cancelled tests); other nulls are dataset gaps. */
+  const years = ['2015/16','2016/17','2017/18','2018/19','2021/22','2022/23','2023/24','2024/25'];
+  const METRICS = {
+    rwm:     { school: { Barclay: [52,76,65,87,null,87,75,87], Elmhurst: [80,81,86,88,null,88,88,92], Plumcroft: [58,64,57,69,null,62,72,79] },
+               england: [null,61.1,64.3,64.9,58.7,59.5,60.6,62.1] },
+    reading: { school: { Barclay: [57,84,76,87,null,null,79,91], Elmhurst: [88,91,92,91,null,null,92,92], Plumcroft: [59,68,72,79,null,null,82,87] },
+               england: [null,71.6,75.3,73.2,74.6,72.8,74.4,75.0] },
+    maths:   { school: { Barclay: [81,82,74,90,null,null,88,91], Elmhurst: [96,89,97,97,null,null,96,95], Plumcroft: [80,80,69,90,null,null,84,84] },
+               england: [null,74.8,75.5,78.7,71.5,73.0,73.2,74.0] },
+  };
+  const schoolColor = { Barclay: () => css('--s1'), Elmhurst: () => css('--s2'), Plumcroft: () => css('--s3') };
+  const svg = document.getElementById('trendchart');
+  const W = 620, H = 240, L = 38, R = 44, T = 14, B = 34;
+  const slots = [0,1,2,3,6,7,8,9]; const maxSlot = 9;
+  const X = i => L + slots[i] * (W - L - R) / maxSlot;
+  const Y = v => T + (100 - v) * (H - T - B) / 60;
+  function runs(vals) {
+    const out = []; let cur = [];
+    vals.forEach((v, i) => {
+      if (v == null) { if (cur.length) out.push(cur); cur = []; return; }
+      if (i === 4 && cur.length && cur[cur.length - 1] === 3) { out.push(cur); cur = []; }
+      cur.push(i);
+    });
+    if (cur.length) out.push(cur);
+    return out;
+  }
+  function renderChart(key) {
+    const m = METRICS[key];
+    const ink3 = css('--ink-3'), border = css('--border');
+    let g = '';
+    const bx1 = X(3) + 12, bx2 = X(4) - 12;
+    g += `<rect class="covid" x="${bx1}" y="${T}" width="${bx2 - bx1}" height="${H - T - B}" rx="4"/>`;
+    g += `<text class="covid-lbl" x="${(bx1 + bx2) / 2}" y="${T + 14}" text-anchor="middle">tests cancelled</text>`;
+    g += `<text class="covid-lbl" x="${(bx1 + bx2) / 2}" y="${T + 26}" text-anchor="middle">'19/20-'20/21</text>`;
+    for (let v = 40; v <= 100; v += 20) {
+      g += `<line x1="${L}" y1="${Y(v)}" x2="${W - R}" y2="${Y(v)}" stroke="${border}" stroke-width="1"/>`;
+      g += `<text x="${L - 6}" y="${Y(v) + 4}" text-anchor="end" font-size="10" fill="${ink3}">${v}%</text>`;
+    }
+    years.forEach((yr, i) => {
+      g += `<text x="${X(i)}" y="${H - B + 18}" text-anchor="middle" font-size="9.5" fill="${ink3}">${yr}</text>`;
+    });
+    const path = (vals, idx) => idx.map((i, k) => (k ? 'L' : 'M') + X(i) + ' ' + Y(vals[i])).join(' ');
+    runs(m.england).forEach(idx => {
+      if (idx.length > 1) g += `<path d="${path(m.england, idx)}" fill="none" stroke="${ink3}" stroke-width="1.5" stroke-dasharray="5 4"/>`;
+      else g += `<circle cx="${X(idx[0])}" cy="${Y(m.england[idx[0]])}" r="2" fill="${ink3}"><title>England ${years[idx[0]]}: ${Math.round(m.england[idx[0]])}%</title></circle>`;
+    });
+    Object.entries(m.school).forEach(([name, vals]) => {
+      const color = schoolColor[name]();
+      runs(vals).forEach(idx => {
+        if (idx.length > 1) g += `<path d="${path(vals, idx)}" fill="none" stroke="${color}" stroke-width="2" stroke-linecap="round"/>`;
+      });
+      vals.forEach((v, i) => {
+        if (v == null) return;
+        g += `<circle cx="${X(i)}" cy="${Y(v)}" r="3" fill="${color}" stroke="${css('--card')}" stroke-width="1.5"><title>${name} ${years[i]}: ${v}%</title></circle>`;
+      });
+    });
+    const ends = Object.entries(m.school)
+      .map(([name, vals]) => ({ v: vals[vals.length - 1], i: vals.length - 1 }))
+      .filter(e => e.v != null)
+      .sort((a, b) => a.v - b.v);
+    let prevY = Infinity;
+    ends.forEach(e => {
+      let y = Y(e.v) + 3.5;
+      if (prevY - y < 12) y = prevY - 12;
+      prevY = y;
+      g += `<text x="${X(e.i) + 7}" y="${y}" font-size="10" font-weight="600" fill="${ink3}">${e.v}%</text>`;
+    });
+    svg.innerHTML = g;
+    document.getElementById('trend-legend').innerHTML =
+      Object.keys(m.school).map(name => `<span class="li"><span class="sw" style="background:${schoolColor[name]()}"></span>${name}</span>`).join('')
+      + `<span class="li"><span class="sw" style="background:none;border-top:2px dashed ${ink3};border-radius:0;height:0"></span>England avg</span>`;
+  }
+  renderChart('rwm');
+  document.getElementById('metric-select').addEventListener('change', e => renderChart(e.target.value));
+
+  new MutationObserver(muts => { if (muts.some(m => m.attributeName === 'data-theme')) location.reload(); })
+    .observe(document.documentElement, { attributes: true });
+})();
+</script>
@@ -19,12 +19,43 @@ function schoolLinks(page: Page) {
  return page.locator('a[href^="/school/"]');
 }

+/**
+ * Two URNs guaranteed to be pure-primary (same phase). The compare page's
+ * phase tabs split all-through schools (which carry KS4 data) onto the
+ * secondary tab, so picking two arbitrary "primary" search hits can land
+ * them on different tabs where only the active one renders. Selecting via
+ * the API by exact phase keeps both on the same tab. Data-invariant: uses
+ * whatever primaries the environment holds.
+ */
+async function twoPrimaryUrns(page: Page): Promise<[string, string]> {
+  const res = await page.request.get('/api/schools?search=primary&per_page=50');
+  expect(res.ok()).toBeTruthy();
+  const body = await res.json();
+  const urns: string[] = (body.schools ?? [])
+    .filter((s: { phase?: string; rwm_expected_pct?: number | null }) =>
+      s.phase === 'Primary' && s.rwm_expected_pct != null,
+    )
+    .map((s: { urn: number }) => String(s.urn));
+  expect(urns.length).toBeGreaterThanOrEqual(2);
+  return [urns[0], urns[1]];
+}
+
 test('home page loads with hero search', async ({ page }) => {
  await page.goto('/');
  await expect(page.locator('h1').first()).toBeVisible();
  await expect(page.getByPlaceholder('School name or postcode').first()).toBeVisible();
 });

+test('home hero offers a "use my location" shortcut beside the search box', async ({ page }) => {
+  await page.goto('/');
+  // The geolocation shortcut lives inside the hero search card, right under the
+  // search input — not in a separate strip further down the page.
+  const searchInput = page.getByPlaceholder('School name or postcode').first();
+  await expect(searchInput).toBeVisible();
+  const nearMe = page.getByRole('button', { name: /use my location/i });
+  await expect(nearMe).toBeVisible();
+});
+
 test('searching by name returns school results', async ({ page }) => {
  await searchByName(page, 'primary');
  await expect(schoolLinks(page).first()).toBeVisible({ timeout: 15_000 });
@@ -50,6 +81,34 @@ test('school detail page renders name and performance data', async ({ page }) =>
  await expect(page.locator('canvas:visible').first()).toBeVisible({ timeout: 15_000 });
 });

+test('school with no performance data still gets a working detail page', async ({ page }) => {
+  // Schools without KS2/KS4 results (special post-16 institutions, sixth-form
+  // centres, PRUs) used to 500 in the API — NaN GIAS fields broke JSON
+  // serialization — which the frontend rendered as a 404 on every such SEO
+  // landing page. Find one via the search API (year === null marks "no
+  // performance rows") and assert its page renders.
+  const candidates: number[] = [];
+  for (const q of ['post 16', 'specialist college', 'sixth form']) {
+    const resp = await page.request.get(
+      `/api/schools?search=${encodeURIComponent(q)}&per_page=20`
+    );
+    if (!resp.ok()) continue;
+    const body = await resp.json();
+    for (const s of body.schools ?? []) {
+      if (s.year === null && s.urn) candidates.push(s.urn);
+    }
+    if (candidates.length) break;
+  }
+  test.skip(candidates.length === 0, 'no results-less school in this dataset');
+
+  const detail = await page.request.get(`/api/schools/${candidates[0]}`);
+  expect(detail.status(), 'detail API must not 500 for a results-less school').toBe(200);
+
+  await page.goto(`/school/${candidates[0]}`);
+  await page.waitForURL(/\/school\/\d+-/); // redirected to canonical slug
+  await expect(page.locator('h1').first()).toBeVisible();
+});
+
 test('school hero map opens fullscreen on mobile without the Fullscreen API', async ({ page }) => {
  // iOS Safari has no Element.requestFullscreen; the map must fall back to a
  // CSS overlay. Simulate that by removing the API before any page script runs.
@@ -75,20 +134,69 @@ test('school hero map opens fullscreen on mobile without the Fullscreen API', as
  await expect(openMap).toBeVisible();
 });

-test('comparing two schools shows both side by side', async ({ page }) => {
-  // Collect two school URNs from search results, then load the share URL
-  await searchByName(page, 'primary');
-  await expect(schoolLinks(page).first()).toBeVisible({ timeout: 15_000 });
-  const hrefs = await schoolLinks(page).evaluateAll((links) =>
-    links.map((l) => (l as HTMLAnchorElement).getAttribute('href') || '')
-  );
-  const urns = [...new Set(hrefs.map((h) => h.match(/\/school\/(\d+)/)?.[1]).filter(Boolean))];
-  expect(urns.length).toBeGreaterThanOrEqual(2);
+test('results map fullscreen falls back to an overlay on iOS', async ({ page }) => {
+  // Same iOS gap as the hero map: no Element.requestFullscreen, so the results
+  // map's fullscreen button must fall back to a CSS overlay.
+  await page.setViewportSize({ width: 390, height: 844 });
+  await page.addInitScript(() => {
+    // @ts-expect-error deliberate API removal
+    delete Element.prototype.requestFullscreen;
+  });

-  await page.goto(`/compare?urns=${urns[0]},${urns[1]}`);
+  await searchByName(page, 'B1 1BB');
+  await expect(schoolLinks(page).first()).toBeVisible({ timeout: 15_000 });
+
+  // Switch to the map view, then open the map fullscreen.
+  await page.getByRole('button', { name: 'Map', exact: true }).click();
+  const openFs = page.getByRole('button', { name: 'View map fullscreen' });
+  await expect(openFs).toBeVisible({ timeout: 15_000 });
+  await openFs.click();
+
+  // The button flips to its exit state once the overlay is up.
+  const exitFs = page.getByRole('button', { name: 'Exit fullscreen' });
+  await expect(exitFs).toBeVisible();
+  await exitFs.click();
+  await expect(openFs).toBeVisible();
+});
+
+test('comparing two schools shows the parent-first sections side by side', async ({ page }) => {
+  // Two same-phase (pure primary) schools so both stay on one tab.
+  const [urn0, urn1] = await twoPrimaryUrns(page);
+
+  await page.goto(`/compare?urns=${urn0},${urn1}`);
  // Both schools' detail links should render in the comparison view
-  await expect(page.locator(`a[href*="${urns[0]}"]`).first()).toBeVisible({ timeout: 15_000 });
-  await expect(page.locator(`a[href*="${urns[1]}"]`).first()).toBeVisible();
+  await expect(page.locator(`a[href*="${urn0}"]`).first()).toBeVisible({ timeout: 15_000 });
+  await expect(page.locator(`a[href*="${urn1}"]`).first()).toBeVisible();
+
+  // The parent-first sections render in order (data-invariant: headings only)
+  for (const heading of [
+    'At a glance',
+    'Ofsted inspection',
+    /How (children|students) do academically/,
+    'Who goes there',
+    'Explore trends',
+  ]) {
+    await expect(
+      page.getByRole('heading', { name: heading }).first(),
+    ).toBeVisible({ timeout: 15_000 });
+  }
+
+  // Every number gets an anchor: at least one England-average tick or label
+  await expect(page.getByText(/England \d+/).first()).toBeVisible();
+
+  // Ofsted linkout goes to the school's provider page, never a report deep-link
+  const ofstedLink = page.getByRole('link', { name: /Ofsted page/i }).first();
+  await expect(ofstedLink).toBeVisible();
+  expect(await ofstedLink.getAttribute('href')).toMatch(
+    /reports\.ofsted\.gov\.uk\/provider\/21\/\d+/
+  );
+
+  // A school never shows both an overall-grade badge AND report-card detail:
+  // "Report card" implies "no overall grade is given" copy is present too.
+  const reportCards = await page.getByText('Report card', { exact: true }).count();
+  if (reportCards > 0) {
+    await expect(page.getByText(/no overall grade/i).first()).toBeVisible();
+  }
 });

 test('compare chart on mobile shows school chips with tap-to-focus', async ({ page }) => {
@@ -100,15 +208,51 @@ test('compare chart on mobile shows school chips with tap-to-focus', async ({ pa
    links.map((l) => (l as HTMLAnchorElement).getAttribute('href') || '')
  );
  const urns = [...new Set(hrefs.map((h) => h.match(/\/school\/(\d+)/)?.[1]).filter(Boolean))];
-  expect(urns.length).toBeGreaterThanOrEqual(2);
+  // Compare three schools, not two: a "primary" search can return all-through
+  // schools that classify as secondary, and the chips only appear for the
+  // active phase. With three schools across two phases, the auto-selected
+  // majority phase always holds ≥2, so the chip legend is guaranteed to render.
+  expect(urns.length).toBeGreaterThanOrEqual(3);

-  await page.goto(`/compare?urns=${urns[0]},${urns[1]}`);
-  await expect(page.locator('canvas:visible').first()).toBeVisible({ timeout: 15_000 });
+  await page.goto(`/compare?urns=${urns[0]},${urns[1]},${urns[2]}`);

-  // The mobile chart legend renders one chip per school inside the chart card.
+  // Mobile is measure-first: the At a glance section stacks all active-phase
+  // schools inside one flow — no horizontal swiping between school columns.
+  await expect(
+    page.getByRole('heading', { name: 'At a glance' }),
+  ).toBeVisible({ timeout: 15_000 });
+  const body = page.locator('body');
+  const bodyOverflowsX = await body.evaluate(
+    (el) => el.scrollWidth > el.clientWidth + 1,
+  );
+  expect(bodyOverflowsX).toBe(false);
+
+  // The sticky school bar must pin *below* the sticky site header, not at
+  // top:0 where the header covers it and the selected schools are hidden.
+  // Assert the sticky offset directly (robust — no scroll timing needed).
+  const barTop = await page
+    .locator('[class*="schoolBar"]')
+    .first()
+    .evaluate((el) => parseFloat(getComputedStyle(el).top));
+  const headerHeight = await page
+    .locator('[class*="header"]')
+    .first()
+    .evaluate((el) => el.getBoundingClientRect().height);
+  expect(barTop).toBeGreaterThanOrEqual(headerHeight - 1);
+
+  // The trends chart still renders (inside the Explore trends section)…
+  const chartCanvas = page.locator('canvas:visible').first();
+  await expect(chartCanvas).toBeVisible({ timeout: 15_000 });
+  // …at a real height, not the squashed ~150px Chart.js fallback that
+  // appears when the container lacks a definite height.
+  const chartBox = await chartCanvas.boundingBox();
+  expect(chartBox && chartBox.height).toBeGreaterThan(220);
+
+  // …with the mobile chart legend chips and tap-to-focus behaviour intact.
  const chipGroup = page.getByRole('group', { name: /highlight a school/i });
  const chips = chipGroup.getByRole('button');
-  await expect(chips).toHaveCount(2);
+  await expect(chips.first()).toBeVisible({ timeout: 15_000 });
+  expect(await chips.count()).toBeGreaterThanOrEqual(2);

  // Tapping a chip focuses that school's line; tapping again releases it.
  await chips.first().click();
@@ -0,0 +1,106 @@
+import { render, screen } from '@testing-library/react';
+
+import { CompareOfsted } from '@/components/compare/CompareOfsted';
+import type { ComparisonData, OfstedInspection, School } from '@/lib/types';
+
+function school(urn: number, name: string): School {
+  return { urn, school_name: name } as School;
+}
+
+function ofsted(partial: Partial<OfstedInspection>): OfstedInspection {
+  return {
+    framework: null,
+    inspection_date: '2021-10-07',
+    inspection_type: null,
+    overall_effectiveness: null,
+    quality_of_education: null,
+    behaviour_attitudes: null,
+    personal_development: null,
+    leadership_management: null,
+    early_years_provision: null,
+    previous_overall: null,
+    rc_safeguarding_met: null,
+    rc_inclusion: null,
+    rc_curriculum_teaching: null,
+    rc_achievement: null,
+    rc_attendance_behaviour: null,
+    rc_personal_development: null,
+    rc_leadership_governance: null,
+    rc_early_years: null,
+    rc_sixth_form: null,
+    ofsted_page_url: 'https://reports.ofsted.gov.uk/provider/21/1',
+    ...partial,
+  };
+}
+
+const schools = [school(1, 'Graded School'), school(2, 'Carried School'), school(3, 'Card School')];
+
+const data: Record<string, ComparisonData> = {
+  '1': {
+    school_info: schools[0],
+    yearly_data: [],
+    ofsted: ofsted({ overall_effectiveness: 1, grade_source: 'graded' }),
+  },
+  '2': {
+    school_info: schools[1],
+    yearly_data: [],
+    ofsted: ofsted({ overall_effectiveness: 2, grade_source: 'ungraded_carried_forward' }),
+  },
+  '3': {
+    school_info: schools[2],
+    yearly_data: [],
+    ofsted: ofsted({
+      inspection_date: '2025-11-14',
+      rc_safeguarding_met: true,
+      report_card: {
+        rc_achievement: { code: 2, label: 'Strong standard' },
+        rc_attendance_behaviour: { code: 4, label: 'Needs attention' },
+      },
+    }),
+  },
+};
+
+describe('CompareOfsted', () => {
+  it('renders the three regimes without inventing an overall grade for report cards', () => {
+    render(<CompareOfsted schools={schools} data={data} />);
+
+    expect(screen.getByText('Outstanding')).toBeInTheDocument();
+    // Carried-forward grade is shown but marked as such
+    expect(screen.getByText('Good')).toBeInTheDocument();
+    expect(screen.getByText(/carried forward/i)).toBeInTheDocument();
+    // Report card: label present, no overall-grade badge for that school
+    expect(screen.getByText('Report card')).toBeInTheDocument();
+    expect(screen.getByText(/no overall grade/i)).toBeInTheDocument();
+  });
+
+  it('uses one chip-list grammar for both regimes in judgement detail', () => {
+    render(<CompareOfsted schools={schools} data={data} />);
+    // report-card area chip
+    expect(screen.getByText('Attendance & behaviour')).toBeInTheDocument();
+    expect(screen.getByText('Needs attention')).toBeInTheDocument();
+    // graded school without published subgrades → honest dataset statement
+    expect(
+      screen.getAllByText(/We don't hold area-by-area detail/i).length,
+    ).toBeGreaterThanOrEqual(1);
+  });
+
+  it('shows the mixed-regime comparability note only when regimes differ', () => {
+    render(<CompareOfsted schools={schools} data={data} />);
+    expect(screen.getByText(/aren't directly comparable/i)).toBeInTheDocument();
+  });
+
+  it('links every school to its Ofsted page', () => {
+    render(<CompareOfsted schools={schools} data={data} />);
+    const links = screen.getAllByRole('link', { name: /Ofsted page/i });
+    expect(links).toHaveLength(3);
+    expect(links[0]).toHaveAttribute('href', 'https://reports.ofsted.gov.uk/provider/21/1');
+  });
+
+  it('renders a per-measure mobile tag with the short school name', () => {
+    render(<CompareOfsted schools={schools} data={data} />);
+    // Each measure repeats the schools, so the short name ("Graded" from
+    // "Graded School") appears once per measure (4) via the cell tag.
+    expect(screen.getAllByText('Graded').length).toBe(4);
+    expect(screen.getAllByText('Card').length).toBe(4);
+  });
+});
@@ -0,0 +1,82 @@
+/**
+ * Regression: on refresh, the compare page must show the SSR-rendered data.
+ *
+ * The basket hydrates from the URL a beat after mount (selectedSchools is
+ * empty for the first render), so the fetch effect must not blank the
+ * SSR payload during that window — and must not refetch data the server
+ * already provided.
+ */
+
+import { render, screen, waitFor } from '@testing-library/react';
+
+import { ComparisonView } from '@/components/ComparisonView';
+import { ComparisonProvider } from '@/context/ComparisonProvider';
+import type { ComparisonData, School } from '@/lib/types';
+
+const fetchComparison = jest.fn();
+jest.mock('@/lib/api', () => ({
+  fetchComparison: (...args: unknown[]) => fetchComparison(...args),
+}));
+jest.mock('@/lib/analytics', () => ({ track: jest.fn() }));
+
+function school(urn: number, name: string): School {
+  return {
+    urn,
+    school_name: name,
+    local_authority: 'Testshire',
+    school_type: 'Community school',
+    rwm_expected_pct: 80,
+    phase: 'Primary',
+  } as School;
+}
+
+function data(urn: number, name: string): ComparisonData {
+  return {
+    school_info: school(urn, name),
+    yearly_data: [{ year: 202425, rwm_expected_pct: 80 }] as ComparisonData['yearly_data'],
+    ofsted: null,
+    census: null,
+    admissions: null,
+    admissions_history: [],
+    deprivation: null,
+  };
+}
+
+const INITIAL_DATA = {
+  '100': data(100, 'Alpha Primary'),
+  '200': data(200, 'Beta Primary'),
+};
+
+beforeEach(() => {
+  fetchComparison.mockReset();
+});
+
+test('renders SSR data on refresh without wiping it or refetching', async () => {
+  render(
+    <ComparisonProvider>
+      <ComparisonView
+        initialData={INITIAL_DATA}
+        initialNationalAverages={{
+          year: 202425,
+          primary: { rwm_expected_pct: 62 },
+          secondary: {},
+          by_year: [],
+        }}
+        initialBenchmarks={undefined}
+        initialUrns={[100, 200]}
+        metrics={[]}
+        selectedMetric="rwm_expected_pct"
+      />
+    </ComparisonProvider>,
+  );
+
+  // Both SSR-provided schools appear (data was not blanked during hydration)
+  await waitFor(() => {
+    expect(screen.getAllByText('Alpha Primary').length).toBeGreaterThan(0);
+  });
+  expect(screen.getAllByText('Beta Primary').length).toBeGreaterThan(0);
+  expect(screen.getByRole('heading', { name: 'At a glance' })).toBeInTheDocument();
+
+  // …and the client never refetched data the server already rendered.
+  expect(fetchComparison).not.toHaveBeenCalled();
+});
@@ -0,0 +1,48 @@
+import { render, screen } from '@testing-library/react';
+
+import { DotStrip } from '@/components/DotStrip';
+
+describe('DotStrip', () => {
+  it('enumerates anchor and school values in the aria-label', () => {
+    render(
+      <DotStrip
+        label="Reading"
+        values={[91, 92, 87]}
+        schoolNames={['Barclay', 'Elmhurst', 'Plumcroft']}
+        anchor={{ value: 75, label: 'England 75%' }}
+      />,
+    );
+    const strip = screen.getByRole('img');
+    expect(strip).toHaveAccessibleName(
+      'Reading: England 75%, Barclay 91%, Elmhurst 92%, Plumcroft 87%',
+    );
+  });
+
+  it('renders the anchor tick when provided and not otherwise', () => {
+    const { rerender } = render(
+      <DotStrip
+        label="Reading"
+        values={[91]}
+        schoolNames={['Barclay']}
+        anchor={{ value: 75, label: 'England 75%' }}
+      />,
+    );
+    expect(screen.getByText('England 75%')).toBeInTheDocument();
+
+    rerender(
+      <DotStrip label="Science" values={[95]} schoolNames={['Barclay']} anchor={null} />,
+    );
+    expect(screen.queryByText(/England/)).not.toBeInTheDocument();
+  });
+
+  it('skips schools without a value', () => {
+    render(
+      <DotStrip
+        label="Maths"
+        values={[91, null]}
+        schoolNames={['Barclay', 'Elmhurst']}
+      />,
+    );
+    expect(screen.getByRole('img')).toHaveAccessibleName('Maths: Barclay 91%');
+  });
+});
@@ -0,0 +1,67 @@
+/**
+ * SecondarySchoolRow — sixth-form tag must come from the GIAS
+ * has_sixth_form flag, not the age_range-contains-"18" heuristic.
+ */
+
+import '@testing-library/jest-dom';
+import { render, screen } from '@testing-library/react';
+import { SecondarySchoolRow } from '@/components/SecondarySchoolRow';
+import type { School } from '@/lib/types';
+
+const base = {
+  urn: 100002,
+  school_name: 'Beta Sixth Form College',
+  local_authority: 'Testshire',
+  school_type: 'Academy',
+  phase: 'Secondary',
+  gender: 'Mixed',
+  attainment_8_score: 50.0,
+} as unknown as School;
+
+describe('SecondarySchoolRow sixth-form tag', () => {
+  it('shows the tag for a 16-19 college with the GIAS flag set', () => {
+    render(
+      <SecondarySchoolRow
+        school={{ ...base, age_range: '16-19', has_sixth_form: true }}
+      />,
+    );
+    expect(screen.getByText('Sixth form')).toBeInTheDocument();
+  });
+
+  it('hides the tag for an 11-18 school without a registered sixth form', () => {
+    render(
+      <SecondarySchoolRow
+        school={{ ...base, age_range: '11-18', has_sixth_form: false }}
+      />,
+    );
+    expect(screen.queryByText('Sixth form')).not.toBeInTheDocument();
+  });
+
+  it('hides the tag when the flag is missing (pipeline not yet re-run)', () => {
+    render(
+      <SecondarySchoolRow school={{ ...base, age_range: '11-18' }} />,
+    );
+    expect(screen.queryByText('Sixth form')).not.toBeInTheDocument();
+  });
+});
+
+describe('SecondarySchoolRow proposed-to-close tag', () => {
+  it('shows the tag when GIAS status is "Open, but proposed to close"', () => {
+    render(
+      <SecondarySchoolRow
+        school={{ ...base, status: 'Open, but proposed to close' }}
+      />,
+    );
+    expect(screen.getByText(/Proposed to close/)).toBeInTheDocument();
+  });
+
+  it('hides the tag for a plain open school', () => {
+    render(<SecondarySchoolRow school={{ ...base, status: 'Open' }} />);
+    expect(screen.queryByText(/Proposed to close/)).not.toBeInTheDocument();
+  });
+
+  it('hides the tag when status is missing', () => {
+    render(<SecondarySchoolRow school={base} />);
+    expect(screen.queryByText(/Proposed to close/)).not.toBeInTheDocument();
+  });
+});
@@ -0,0 +1,84 @@
+/**
+ * buildCompareChart: every selected school must produce a rendered series
+ * (regression guard for the production bug where a third school's line
+ * vanished), the x-axis must include cancelled/unpublished years as real
+ * gaps (never compressing time), and the England overlay renders dashed
+ * with no gap-bridging.
+ */
+
+import { buildCompareChart, fillAcademicYears } from '@/lib/compareChartData';
+import type { ComparisonData } from '@/lib/types';
+
+function school(urn: number, years: Array<[number, number | null]>): ComparisonData {
+  return {
+    school_info: { urn, school_name: `School ${urn}` } as ComparisonData['school_info'],
+    yearly_data: years.map(([year, v]) => ({ year, rwm_expected_pct: v })) as ComparisonData['yearly_data'],
+  };
+}
+
+const THREE_SCHOOLS = {
+  '1': school(1, [[201819, 87], [202223, 87], [202425, 87]]),
+  '2': school(2, [[201819, 88], [202223, 88], [202425, 92]]),
+  '3': school(3, [[201819, 69], [202223, 62], [202425, 79]]),
+};
+
+const SCHOOL_LIST = [1, 2, 3].map((urn) => ({ urn, school_name: `School ${urn}` }));
+
+describe('fillAcademicYears', () => {
+  it('fills every academic year between min and max', () => {
+    expect(fillAcademicYears([201819, 202223])).toEqual([
+      201819, 201920, 202021, 202122, 202223,
+    ]);
+  });
+});
+
+describe('buildCompareChart', () => {
+  it('renders one series per selected school — none silently dropped', () => {
+    const chart = buildCompareChart(THREE_SCHOOLS, SCHOOL_LIST, 'rwm_expected_pct');
+    expect(chart.schoolDatasets).toHaveLength(3);
+    for (const ds of chart.schoolDatasets) {
+      expect(ds.data.some((v) => v != null)).toBe(true);
+    }
+  });
+
+  it('handles float years from the API (202425.0 style)', () => {
+    const floaty = {
+      '1': school(1, [[201819.0 as number, 80], [202425.0 as number, 85]]),
+    };
+    const chart = buildCompareChart(floaty, [SCHOOL_LIST[0]], 'rwm_expected_pct');
+    expect(chart.schoolDatasets[0].data.filter((v) => v != null)).toHaveLength(2);
+  });
+
+  it('includes cancelled/unpublished years as null gaps, not compressed time', () => {
+    const chart = buildCompareChart(THREE_SCHOOLS, SCHOOL_LIST, 'rwm_expected_pct');
+    expect(chart.years).toContain(201920);
+    expect(chart.years).toContain(202122);
+    const idx = chart.years.indexOf(202021);
+    expect(chart.schoolDatasets[0].data[idx]).toBeNull();
+  });
+
+  it('adds a dashed England overlay when national data is supplied', () => {
+    const chart = buildCompareChart(THREE_SCHOOLS, SCHOOL_LIST, 'rwm_expected_pct', {
+      201819: 64.9,
+      202122: 58.7,
+      202223: 59.5,
+      202425: 62.1,
+    });
+    expect(chart.englandDataset).not.toBeNull();
+    const eng = chart.englandDataset!;
+    expect(eng.label).toBe('England average');
+    expect(eng.borderDash).toEqual([5, 4]);
+    expect(eng.spanGaps).toBe(false);
+    // England has a value for 2021/22 even though schools do not
+    expect(eng.data[chart.years.indexOf(202122)]).toBe(58.7);
+  });
+
+  it('flags the unpublished 2021/22 school-level year when England has data but schools do not', () => {
+    const withNational = buildCompareChart(THREE_SCHOOLS, SCHOOL_LIST, 'rwm_expected_pct', {
+      202122: 58.7,
+    });
+    expect(withNational.showUnpublished202122Note).toBe(true);
+    const withoutNational = buildCompareChart(THREE_SCHOOLS, SCHOOL_LIST, 'rwm_expected_pct');
+    expect(withoutNational.showUnpublished202122Note).toBe(false);
+  });
+});
@@ -0,0 +1,266 @@
+/**
+ * compareLogic encodes the expert-reviewed comprehension rules for the
+ * compare screen: report-card summarisation (safeguarding never counted),
+ * three-regime Ofsted display, one consistent admissions chip metric,
+ * CI-based progress banding, verdict chips and dot-strip geometry.
+ */
+
+import {
+  OFSTED_LEGACY_GRADES,
+  ofstedDisplay,
+  progressBand,
+  rcAreaLabel,
+  stripPositions,
+  summariseAdmissions,
+  summariseReportCard,
+  verdict,
+} from '@/lib/compareLogic';
+import type { OfstedInspection, SchoolAdmissions } from '@/lib/types';
+
+function ofsted(partial: Partial<OfstedInspection>): OfstedInspection {
+  return {
+    framework: null,
+    inspection_date: null,
+    inspection_type: null,
+    overall_effectiveness: null,
+    quality_of_education: null,
+    behaviour_attitudes: null,
+    personal_development: null,
+    leadership_management: null,
+    early_years_provision: null,
+    previous_overall: null,
+    rc_safeguarding_met: null,
+    rc_inclusion: null,
+    rc_curriculum_teaching: null,
+    rc_achievement: null,
+    rc_attendance_behaviour: null,
+    rc_personal_development: null,
+    rc_leadership_governance: null,
+    rc_early_years: null,
+    rc_sixth_form: null,
+    ...partial,
+  };
+}
+
+const REPORT_CARD = {
+  rc_achievement: { code: 2, label: 'Strong standard' },
+  rc_curriculum_teaching: { code: 2, label: 'Strong standard' },
+  rc_personal_development: { code: 2, label: 'Strong standard' },
+  rc_leadership_governance: { code: 2, label: 'Strong standard' },
+  rc_inclusion: { code: 3, label: 'Expected standard' },
+  rc_early_years: { code: 3, label: 'Expected standard' },
+  rc_attendance_behaviour: { code: 4, label: 'Needs attention' },
+};
+
+describe('summariseReportCard', () => {
+  it('counts graded areas best-first and NAMES problem areas', () => {
+    const s = summariseReportCard(
+      ofsted({ report_card: REPORT_CARD, rc_safeguarding_met: true }),
+    );
+    expect(s.counts).toEqual([
+      { label: 'Strong standard', count: 4 },
+      { label: 'Expected standard', count: 2 },
+    ]);
+    expect(s.problems).toEqual([
+      { areaLabel: 'Attendance & behaviour', label: 'Needs attention' },
+    ]);
+    expect(s.safeguarding).toBe('met');
+    expect(s.allClear).toBe(false);
+  });
+
+  it('never counts safeguarding as a graded area', () => {
+    const s = summariseReportCard(
+      ofsted({
+        report_card: { rc_achievement: { code: 3, label: 'Expected standard' } },
+        rc_safeguarding_met: true,
+      }),
+    );
+    const total = s.counts.reduce((n, c) => n + c.count, 0);
+    expect(total).toBe(1);
+  });
+
+  it('is allClear when everything is Expected standard or better and safeguarding met', () => {
+    const s = summariseReportCard(
+      ofsted({
+        report_card: {
+          rc_achievement: { code: 3, label: 'Expected standard' },
+          rc_inclusion: { code: 1, label: 'Exceptional' },
+        },
+        rc_safeguarding_met: true,
+      }),
+    );
+    expect(s.allClear).toBe(true);
+    expect(s.counts[0]).toEqual({ label: 'Exceptional', count: 1 });
+  });
+
+  it('passes labels through from the API — never invents wording', () => {
+    const s = summariseReportCard(
+      ofsted({ report_card: { rc_inclusion: { code: 4, label: 'Needs attention' } } }),
+    );
+    expect(JSON.stringify(s)).not.toContain('Attention needed');
+  });
+});
+
+describe('ofstedDisplay', () => {
+  it('prefers the report card over any legacy grade', () => {
+    const d = ofstedDisplay(
+      ofsted({ overall_effectiveness: 2, report_card: REPORT_CARD }),
+    );
+    expect(d.kind).toBe('report_card');
+  });
+
+  it('distinguishes graded from carried-forward grades', () => {
+    const graded = ofstedDisplay(
+      ofsted({ overall_effectiveness: 1, grade_source: 'graded' }),
+    );
+    expect(graded).toMatchObject({ kind: 'graded', gradeLabel: 'Outstanding', carriedForward: false });
+
+    const carried = ofstedDisplay(
+      ofsted({ overall_effectiveness: 2, grade_source: 'ungraded_carried_forward' }),
+    );
+    expect(carried).toMatchObject({ kind: 'carried_forward', gradeLabel: 'Good', carriedForward: true });
+  });
+
+  it('handles missing data', () => {
+    expect(ofstedDisplay(null).kind).toBe('none');
+    expect(ofstedDisplay(ofsted({})).kind).toBe('none');
+  });
+
+  it('identifies transitional inspections without overall grades', () => {
+    const transitional = ofstedDisplay(
+      ofsted({ overall_effectiveness: null, inspection_date: '2024-11-05' }),
+    );
+    expect(transitional.kind).toBe('transitional');
+  });
+
+  it('uses the four legacy grade words', () => {
+    expect(OFSTED_LEGACY_GRADES).toEqual({
+      1: 'Outstanding',
+      2: 'Good',
+      3: 'Requires improvement',
+      4: 'Inadequate',
+    });
+  });
+});
+
+describe('rcAreaLabel', () => {
+  it('maps rc keys to the mockups’ area labels', () => {
+    expect(rcAreaLabel('rc_attendance_behaviour')).toBe('Attendance & behaviour');
+    expect(rcAreaLabel('rc_curriculum_teaching')).toBe('Curriculum & teaching');
+    expect(rcAreaLabel('rc_leadership_governance')).toBe('Leadership & governance');
+  });
+});
+
+describe('summariseAdmissions', () => {
+  function admissions(partial: Partial<SchoolAdmissions>): SchoolAdmissions {
+    return {
+      year: 202627,
+      places_offered: null,
+      total_applications: null,
+      first_preference_offer_pct: null,
+      oversubscribed: null,
+      ...partial,
+    };
+  }
+
+  it('97% → good chip with the mockup wording', () => {
+    const s = summariseAdmissions(
+      admissions({ first_preference_offer_pct: 96.98, total_applications: 457, places_offered: 180 }),
+    );
+    expect(s.chip).toEqual({ tone: 'good', text: '97% of first choices offered' });
+    expect(s.interest).toBe('Named on 457 forms · 180 places');
+  });
+
+  it('73% → warn chip "Over 1 in 4 first choices missed out"', () => {
+    const s = summariseAdmissions(admissions({ first_preference_offer_pct: 73.4 }));
+    expect(s.chip).toEqual({ tone: 'warn', text: 'Over 1 in 4 first choices missed out' });
+  });
+
+  it('100% → "All first choices offered"', () => {
+    const s = summariseAdmissions(admissions({ first_preference_offer_pct: 100 }));
+    expect(s.chip).toEqual({ tone: 'good', text: 'All first choices offered' });
+  });
+
+  it('no data → null chip and interest', () => {
+    const s = summariseAdmissions(null);
+    expect(s.chip).toBeNull();
+    expect(s.interest).toBeNull();
+  });
+});
+
+describe('progressBand', () => {
+  it('CI entirely above zero → above', () => {
+    expect(progressBand(1.2, 0.4, 2.0)).toBe('above');
+  });
+  it('CI entirely below zero → below', () => {
+    expect(progressBand(-1.2, -2.0, -0.4)).toBe('below');
+  });
+  it('CI straddling zero → average', () => {
+    expect(progressBand(0.3, -0.5, 1.1)).toBe('average');
+  });
+  it('missing CI → null (no naive thresholding)', () => {
+    expect(progressBand(1.2, null, null)).toBeNull();
+    expect(progressBand(null, null, null)).toBeNull();
+  });
+});
+
+describe('verdict', () => {
+  it('above / close / below with a 2pp tolerance', () => {
+    expect(verdict(87, 62)).toBe('above');
+    expect(verdict(61, 62)).toBe('close');
+    expect(verdict(40, 62)).toBe('below');
+  });
+});
+
+describe('stripPositions', () => {
+  it('maps a custom domain', () => {
+    const pts = stripPositions([106], 100, 120);
+    expect(pts[0].pos).toBe(30);
+  });
+
+  it('flips a colliding label above', () => {
+    const pts = stripPositions([91, 92], 0, 100);
+    const sorted = [...pts].sort((a, b) => a.value - b.value);
+    expect(sorted[0].labelAbove).toBe(false);
+    expect(sorted[1].labelAbove).toBe(true);
+  });
+
+  it('skips nulls and keeps school indices', () => {
+    const pts = stripPositions([50, null, 70], 0, 100);
+    expect(pts).toHaveLength(2);
+    expect(pts.map((p) => p.schoolIndex)).toEqual([0, 2]);
+  });
+
+  it('clamps out-of-domain values', () => {
+    const pts = stripPositions([95], 100, 120);
+    expect(pts[0].pos).toBe(0);
+  });
+});
+
+describe('latestValues', () => {
+  const data = {
+    '1': {
+      yearly_data: [
+        { year: 202324, rwm_expected_pct: 75 },
+        { year: 202425, rwm_expected_pct: 87 },
+      ],
+    },
+    '2': {
+      yearly_data: [
+        { year: 202324, rwm_expected_pct: 82 },
+        { year: 202425, rwm_expected_pct: null },
+      ],
+    },
+  };
+
+  it('takes the latest non-null value per school in urn order', async () => {
+    const { latestValues } = await import('@/lib/compareLogic');
+    expect(latestValues(data, [1, 2], 'rwm_expected_pct')).toEqual([87, 82]);
+  });
+
+  it('returns null for unknown schools and metrics', async () => {
+    const { latestValues } = await import('@/lib/compareLogic');
+    expect(latestValues(data, [3], 'rwm_expected_pct')).toEqual([null]);
+    expect(latestValues(data, [1], 'nope')).toEqual([null]);
+  });
+});
@@ -10,6 +10,7 @@ import {
  debounce,
  buildOfstedListBadge,
  metricKind,
+  shortName,
  computeYBounds,
 } from '@/lib/utils';

@@ -212,3 +213,28 @@ describe('computeYBounds', () => {
    expect(computeYBounds([], 'progress')).toEqual({});
  });
 });
+
+describe('isProposedToClose', () => {
+  const { isProposedToClose } = require('@/lib/utils');
+
+  it('is true only for the exact GIAS proposed-to-close status', () => {
+    expect(isProposedToClose({ status: 'Open, but proposed to close' })).toBe(true);
+    expect(isProposedToClose({ status: 'Open' })).toBe(false);
+    expect(isProposedToClose({ status: null })).toBe(false);
+    expect(isProposedToClose({})).toBe(false);
+  });
+});
+
+describe('shortName', () => {
+  it('drops the trailing establishment-type words', () => {
+    expect(shortName('Barclay Primary School')).toBe('Barclay');
+    expect(shortName('Elmhurst Primary School')).toBe('Elmhurst');
+    expect(shortName("St Mary's Catholic Primary School")).toBe("St Mary's");
+    expect(shortName('Riverside Community Junior School')).toBe('Riverside');
+  });
+
+  it('keeps a name that carries no type suffix, capping very long ones', () => {
+    expect(shortName('Beaver Road')).toBe('Beaver Road');
+    expect(shortName('A'.repeat(30), 10)).toBe('AAAAAAAAA…');
+  });
+});
@@ -16,8 +16,10 @@ interface ComparePageProps {

 export const metadata: Metadata = {
  title: 'Compare Schools',
-  description: 'Compare KS2 performance across multiple primary schools in England',
-  keywords: 'school comparison, compare schools, KS2 comparison, primary school performance',
+  description:
+    'Compare schools in England side by side — Ofsted inspections, KS2 and GCSE results against the England average, admissions odds and school community.',
+  keywords:
+    'school comparison, compare schools, Ofsted comparison, school admissions, KS2 comparison, primary school performance',
 };

 // Dynamic via searchParams; remove force-dynamic so internal data fetches
@@ -30,26 +32,24 @@ export default async function ComparePage({ searchParams }: ComparePageProps) {
  const selectedMetric = metricParam || 'rwm_expected_pct';

  try {
-    // Fetch comparison data if URNs provided
-    let comparisonData = null;
-    if (urns.length > 0) {
-      try {
-        const response = await fetchComparison(urnsParam!);
-        comparisonData = response.comparison;
-      } catch (error) {
+    // Fetch comparison + metrics in parallel — they are independent.
+    const [comparisonResponse, metricsResponse] = await Promise.all([
+      urns.length > 0
+        ? fetchComparison(urnsParam!).catch((error) => {
            console.error('Failed to fetch comparison:', error);
-      }
-    }
+            return null;
+          })
+        : Promise.resolve(null),
+      fetchMetrics(),
+    ]);

-    // Fetch available metrics
-    const metricsResponse = await fetchMetrics();
-
-    // Metrics is already an array
    const metricsArray = metricsResponse?.metrics || [];

    return (
      <ComparisonView
-        initialData={comparisonData}
+        initialData={comparisonResponse?.comparison ?? null}
+        initialNationalAverages={comparisonResponse?.national_averages}
+        initialBenchmarks={comparisonResponse?.benchmarks}
        initialUrns={urns}
        metrics={metricsArray}
        selectedMetric={selectedMetric}
@@ -21,8 +21,10 @@

@media (max-width: 640px) {
    .chips {
-        display: flex;
-        flex-wrap: wrap;
+        /* Two chips per row so long school names don't crowd into a single
+           line; each chip fills its column and truncates with an ellipsis. */
+        display: grid;
+        grid-template-columns: 1fr 1fr;
        gap: 6px;
        padding-bottom: 8px;
    }
@@ -31,8 +33,8 @@
        display: inline-flex;
        align-items: center;
        gap: 6px;
-        min-height: 44px;
-        max-width: 100%;
+        min-height: 40px;
+        min-width: 0;
        padding: 4px 10px;
        border: 1px solid rgba(0, 0, 0, .12);
        border-radius: 999px;
@@ -58,6 +60,14 @@
        overflow: hidden;
        text-overflow: ellipsis;
        white-space: nowrap;
-        max-width: 9rem;
+        /* min-width:0 lets the name shrink inside the grid cell so the
+           ellipsis kicks in instead of overflowing. */
+        min-width: 0;
    }
 }
+
+.chartNote {
+  font-size: 0.78rem;
+  color: var(--text-muted);
+  margin: 0.5rem 0 0;
+}
@@ -15,6 +15,7 @@ import { useEffect, useState } from 'react';
 import { Line } from 'react-chartjs-2';
 import { ChartOptions, ChartDataset, PointStyle } from 'chart.js';
 import '@/lib/chartSetup';
+import { buildCompareChart } from '@/lib/compareChartData';
 import type { ComparisonData } from '@/lib/types';
 import {
  CHART_COLORS,
@@ -34,13 +35,16 @@ interface ComparisonChartProps {
  schools: Array<{ urn: number; school_name: string }>;
  metric: string;
  metricLabel: string;
+  /** Official England figure per academic year for this metric — renders a
+   * dashed grey reference line when provided. */
+  nationalByYear?: Record<number, number | null | undefined>;
 }

 // One shape per basket slot (MAX_SCHOOLS = 5) — secondary encoding so
 // converging lines stay tellable apart without relying on hue alone.
 const POINT_STYLES: PointStyle[] = ['circle', 'triangle', 'rect', 'rectRot', 'star'];

-export function ComparisonChart({ comparisonData, schools, metric, metricLabel }: ComparisonChartProps) {
+export function ComparisonChart({ comparisonData, schools, metric, metricLabel, nationalByYear }: ComparisonChartProps) {
  const isMobile = useIsMobile();
  const [focusedUrn, setFocusedUrn] = useState<number | null>(null);

@@ -54,34 +58,48 @@ export function ComparisonChart({ comparisonData, schools, metric, metricLabel }
    return <div>No data available</div>;
  }

-  // Union of years across all schools — coverage differs between them.
-  const years = [
-    ...new Set(schools.flatMap((s) => comparisonData[String(s.urn)]?.yearly_data.map((d) => d.year) ?? [])),
-  ].sort((a, b) => a - b);
+  // Pure, tested series construction: union of years with cancelled /
+  // unpublished years kept as real gaps, plus the England overlay.
+  const built = buildCompareChart(comparisonData, schools, metric, nationalByYear);
+  const { years } = built;

-  const datasets: ChartDataset<'line'>[] = schools.map((school, index) => {
-    const data = comparisonData[String(school.urn)];
-    const color = CHART_COLORS[index % CHART_COLORS.length];
+  const datasets: ChartDataset<'line'>[] = built.schoolDatasets.map((series) => {
+    const school = schools[series.schoolIndex];
+    const color = CHART_COLORS[series.schoolIndex % CHART_COLORS.length];
    const dimmed = focusedUrn !== null && focusedUrn !== school.urn;

    return {
-      label: school.school_name,
-      data: years.map((year) => {
-        const yearData = data?.yearly_data.find((d) => d.year === year);
-        if (!yearData) return null;
-        return yearData[metric as keyof typeof yearData] as number | null;
-      }),
+      label: series.label,
+      data: series.data,
      borderColor: dimmed ? rgbToRgba(color, 0.2) : color,
      backgroundColor: dimmed ? 'transparent' : rgbToRgba(color, 0.1),
      borderWidth: focusedUrn === school.urn ? 3 : dimmed ? 1.5 : 2,
-      pointStyle: POINT_STYLES[index % POINT_STYLES.length],
+      pointStyle: POINT_STYLES[series.schoolIndex % POINT_STYLES.length],
      pointRadius: dimmed ? 2 : isMobile ? 3 : 4,
      pointHoverRadius: isMobile ? 5 : 6,
      tension: 0.3,
-      spanGaps: true,
+      // Never bridge missing years — gaps are information (COVID
+      // cancellations, unpublished 2021/22, schools that opened later).
+      spanGaps: false,
    };
  });

+  if (built.englandDataset) {
+    datasets.push({
+      label: built.englandDataset.label,
+      data: built.englandDataset.data,
+      borderColor: 'rgba(109, 104, 95, 0.9)',
+      backgroundColor: 'transparent',
+      borderWidth: 1.5,
+      borderDash: built.englandDataset.borderDash,
+      pointStyle: 'line',
+      pointRadius: 0,
+      pointHoverRadius: 4,
+      tension: 0,
+      spanGaps: false,
+    });
+  }
+
  const chartData = {
    labels: years.map(formatAcademicYear),
    datasets,
@@ -222,6 +240,12 @@ export function ComparisonChart({ comparisonData, schools, metric, metricLabel }
      <div className={styles.canvasBox}>
        <Line data={chartData} options={options} aria-label={`${metricLabel} comparison chart`} />
      </div>
+      {built.showUnpublished202122Note && (
+        <p className={styles.chartNote}>
+          No national tests were held in 2019/20 and 2020/21 (COVID), and DfE didn&apos;t publish
+          school-level figures for 2021/22 — the England average is shown for that year.
+        </p>
+      )}
    </div>
  );
 }
@@ -28,8 +28,15 @@
  color: var(--text-secondary, #5c564d);
  margin: 0;
  line-height: 1.6;
+  max-width: 60ch;
 }

+.headerActions {
+  display: flex;
+  gap: 0.75rem;
+  align-items: center;
+  flex-wrap: wrap;
+}

 /* Phase Tabs */
 .phaseTabs {
@@ -72,408 +79,136 @@
  background: var(--accent-coral-darker, #9c3f26);
 }

-/* Metric Selector */
-.metricSelector {
-  background: var(--bg-card, white);
-  border: 1px solid var(--border-color, #e5dfd5);
-  border-radius: 12px;
-  padding: 1.5rem;
-  margin-bottom: 2rem;
+/* Sticky school bar — column identity while scrolling; horizontal scroll on
+   narrow screens. Offset by the sticky site header's height (Navigation is
+   position: sticky, top: 0) so this bar pins just below it instead of
+   sliding underneath and being hidden. Header ≈ 65px desktop / 57px mobile. */
+.schoolBar {
+  position: sticky;
+  top: 65px;
+  z-index: 10;
+  background: var(--bg-primary, #faf7f2);
  display: flex;
-  align-items: center;
-  flex-wrap: wrap;
-  gap: 1rem;
-  box-shadow: var(--shadow-soft, 0 2px 8px rgba(26, 22, 18, 0.06));
-}
-
-.metricLabel {
-  font-size: 0.9375rem;
-  font-weight: 600;
-  color: var(--text-primary, #1a1612);
-  white-space: nowrap;
-}
-
-.metricSelect {
-  flex: 1;
-  max-width: 400px;
-  padding: 0.625rem 1rem;
-  font-size: 0.9375rem;
-  border: 1px solid var(--border-color, #e5dfd5);
-  border-radius: 8px;
-  background: var(--bg-card, white);
-  color: var(--text-primary, #1a1612);
-  cursor: pointer;
-  transition: all 0.2s ease;
-}
-
-.metricSelect:hover {
-  border-color: var(--accent-coral, #e07256);
-}
-
-.metricSelect:focus {
-  outline: none;
-  border-color: var(--accent-coral, #e07256);
-  box-shadow: 0 0 0 3px var(--accent-coral-bg);
-}
-
-.metricSelect optgroup {
-  font-weight: 700;
-  color: var(--text-primary, #1a1612);
-  background: var(--bg-secondary, #f3ede4);
-  padding: 0.5rem 0;
-}
-
-.metricSelect option {
-  font-weight: 400;
-  color: var(--text-secondary, #5c564d);
-  padding: 0.375rem 1rem;
-}
-
-/* Schools Section */
-.schoolsSection {
-  margin-bottom: 2rem;
-}
-
-.schoolsGrid {
-  display: grid;
-  grid-template-columns: repeat(auto-fill, minmax(280px, 1fr));
-  gap: 1.5rem;
-}
-
-.schoolCard {
-  background: var(--bg-card, white);
-  border: 1px solid var(--border-color, #e5dfd5);
-  border-left: 3px solid var(--accent-teal, #2d7d7d);
-  border-radius: 12px;
-  padding: 1.5rem;
-  position: relative;
-  box-shadow: var(--shadow-soft, 0 2px 8px rgba(26, 22, 18, 0.06));
-  transition: all 0.3s ease;
-  display: flex;
-  flex-direction: column;
-}
-
-.schoolCard:hover {
-  box-shadow: var(--shadow-medium, 0 4px 20px rgba(26, 22, 18, 0.1));
-  transform: translateY(-2px);
-}
-
-.removeButton {
-  position: absolute;
-  top: 0.75rem;
-  right: 0.75rem;
-  width: 28px;
-  height: 28px;
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  background: var(--accent-coral, #e07256);
-  color: white;
-  border: none;
-  border-radius: 50%;
-  font-size: 1.25rem;
-  line-height: 1;
-  cursor: pointer;
-  transition: all 0.2s ease;
-}
-
-.removeButton:hover {
-  background: var(--accent-coral-dark, #c45a3f);
-  transform: scale(1.1);
-}
-
-.schoolName {
-  font-size: 1.125rem;
-  font-weight: 600;
-  margin-bottom: 0.75rem;
-  padding-right: 2rem;
-  line-height: 1.3;
-  font-family: var(--font-playfair), 'Playfair Display', serif;
-}
-
-.schoolName a {
-  color: var(--text-primary, #1a1612);
-  text-decoration: none;
-  transition: color 0.2s ease;
-}
-
-.schoolName a:hover {
-  color: var(--accent-coral-dark, #b04a2e);
-}
-
-.schoolMeta {
-  display: flex;
-  flex-direction: column;
-  gap: 0.5rem;
-  margin-bottom: 1rem;
-  flex: 1;
-}
-
-.metaItem {
-  font-size: 0.875rem;
-  color: var(--text-secondary, #5c564d);
-  display: flex;
-  align-items: center;
-  gap: 0.25rem;
-}
-
-.latestValue {
-  margin-top: auto;
-  padding-top: 1rem;
-  border-top: 1px solid var(--border-color, #e5dfd5);
-  text-align: center;
-  background: var(--bg-secondary, #f3ede4);
-  margin-left: -1.5rem;
-  margin-right: -1.5rem;
-  margin-bottom: -1.5rem;
-  padding: 1.25rem 1.5rem;
-  border-radius: 0 0 12px 9px;
-}
-
-.latestLabel {
-  font-size: 0.75rem;
-  color: var(--text-muted, #8a847a);
-  margin-bottom: 0.25rem;
-  text-transform: uppercase;
-  letter-spacing: 0.05em;
-}
-
-.latestNumber {
-  font-size: 1.75rem;
-  font-weight: 700;
-  color: var(--accent-teal, #2d7d7d);
-}
-
-/* Chart Section */
-.chartSection {
-  background: var(--bg-card, white);
-  border: 1px solid var(--border-color, #e5dfd5);
-  border-radius: 12px;
-  padding: 2rem;
-  margin-bottom: 2rem;
-  box-shadow: var(--shadow-soft, 0 2px 8px rgba(26, 22, 18, 0.06));
-}
-
-.sectionTitle {
-  font-size: 1.5rem;
-  font-weight: 600;
-  color: var(--text-primary, #1a1612);
-  margin-bottom: 1.5rem;
-  padding-bottom: 0.75rem;
-  border-bottom: 2px solid var(--border-color, #e5dfd5);
-  font-family: var(--font-playfair), 'Playfair Display', serif;
-  display: flex;
-  align-items: center;
-  gap: 0.5rem;
-}
-
-.sectionTitle::before {
-  content: '';
-  display: inline-block;
-  width: 4px;
-  height: 1em;
-  background: var(--accent-coral, #e07256);
-  border-radius: 2px;
-}
-
-.chartContainer {
-  width: 100%;
-  height: 400px;
-  position: relative;
-}
-
-.loadingMessage {
-  text-align: center;
-  padding: 3rem;
-  color: var(--text-secondary, #5c564d);
-  font-size: 1rem;
-}
-
-/* Table Section */
-.tableSection {
-  background: var(--bg-card, white);
-  border: 1px solid var(--border-color, #e5dfd5);
-  border-radius: 12px;
-  padding: 2rem;
-  margin-bottom: 2rem;
-  box-shadow: var(--shadow-soft, 0 2px 8px rgba(26, 22, 18, 0.06));
-}
-
-.tableWrapper {
+  gap: 0.75rem;
  overflow-x: auto;
-  max-width: 100%;
-  margin-top: 1rem;
+  padding: 0.75rem 0;
+  border-bottom: 1px solid var(--border-light, #e5dfd5);
  -webkit-overflow-scrolling: touch;
 }

-/* Right-edge fade so phone users see the comparison table scrolls.
-   Otherwise the wider-than-viewport table silently clips. */
-@media (max-width: 640px) {
-  .tableWrapper {
-    -webkit-mask-image: linear-gradient(to right, #000 calc(100% - 28px), transparent);
-            mask-image: linear-gradient(to right, #000 calc(100% - 28px), transparent);
-  }
+.schoolChip {
+  flex: 1 1 0;
+  min-width: 180px;
+  background: var(--bg-card, white);
+  border: 1px solid var(--border-light, #e5dfd5);
+  border-top: 3px solid var(--accent-coral, #e07256);
+  border-radius: 8px;
+  box-shadow: var(--shadow-soft, 0 2px 8px rgba(26, 22, 18, 0.06));
+  padding: 0.55rem 0.75rem;
+  display: flex;
+  gap: 0.55rem;
+  align-items: center;
 }

-.comparisonTable {
-  width: 100%;
-  border-collapse: separate;
-  border-spacing: 0;
-  font-size: 0.9375rem;
+.chipDot {
+  width: 11px;
+  height: 11px;
+  border-radius: 50%;
+  flex: none;
 }

-.comparisonTable thead {
-  background: var(--bg-secondary, #f3ede4);
+.chipText {
+  min-width: 0;
 }

-.comparisonTable th {
-  padding: 1rem;
-  text-align: left;
+.chipName {
+  display: block;
  font-weight: 600;
+  font-size: 0.92rem;
+  line-height: 1.25;
  color: var(--text-primary, #1a1612);
-  border-bottom: 2px solid var(--border-color, #e5dfd5);
-  background: var(--bg-secondary, #f3ede4);
+  text-decoration: none;
+}
+
+.chipName:hover {
+  color: var(--accent-coral-dark, #b04a2e);
+}
+
+/* Full name on desktop, short name on the compact mobile pills. */
+.chipNameShort {
+  display: none;
+}
+
+.chipMeta {
+  display: block;
+  font-size: 0.78rem;
+  color: var(--text-muted, #6d685f);
  white-space: nowrap;
-  text-transform: uppercase;
-  font-size: 0.75rem;
-  letter-spacing: 0.05em;
+  overflow: hidden;
+  text-overflow: ellipsis;
 }

-.comparisonTable td {
-  padding: 1rem;
-  border-bottom: 1px solid var(--border-color, #e5dfd5);
-  color: var(--text-secondary, #5c564d);
-  text-align: left;
-  background: var(--bg-card, white);
-}
-
-/* Sticky first column (Year) so labels remain visible while scrolling */
-.comparisonTable th:first-child,
-.comparisonTable td:first-child {
-  position: sticky;
-  left: 0;
-  z-index: 1;
-  box-shadow: 2px 0 4px -2px rgba(26, 22, 18, 0.08);
-}
-
-.comparisonTable thead th:first-child {
-  z-index: 2;
-}
-
-.comparisonTable tbody tr:hover td:first-child {
+.chipRemove {
+  margin-left: auto;
+  border: none;
  background: var(--bg-secondary, #f3ede4);
+  color: var(--text-muted, #6d685f);
+  border-radius: 50%;
+  width: 22px;
+  height: 22px;
+  cursor: pointer;
+  flex: none;
+  font-size: 0.9rem;
+  line-height: 1;
 }

-.comparisonTable tbody tr:last-child td {
-  border-bottom: none;
+.footnote {
+  font-size: 0.78rem;
+  color: var(--text-muted, #6d685f);
+  margin-top: 2.5rem;
+  border-top: 1px solid var(--border-light, #e5dfd5);
+  padding-top: 1rem;
+  max-width: 75ch;
 }

-.comparisonTable tbody tr:hover {
-  background: var(--bg-secondary, #f3ede4);
-}
+/* Mobile: the sticky school bar becomes compact, horizontally-scrollable
+   pills with short names (matching the mobile mockup) instead of full-width
+   cards whose names wrap to several lines. */
+@media (max-width: 640px) {
+  /* The mobile Navigation header is shorter (≈57px). */
+  .schoolBar {
+    top: 57px;
+  }

-.yearCell {
-  font-weight: 700;
-  color: var(--accent-gold, #c9a227);
-}
+  .schoolChip {
+    flex: 0 0 auto;
+    min-width: 0;
+    border-top-width: 2px;
+    border-radius: 999px;
+    padding: 0.35rem 0.7rem;
+    box-shadow: none;
+  }

-/* Empty State */
-.emptyState {
-  text-align: center;
-  padding: 4rem 2rem;
-  background: var(--bg-card, white);
-  border: 1px solid var(--border-color, #e5dfd5);
-  border-radius: 12px;
-}
-
-.emptyStateTitle {
-  font-size: 1.5rem;
-  font-weight: 600;
-  color: var(--text-primary, #1a1612);
-  margin-bottom: 0.5rem;
-  font-family: var(--font-playfair), 'Playfair Display', serif;
-}
-
-.emptyStateDescription {
-  font-size: 1rem;
-  color: var(--text-secondary, #5c564d);
-  max-width: 400px;
-  margin: 0 auto 1.5rem;
-}
-
-.metricDescription {
-  margin-top: 0.5rem;
+  .chipName {
    font-size: 0.85rem;
-  color: var(--text-secondary);
-  max-width: 600px;
-  flex-basis: 100%;
-  margin-top: 0.25rem;
-}
-
-.progressNote {
-  background: var(--bg-secondary);
-  border-left: 3px solid var(--accent-teal);
-  padding: 0.75rem 1rem;
-  margin: 0 0 1.5rem;
-  font-size: 0.875rem;
-  color: var(--text-secondary);
-  border-radius: 0 var(--radius-sm) var(--radius-sm) 0;
-}
-
-
-/* Responsive Design */
-@media (max-width: 768px) {
-  .headerContent {
-    flex-direction: column;
-    align-items: stretch;
+    white-space: nowrap;
  }

-  .header h1 {
-    font-size: 1.75rem;
+  .chipNameFull {
+    display: none;
  }

-  .metricSelector {
-    flex-direction: column;
-    align-items: stretch;
-    padding: 1rem;
-    border-radius: 8px;
+  .chipNameShort {
+    display: inline;
  }

-  .metricSelect {
-    max-width: 100%;
+  .chipMeta {
+    display: none;
  }

-  .schoolsGrid {
-    grid-template-columns: 1fr;
-  }
-
-  .chartSection,
-  .tableSection {
-    padding: 1rem;
-    border-radius: 8px;
-  }
-
-  .chartContainer {
-    /* Taller than desktop's proportion would suggest: the chip legend row
-       sits inside, and the in-chart title/legend/axis titles are gone, so
-       nearly all of this is plot area. */
-    height: 340px;
-  }
-
-  .comparisonTable {
-    font-size: 0.875rem;
-  }
-
-  .comparisonTable th,
-  .comparisonTable td {
-    padding: 0.75rem 0.5rem;
-  }
-
-  .latestValue {
-    margin-left: -1rem;
-    margin-right: -1rem;
-    margin-bottom: -1rem;
-    padding: 1rem;
-    border-radius: 0 0 8px 5px;
+  .chipRemove {
+    width: 18px;
+    height: 18px;
+    font-size: 0.75rem;
  }
 }
@@ -1,49 +1,42 @@
 /**
- * ComparisonView Component
- * Client-side comparison interface with phase tabs, charts, and tables
+ * ComparisonView — the parent-first compare screen: a sticky school bar and
+ * six sections (At a glance / Ofsted / Academics / Getting a place / Who
+ * goes there / Explore trends), every number anchored against the England
+ * average or the computed state-school benchmark with provenance-correct
+ * labels. Layout and copy follow the reviewed mockups
+ * (docs/superpowers/specs/mockups/).
 */

 'use client';

 import { useEffect, useRef, useState } from 'react';
 import { useRouter, usePathname, useSearchParams } from 'next/navigation';
-import dynamic from 'next/dynamic';
 import { useComparison } from '@/hooks/useComparison';

-const ComparisonChart = dynamic(
-  () => import('./ComparisonChart').then((m) => m.ComparisonChart),
-  { ssr: false },
-);
 import { SchoolSearchModal } from './SchoolSearchModal';
 import { EmptyState } from './EmptyState';
-import { LoadingSkeleton } from './LoadingSkeleton';
-import type { ComparisonData, MetricDefinition, School } from '@/lib/types';
-import { formatPercentage, formatProgress, formatAcademicYear, CHART_COLORS, CHART_TEXT_COLORS, schoolUrl } from '@/lib/utils';
+import { CompareAtAGlance } from './compare/CompareAtAGlance';
+import { CompareOfsted } from './compare/CompareOfsted';
+import { CompareAcademics } from './compare/CompareAcademics';
+import { CompareAdmissions } from './compare/CompareAdmissions';
+import { CompareCommunity } from './compare/CompareCommunity';
+import { TrendsExplorer, PRIMARY_CATEGORIES, SECONDARY_CATEGORIES } from './compare/TrendsExplorer';
+import type {
+  Benchmarks,
+  ComparisonData,
+  MetricDefinition,
+  NationalAverages,
+  School,
+} from '@/lib/types';
+import { CHART_COLORS, schoolUrl, shortName } from '@/lib/utils';
 import { fetchComparison } from '@/lib/api';
 import { track } from '@/lib/analytics';
 import styles from './ComparisonView.module.css';

-const PRIMARY_CATEGORIES = ['expected', 'higher', 'progress', 'average', 'gender', 'equity', 'context', 'absence', 'trends'];
-const SECONDARY_CATEGORIES = ['gcse'];
-
-const PRIMARY_OPTGROUPS: { label: string; category: string }[] = [
-  { label: 'Expected Standard', category: 'expected' },
-  { label: 'Higher Standard', category: 'higher' },
-  { label: 'Progress Scores', category: 'progress' },
-  { label: 'Average Scores', category: 'average' },
-  { label: 'Gender Performance', category: 'gender' },
-  { label: 'Equity (Disadvantaged)', category: 'equity' },
-  { label: 'School Context', category: 'context' },
-  { label: 'Absence', category: 'absence' },
-  { label: '3-Year Trends', category: 'trends' },
-];
-
-const SECONDARY_OPTGROUPS: { label: string; category: string }[] = [
-  { label: 'GCSE Performance', category: 'gcse' },
-];
-
 interface ComparisonViewProps {
  initialData: Record<string, ComparisonData> | null;
+  initialNationalAverages?: NationalAverages;
+  initialBenchmarks?: Benchmarks;
  initialUrns: number[];
  metrics: MetricDefinition[];
  selectedMetric: string;
@@ -51,6 +44,8 @@ interface ComparisonViewProps {

 export function ComparisonView({
  initialData,
+  initialNationalAverages,
+  initialBenchmarks,
  initialUrns,
  metrics,
  selectedMetric: initialMetric,
@@ -58,11 +53,15 @@ export function ComparisonView({
  const router = useRouter();
  const pathname = usePathname();
  const searchParams = useSearchParams();
-  const { selectedSchools, removeSchool, addSchool, replaceSchools, isInitialized } = useComparison();
+  const { selectedSchools, removeSchool, replaceSchools, isInitialized } = useComparison();

  const [selectedMetric, setSelectedMetric] = useState(initialMetric);
  const [isModalOpen, setIsModalOpen] = useState(false);
  const [comparisonData, setComparisonData] = useState(initialData);
+  const [nationalAverages, setNationalAverages] = useState<NationalAverages | undefined>(
+    initialNationalAverages,
+  );
+  const [benchmarks, setBenchmarks] = useState<Benchmarks | undefined>(initialBenchmarks);
  const [shareConfirm, setShareConfirm] = useState(false);
  const [comparePhase, setComparePhase] = useState<'primary' | 'secondary'>('primary');
  // Tracks whether the user has explicitly clicked a phase tab.
@@ -77,24 +76,27 @@ export function ComparisonView({
    if (!isInitialized) return;
    if (initialUrns.length > 0 && initialData) {
      const urlSchools = initialUrns
-        .map(urn => initialData[String(urn)]?.school_info)
+        .map((urn) => initialData[String(urn)]?.school_info)
        .filter((info): info is NonNullable<typeof info> => Boolean(info));
      const sameSet =
        urlSchools.length === selectedSchools.length &&
-        urlSchools.every(s => selectedSchools.some(sel => sel.urn === s.urn));
+        urlSchools.every((s) => selectedSchools.some((sel) => sel.urn === s.urn));
      if (urlSchools.length > 0 && !sameSet) {
        replaceSchools(urlSchools);
      }
    }
  }, [isInitialized]); // eslint-disable-line react-hooks/exhaustive-deps

-  // Sync URL with selected schools
+  const urnKey = selectedSchools.map((s) => s.urn).join(',');
+
+  // Sync the URL with the selection + metric. Pure navigation state — no
+  // fetching here: metric changes are presentational (the data is already
+  // client-side) and must not refire the comparison request.
  useEffect(() => {
-    const urns = selectedSchools.map((s) => s.urn).join(',');
    const params = new URLSearchParams(searchParams);

-    if (urns) {
-      params.set('urns', urns);
+    if (urnKey) {
+      params.set('urns', urnKey);
    } else {
      params.delete('urns');
    }
@@ -103,52 +105,70 @@ export function ComparisonView({

    const newUrl = `${pathname}?${params.toString()}`;
    router.replace(newUrl, { scroll: false });
+  }, [urnKey, selectedMetric, pathname, searchParams, router]);

-    // Fetch comparison data
-    if (selectedSchools.length > 0) {
-      fetchComparison(urns, { cache: 'no-store' })
+  // Fetch when the school set changes, but only for schools we don't already
+  // have data for. This skips the refetch of SSR-rendered data on load AND
+  // avoids a network call when a school is merely removed. A ref holds the
+  // latest data so the effect can read it without re-running on every fetch.
+  //
+  // Correctness note: we must NOT null the data on a transient empty urnKey.
+  // On mount the basket is empty for a beat before it hydrates from the URL,
+  // and blanking here (then skipping the refetch because SSR "covers" the set)
+  // was leaving the page empty on refresh. The render already shows the empty
+  // state whenever `selectedSchools` is empty, so stale data for deselected
+  // schools is harmless — it's simply unused.
+  const comparisonDataRef = useRef(comparisonData);
+  comparisonDataRef.current = comparisonData;
+
+  useEffect(() => {
+    if (!isInitialized || !urnKey) return;
+
+    const have = comparisonDataRef.current ?? {};
+    const covered = urnKey.split(',').every((urn) => have[urn] != null);
+    if (covered) return;
+
+    fetchComparison(urnKey, { cache: 'no-store' })
      .then((data) => {
        setComparisonData(data.comparison);
+        setNationalAverages(data.national_averages);
+        setBenchmarks(data.benchmarks);
      })
      .catch((err) => {
        // Keep whatever we already have (SSR data or a previous fetch) rather
-          // than blanking the chart — a transient refetch failure shouldn't
+        // than blanking the page — a transient refetch failure shouldn't
        // destroy a working comparison the user is looking at.
        console.error('Failed to fetch comparison:', err);
      });
-    } else {
-      setComparisonData(null);
-    }
-  }, [selectedSchools, selectedMetric, pathname, searchParams, router]);
+  }, [urnKey, isInitialized]);

-  // Classify schools by phase using comparison data
-  const classifySchool = (school: School): 'primary' | 'secondary' => {
+  const primarySchools = selectedSchools.filter((school) => {
    const info = comparisonData?.[school.urn]?.school_info;
-    if (info?.attainment_8_score != null) return 'secondary';
-    if (info?.rwm_expected_pct != null) return 'primary';
-    // Fallback: check yearly data
-    const yearlyData = comparisonData?.[school.urn]?.yearly_data;
-    if (yearlyData?.some((d: any) => d.attainment_8_score != null)) return 'secondary';
-    return 'primary';
-  };
+    const hasPrimaryData =
+      info?.rwm_expected_pct != null ||
+      comparisonData?.[school.urn]?.yearly_data?.some((d) => d.rwm_expected_pct != null);
+    if (hasPrimaryData) return true;
+    return school.phase?.toLowerCase().includes('primary') || false;
+  });

-  const primarySchools = selectedSchools.filter(s => classifySchool(s) === 'primary');
-  const secondarySchools = selectedSchools.filter(s => classifySchool(s) === 'secondary');
+  const secondarySchools = selectedSchools.filter((school) => {
+    const info = comparisonData?.[school.urn]?.school_info;
+    const hasSecondaryData =
+      info?.attainment_8_score != null ||
+      comparisonData?.[school.urn]?.yearly_data?.some((d) => d.attainment_8_score != null);
+    if (hasSecondaryData) return true;
+    return school.phase?.toLowerCase().includes('secondary') || false;
+  });

-  // Auto-select tab with more schools and sync the metric to match the detected phase.
-  // This fixes the case where the URL carries a primary metric (e.g. rwm_expected_pct)
-  // but the shortlisted schools are secondary — the phase tab switches but the metric
-  // needs to follow, otherwise all secondary cards show "–" for a primary-only field.
+  // Auto-select tab with more schools and sync the metric to match the phase.
  useEffect(() => {
    if (!comparisonData || selectedSchools.length === 0) return;
    if (phaseLockedByUser.current) return;
    const newPhase = secondarySchools.length > primarySchools.length ? 'secondary' : 'primary';
    setComparePhase(newPhase);
-    // Only reset the metric when it doesn't belong to the newly detected phase.
-    // This preserves a correct metric that came from the URL (e.g. metric=attainment_8_score).
    const phaseCategories = newPhase === 'secondary' ? SECONDARY_CATEGORIES : PRIMARY_CATEGORIES;
    const metricFitsPhase = metrics.some(
-      (m) => m.key === selectedMetric && phaseCategories.includes(m.category)
+      (m) => m.key === selectedMetric && phaseCategories.includes(m.category),
    );
    if (!metricFitsPhase) {
      setSelectedMetric(newPhase === 'secondary' ? 'attainment_8_score' : 'rwm_expected_pct');
@@ -158,29 +178,24 @@ export function ComparisonView({
  const handlePhaseChange = (phase: 'primary' | 'secondary') => {
    phaseLockedByUser.current = true;
    setComparePhase(phase);
-    const defaultMetric = phase === 'secondary' ? 'attainment_8_score' : 'rwm_expected_pct';
-    setSelectedMetric(defaultMetric);
+    setSelectedMetric(phase === 'secondary' ? 'attainment_8_score' : 'rwm_expected_pct');
  };

  // compare_viewed: fire once after the page has its first selection.
-  // We watch `selectedSchools.length` going from 0 → ≥1 so the event is
-  // sent only when there's actual content to view, not for empty arrivals.
  const compareViewedRef = useRef(false);
  useEffect(() => {
    if (compareViewedRef.current) return;
    if (selectedSchools.length === 0) return;
    compareViewedRef.current = true;
-    const primaryCount = selectedSchools.filter(s => s.phase?.toLowerCase().includes('primary')).length;
+    const primaryCount = selectedSchools.filter((s) =>
+      s.phase?.toLowerCase().includes('primary'),
+    ).length;
    const secondaryCount = selectedSchools.length - primaryCount;
-    const phaseMix = primaryCount === 0 ? 'all_secondary' : secondaryCount === 0 ? 'all_primary' : 'mixed';
+    const phaseMix =
+      primaryCount === 0 ? 'all_secondary' : secondaryCount === 0 ? 'all_primary' : 'mixed';
    track('compare_viewed', { school_count: selectedSchools.length, phase_mix: phaseMix });
  }, [selectedSchools]);

-  const handleMetricChange = (metric: string) => {
-    track('compare_metric_changed', { metric, phase: comparePhase });
-    setSelectedMetric(metric);
-  };
-
  const handleRemoveSchool = (urn: number) => {
    removeSchool(urn);
    track('compare_school_removed', { urn, from: 'compare' });
@@ -191,21 +206,22 @@ export function ComparisonView({
    const count = selectedSchools.length;
    const shareData = {
      title: 'School comparison · SchoolCompare',
-      text: count > 0
+      text:
+        count > 0
          ? `Comparing ${count} school${count === 1 ? '' : 's'} on SchoolCompare`
          : 'SchoolCompare',
      url,
    };
-    // Prefer the native share sheet on platforms that support it (iOS / Android).
-    // canShare is feature-detected because Safari iOS exposes share() but
-    // some configurations refuse the payload.
-    if (typeof navigator !== 'undefined' && navigator.share && (!navigator.canShare || navigator.canShare(shareData))) {
+    if (
+      typeof navigator !== 'undefined' &&
+      navigator.share &&
+      (!navigator.canShare || navigator.canShare(shareData))
+    ) {
      try {
        await navigator.share(shareData);
        track('compare_shared', { method: 'native', school_count: count });
        return;
      } catch (err) {
-        // User cancelled — bail silently. Any other error falls through to clipboard.
        if ((err as DOMException)?.name === 'AbortError') return;
      }
    }
@@ -214,27 +230,22 @@ export function ComparisonView({
      track('compare_shared', { method: 'clipboard', school_count: count });
      setShareConfirm(true);
      setTimeout(() => setShareConfirm(false), 2000);
-    } catch { /* fallback: do nothing */ }
+    } catch {
+      /* fallback: do nothing */
+    }
  };

  const isPrimary = comparePhase === 'primary';
-  const allowedCategories = isPrimary ? PRIMARY_CATEGORIES : SECONDARY_CATEGORIES;
-  const optgroups = isPrimary ? PRIMARY_OPTGROUPS : SECONDARY_OPTGROUPS;
-  const filteredMetrics = metrics.filter(m => allowedCategories.includes(m.category));
  const activeSchools = isPrimary ? primarySchools : secondarySchools;

-  // Get metric definition
-  const currentMetricDef = metrics.find((m) => m.key === selectedMetric);
-  const metricLabel = currentMetricDef?.label || selectedMetric;
-
-  // No schools selected
  if (selectedSchools.length === 0) {
    return (
      <div className={styles.container}>
        <header className={styles.header}>
          <h1>Compare Schools</h1>
          <p className={styles.subtitle}>
-            Add schools to your comparison basket to see side-by-side performance data
+            Add schools to your comparison basket to see them side by side — inspection results,
+            academics, admissions and community.
          </p>
        </header>

@@ -252,39 +263,46 @@ export function ComparisonView({
    );
  }

-  // Build filtered comparison data for active phase
+  // Build filtered comparison data for the active phase
  const activeComparisonData: Record<string, ComparisonData> = {};
  if (comparisonData) {
-    activeSchools.forEach(s => {
+    activeSchools.forEach((s) => {
      if (comparisonData[s.urn]) {
        activeComparisonData[s.urn] = comparisonData[s.urn];
      }
    });
  }
-
-  // Get years for table
-  const years =
-    Object.keys(activeComparisonData).length > 0
-      ? activeComparisonData[Object.keys(activeComparisonData)[0]].yearly_data.map((d) => d.year)
-      : [];
+  const hasData = Object.keys(activeComparisonData).length > 0;

  return (
    <div className={styles.container}>
-      {/* Header */}
      <header className={styles.header}>
        <div className={styles.headerContent}>
          <div>
            <h1>Compare Schools</h1>
            <p className={styles.subtitle}>
-              Comparing {selectedSchools.length} school{selectedSchools.length !== 1 ? 's' : ''}
+              {selectedSchools.length} school{selectedSchools.length !== 1 ? 's' : ''} side by side
+              — each number anchored against the England average so you can tell at a glance
+              what&apos;s typical and what stands out.
            </p>
          </div>
-          <div style={{ display: 'flex', gap: '0.75rem', alignItems: 'center', flexWrap: 'wrap' }}>
+          <div className={styles.headerActions}>
            <button onClick={() => setIsModalOpen(true)} className="btn btn-primary">
              + Add School
            </button>
            <button onClick={handleShare} className="btn btn-tertiary" title="Copy comparison link">
-              <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" width="16" height="16"><path d="M4 12v8a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2v-8"/><polyline points="16 6 12 2 8 6"/><line x1="12" y1="2" x2="12" y2="15"/></svg>
+              <svg
+                viewBox="0 0 24 24"
+                fill="none"
+                stroke="currentColor"
+                strokeWidth="2"
+                width="16"
+                height="16"
+              >
+                <path d="M4 12v8a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2v-8" />
+                <polyline points="16 6 12 2 8 6" />
+                <line x1="12" y1="2" x2="12" y2="15" />
+              </svg>
              {shareConfirm ? 'Copied!' : 'Share'}
            </button>
          </div>
@@ -292,6 +310,7 @@ export function ComparisonView({
      </header>

      {/* Phase Tabs */}
+      {secondarySchools.length > 0 && primarySchools.length > 0 && (
        <div className={styles.phaseTabs}>
          <button
            className={`${styles.phaseTab} ${isPrimary ? styles.phaseTabActive : ''}`}
@@ -306,6 +325,7 @@ export function ComparisonView({
            Secondary ({secondarySchools.length})
          </button>
        </div>
+      )}

      {activeSchools.length === 0 ? (
        <EmptyState
@@ -318,184 +338,86 @@ export function ComparisonView({
        />
      ) : (
        <>
-          {/* Metric Selector */}
-          <section className={styles.metricSelector}>
-            <label htmlFor="metric-select" className={styles.metricLabel}>
-              Select Metric:
-            </label>
-            <select
-              id="metric-select"
-              value={selectedMetric}
-              onChange={(e) => handleMetricChange(e.target.value)}
-              className={styles.metricSelect}
-            >
-              {optgroups.map(({ label, category }) => {
-                const groupMetrics = filteredMetrics.filter(m => m.category === category);
-                if (groupMetrics.length === 0) return null;
-                return (
-                  <optgroup key={category} label={label}>
-                    {groupMetrics.map((metric) => (
-                      <option key={metric.key} value={metric.key}>{metric.label}</option>
-                    ))}
-                  </optgroup>
-                );
-              })}
-            </select>
-            {currentMetricDef?.description && (
-              <p className={styles.metricDescription}>{currentMetricDef.description}</p>
-            )}
-          </section>
-
-          {/* Progress score explanation */}
-          {selectedMetric.includes('progress') && (
-            <p className={styles.progressNote}>
-              Progress scores measure pupils&apos; progress from KS1 to KS2. A score of 0 equals the national average; positive scores are above average.
-            </p>
-          )}
-
-          {/* School Cards */}
-          <section className={styles.schoolsSection}>
-            <div className={styles.schoolsGrid}>
+          {/* Sticky school bar — column identity while scrolling */}
+          <div className={styles.schoolBar} aria-label="Schools in this comparison">
            {activeSchools.map((school, index) => (
              <div
                key={school.urn}
-                  className={styles.schoolCard}
-                  style={{ borderLeft: `3px solid ${CHART_COLORS[index % CHART_COLORS.length]}` }}
+                className={styles.schoolChip}
+                style={{ borderTopColor: CHART_COLORS[index % CHART_COLORS.length] }}
              >
+                <span
+                  className={styles.chipDot}
+                  style={{ background: CHART_COLORS[index % CHART_COLORS.length] }}
+                  aria-hidden="true"
+                />
+                <span className={styles.chipText}>
+                  <a className={styles.chipName} href={schoolUrl(school.urn, school.school_name)}>
+                    <span className={styles.chipNameFull}>{school.school_name}</span>
+                    <span className={styles.chipNameShort}>{shortName(school.school_name)}</span>
+                  </a>
+                  <span className={styles.chipMeta}>
+                    {[school.local_authority, school.school_type].filter(Boolean).join(' · ')}
+                  </span>
+                </span>
                <button
                  onClick={() => handleRemoveSchool(school.urn)}
-                    className={styles.removeButton}
+                  className={styles.chipRemove}
                  aria-label={`Remove ${school.school_name}`}
                  title="Remove from comparison"
                >
                  ×
                </button>
-                  <h2 className={styles.schoolName}>
-                    <a href={schoolUrl(school.urn, school.school_name)}>{school.school_name}</a>
-                  </h2>
-                  <div className={styles.schoolMeta}>
-                    {school.local_authority && (
-                      <span className={styles.metaItem}>{school.local_authority}</span>
-                    )}
-                    {school.school_type && (
-                      <span className={styles.metaItem}>{school.school_type}</span>
-                    )}
-                  </div>
-
-                  {/* Latest metric value */}
-                  {activeComparisonData[school.urn] && (
-                    <div className={styles.latestValue}>
-                      <div className={styles.latestLabel}>{metricLabel}</div>
-                      {/* Text uses the AA-dark variant; the swatch dot keeps the true series colour */}
-                      <div className={styles.latestNumber} style={{ color: CHART_TEXT_COLORS[index % CHART_TEXT_COLORS.length] }}>
-                        <span
-                          style={{
-                            display: 'inline-block',
-                            width: '10px',
-                            height: '10px',
-                            borderRadius: '50%',
-                            background: CHART_COLORS[index % CHART_COLORS.length],
-                            marginRight: '0.4rem',
-                            verticalAlign: 'middle',
-                          }}
-                        />
-                        {(() => {
-                          const yearlyData = activeComparisonData[school.urn].yearly_data;
-                          if (yearlyData.length === 0) return '-';
-
-                          const latestData = yearlyData[yearlyData.length - 1];
-                          const value = latestData[selectedMetric as keyof typeof latestData];
-
-                          if (value === null || value === undefined) return '-';
-
-                          if (selectedMetric.includes('progress')) {
-                            return formatProgress(value as number);
-                          } else if (selectedMetric.includes('pct') || selectedMetric.includes('rate')) {
-                            return formatPercentage(value as number);
-                          } else {
-                            return typeof value === 'number' ? value.toFixed(1) : String(value);
-                          }
-                        })()}
-                      </div>
-                    </div>
-                  )}
              </div>
            ))}
          </div>
-          </section>

-          {/* Comparison Chart */}
-          {Object.keys(activeComparisonData).length > 0 ? (
-            <section className={styles.chartSection}>
-              <h2 className={styles.sectionTitle}>Performance Over Time</h2>
-              <div className={styles.chartContainer}>
-                <ComparisonChart
-                  comparisonData={activeComparisonData}
+          {hasData && (
+            <>
+              <CompareAtAGlance
                schools={activeSchools}
+                data={activeComparisonData}
+                nationalAverages={nationalAverages}
+                benchmarks={benchmarks}
+                isSecondary={!isPrimary}
+              />
+              <CompareOfsted schools={activeSchools} data={activeComparisonData} />
+              <CompareAcademics
+                schools={activeSchools}
+                data={activeComparisonData}
+                nationalAverages={nationalAverages}
+                benchmarks={benchmarks}
+                isSecondary={!isPrimary}
+              />
+              <CompareAdmissions schools={activeSchools} data={activeComparisonData} />
+              <CompareCommunity
+                schools={activeSchools}
+                data={activeComparisonData}
+                benchmarks={benchmarks}
+                isSecondary={!isPrimary}
+              />
+              <TrendsExplorer
+                schools={activeSchools}
+                data={activeComparisonData}
+                metrics={metrics}
                metric={selectedMetric}
-                  metricLabel={metricLabel}
+                onMetricChange={setSelectedMetric}
+                isPrimaryPhase={isPrimary}
+                nationalAverages={nationalAverages}
              />
-              </div>
-            </section>
-          ) : activeSchools.length > 0 ? (
-            <section className={styles.chartSection}>
-              <LoadingSkeleton type="list" />
-            </section>
-          ) : null}

-          {/* Comparison Table */}
-          {Object.keys(activeComparisonData).length > 0 && years.length > 0 && (
-            <section className={styles.tableSection}>
-              <h2 className={styles.sectionTitle}>Detailed Comparison</h2>
-              <div className={styles.tableWrapper}>
-                <table className={styles.comparisonTable}>
-                  <thead>
-                    <tr>
-                      <th>Year</th>
-                      {activeSchools.map((school) => (
-                        <th key={school.urn}>{school.school_name}</th>
-                      ))}
-                    </tr>
-                  </thead>
-                  <tbody>
-                    {years.map((year) => (
-                      <tr key={year}>
-                        <td className={styles.yearCell}>{formatAcademicYear(year)}</td>
-                        {activeSchools.map((school) => {
-                          const schoolData = activeComparisonData[school.urn];
-                          if (!schoolData) return <td key={school.urn}>-</td>;
-
-                          const yearData = schoolData.yearly_data.find((d) => d.year === year);
-                          if (!yearData) return <td key={school.urn}>-</td>;
-
-                          const value = yearData[selectedMetric as keyof typeof yearData];
-
-                          if (value === null || value === undefined) {
-                            return <td key={school.urn}>-</td>;
-                          }
-
-                          let displayValue: string;
-                          if (selectedMetric.includes('progress')) {
-                            displayValue = formatProgress(value as number);
-                          } else if (selectedMetric.includes('pct') || selectedMetric.includes('rate')) {
-                            displayValue = formatPercentage(value as number);
-                          } else {
-                            displayValue = typeof value === 'number' ? value.toFixed(1) : String(value);
-                          }
-
-                          return <td key={school.urn}>{displayValue}</td>;
-                        })}
-                      </tr>
-                    ))}
-                  </tbody>
-                </table>
-              </div>
-            </section>
+              <p className={styles.footnote}>
+                Sources: DfE Compare School Performance (KS2/KS4 results), Ofsted inspection
+                outcomes, DfE school admissions data, school census. England averages for test
+                results are official DfE figures; other benchmarks are state-school averages
+                computed from our dataset. Following DfE practice, figures based on 5 or fewer
+                pupils are suppressed and shown as &quot;no data&quot;.
+              </p>
+            </>
          )}
        </>
      )}

-      {/* School Search Modal */}
      <SchoolSearchModal isOpen={isModalOpen} onClose={() => setIsModalOpen(false)} />
    </div>
  );
@@ -0,0 +1,102 @@
+.row {
+  margin: 1.1rem 0 1.6rem;
+}
+
+.head {
+  display: flex;
+  justify-content: space-between;
+  align-items: baseline;
+  gap: 1rem;
+  flex-wrap: wrap;
+}
+
+.title {
+  font-weight: 600;
+  font-size: 0.95rem;
+}
+
+.headNote {
+  font-size: 0.8rem;
+  color: var(--text-muted);
+}
+
+.strip {
+  position: relative;
+  height: 34px;
+  margin-top: 0.45rem;
+}
+
+.track {
+  position: absolute;
+  left: 0;
+  right: 0;
+  top: 15px;
+  height: 4px;
+  border-radius: 2px;
+  background: var(--bg-secondary);
+}
+
+.anchorTick {
+  position: absolute;
+  top: 4px;
+  width: 2px;
+  height: 26px;
+  background: var(--text-muted);
+}
+
+.anchorLabel {
+  position: absolute;
+  top: -14px;
+  transform: translateX(-50%);
+  font-size: 0.7rem;
+  color: var(--text-muted);
+  white-space: nowrap;
+}
+
+.point {
+  position: absolute;
+  top: 9px;
+  width: 16px;
+  height: 16px;
+  border-radius: 50%;
+  transform: translateX(-50%);
+  border: 2px solid var(--bg-card);
+  box-shadow: 0 0 0 1px rgba(26, 22, 18, 0.08);
+}
+
+.pointLabel {
+  position: absolute;
+  top: 27px;
+  transform: translateX(-50%);
+  font-size: 0.72rem;
+  font-weight: 600;
+  font-variant-numeric: tabular-nums;
+  color: var(--text-secondary);
+}
+
+.pointLabelAbove {
+  top: -6px;
+}
+
+@media (max-width: 760px) {
+  .row {
+    margin: 0.9rem 0 1.3rem;
+  }
+
+  .title {
+    font-size: 0.82rem;
+  }
+
+  .strip {
+    height: 32px;
+  }
+
+  .point {
+    width: 14px;
+    height: 14px;
+  }
+
+  .pointLabel {
+    font-size: 0.64rem;
+  }
+}
@@ -0,0 +1,97 @@
+/**
+ * DotStrip — the compare screen's signature element: one measure per strip,
+ * every school's dot on a shared track, anchored by a grey England-average
+ * tick so "right of the tick = above average" needs no domain knowledge.
+ */
+
+'use client';
+
+import { stripPositions } from '@/lib/compareLogic';
+import { CHART_COLORS, CHART_TEXT_COLORS } from '@/lib/utils';
+import styles from './DotStrip.module.css';
+
+export interface DotStripProps {
+  label: string;
+  /** One value per school; index = the school's chart-colour index. */
+  values: Array<number | null>;
+  schoolNames: string[];
+  /** Anchor tick, e.g. { value: 62, label: 'England 62%' }. Omit when the
+   * benchmark isn't available — the caller should say why in `headNote`. */
+  anchor?: { value: number; label: string } | null;
+  min?: number;
+  max?: number;
+  unit?: string;
+  /** Tooltip on the measure label (plain-English definition). */
+  tip?: string;
+  /** Small note on the right of the header row (e.g. the tick legend). */
+  headNote?: string;
+}
+
+export function DotStrip({
+  label,
+  values,
+  schoolNames,
+  anchor = null,
+  min = 0,
+  max = 100,
+  unit = '%',
+  tip,
+  headNote,
+}: DotStripProps) {
+  const points = stripPositions(values, min, max);
+  const span = max - min;
+  const anchorPos =
+    anchor != null
+      ? Math.min(100, Math.max(0, ((anchor.value - min) / span) * 100))
+      : null;
+
+  const ariaParts = [
+    anchor ? `${anchor.label}` : null,
+    ...points.map(
+      (p) => `${schoolNames[p.schoolIndex] ?? `School ${p.schoolIndex + 1}`} ${p.value}${unit}`,
+    ),
+  ].filter(Boolean);
+
+  return (
+    <div className={styles.row}>
+      <div className={styles.head}>
+        <span className={styles.title} title={tip}>
+          {label}
+        </span>
+        {headNote && <span className={styles.headNote}>{headNote}</span>}
+      </div>
+      <div className={styles.strip} role="img" aria-label={`${label}: ${ariaParts.join(', ')}`}>
+        <div className={styles.track} />
+        {anchorPos != null && anchor && (
+          <>
+            <span className={styles.anchorTick} style={{ left: `${anchorPos}%` }} />
+            <span className={styles.anchorLabel} style={{ left: `${anchorPos}%` }}>
+              {anchor.label}
+            </span>
+          </>
+        )}
+        {points.map((p) => (
+          <span key={p.schoolIndex}>
+            <span
+              className={styles.point}
+              style={{
+                left: `${p.pos}%`,
+                background: CHART_COLORS[p.schoolIndex % CHART_COLORS.length],
+              }}
+              title={`${schoolNames[p.schoolIndex] ?? ''}: ${p.value}${unit}`}
+            />
+            <span
+              className={`${styles.pointLabel} ${p.labelAbove ? styles.pointLabelAbove : ''}`}
+              style={{
+                left: `${p.pos}%`,
+                color: CHART_TEXT_COLORS[p.schoolIndex % CHART_TEXT_COLORS.length],
+              }}
+            >
+              {p.value}
+            </span>
+          </span>
+        ))}
+      </div>
+    </div>
+  );
+}
@@ -36,6 +36,91 @@
  margin-bottom: 0;
 }

+.searchHint {
+  margin: 0.875rem 0 0;
+  font-size: 0.95rem;
+  color: var(--text-secondary, #5a554d);
+  text-align: center;
+}
+
+.searchHint strong {
+  color: var(--text-primary, #1a1612);
+  font-weight: 600;
+}
+
+@media (max-width: 600px) {
+  .searchHint {
+    font-size: 0.85rem;
+    text-align: left;
+  }
+}
+
+.nearMeRow {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  gap: 0.5rem;
+  margin-top: 0.75rem;
+}
+
+.nearMeBtn {
+  display: inline-flex;
+  align-items: center;
+  gap: 0.5rem;
+  padding: 0.625rem 1.375rem;
+  background: var(--accent-teal, #2d7d7d);
+  color: #fff;
+  border: none;
+  border-radius: 999px;
+  font-size: 0.9375rem;
+  font-weight: 600;
+  cursor: pointer;
+  transition: background 0.2s ease, transform 0.15s ease;
+  font-family: inherit;
+}
+
+.nearMeBtn:hover:not(:disabled) {
+  background: #235f5f;
+  transform: translateY(-1px);
+}
+
+.nearMeBtn:disabled {
+  opacity: 0.7;
+  cursor: not-allowed;
+}
+
+.nearMeSpinner {
+  display: inline-block;
+  width: 14px;
+  height: 14px;
+  border: 2px solid rgba(255, 255, 255, 0.35);
+  border-top-color: #fff;
+  border-radius: 50%;
+  animation: nearMeSpin 0.7s linear infinite;
+  flex-shrink: 0;
+}
+
+@keyframes nearMeSpin {
+  to {
+    transform: rotate(360deg);
+  }
+}
+
+.geoError {
+  font-size: 0.8125rem;
+  color: var(--accent-coral-dark, #b04a2e);
+  margin: 0;
+  max-width: 340px;
+  text-align: center;
+}
+
+@media (max-width: 600px) {
+  .nearMeBtn {
+    width: 100%;
+    justify-content: center;
+  }
+}
+
 .searchSection {
  margin-bottom: 0;
 }
@@ -11,9 +11,21 @@ interface FilterBarProps {
  filters: Filters;
  isHero?: boolean;
  resultFilters?: ResultFilters;
+  // Geolocation "use my location" affordance, shown beside the hero search box.
+  // The state and handler live in HomeView (which owns the geolocation flow).
+  onNearMe?: () => void;
+  geoState?: "idle" | "requesting" | "error";
+  geoError?: string | null;
 }

-export function FilterBar({ filters, isHero, resultFilters }: FilterBarProps) {
+export function FilterBar({
+  filters,
+  isHero,
+  resultFilters,
+  onNearMe,
+  geoState = "idle",
+  geoError,
+}: FilterBarProps) {
  const router = useRouter();
  const pathname = usePathname();
  const searchParams = useSearchParams();
@@ -182,6 +194,52 @@ export function FilterBar({ filters, isHero, resultFilters }: FilterBarProps) {
            {isPending ? <div className={styles.spinner}></div> : "Search"}
          </button>
        </div>
+        {isHero && (
+          <>
+            <p className={styles.searchHint}>
+              Search by <strong>school name</strong> — or use your{" "}
+              <strong>postcode</strong> for the nearest schools.
+            </p>
+            {onNearMe && (
+              <div className={styles.nearMeRow}>
+                <button
+                  type="button"
+                  className={styles.nearMeBtn}
+                  onClick={onNearMe}
+                  disabled={geoState === "requesting"}
+                >
+                  {geoState === "requesting" ? (
+                    <>
+                      <span className={styles.nearMeSpinner} aria-hidden="true" />
+                      Locating you…
+                    </>
+                  ) : (
+                    <>
+                      <svg
+                        width="15"
+                        height="15"
+                        viewBox="0 0 24 24"
+                        fill="none"
+                        stroke="currentColor"
+                        strokeWidth="2.5"
+                        aria-hidden="true"
+                      >
+                        <path d="M12 2a7 7 0 0 1 7 7c0 5.25-7 13-7 13S5 14.25 5 9a7 7 0 0 1 7-7z" />
+                        <circle cx="12" cy="9" r="2.5" />
+                      </svg>
+                      Use my location
+                    </>
+                  )}
+                </button>
+                {geoError && (
+                  <p className={styles.geoError} role="alert">
+                    {geoError}
+                  </p>
+                )}
+              </div>
+            )}
+          </>
+        )}
      </form>

      {!isHero && (
@@ -310,8 +368,8 @@ export function FilterBar({ filters, isHero, resultFilters }: FilterBarProps) {
                    disabled={isPending}
                  >
                    <option value="">With or without sixth form</option>
-                    <option value="yes">With sixth form (11-18)</option>
-                    <option value="no">Without sixth form (11-16)</option>
+                    <option value="yes">With sixth form</option>
+                    <option value="no">Without sixth form</option>
                  </select>

                  {admissionsPolicyOptions.length > 0 && (
@@ -369,6 +369,16 @@

  .viewToggle {
    justify-content: center;
+    flex-shrink: 0;
+  }
+
+  /* The sort <select> sizes to its widest option ("Highest Reading, Writing
+     & Maths %"), which overflows a phone viewport — beside the view toggle it
+     ran off the right edge. Let it flex into the remaining space and shrink;
+     the selected label truncates instead of pushing past the screen. */
+  .sortSelect {
+    flex: 1;
+    min-width: 0;
  }

  .mapViewContainer {
@@ -496,68 +506,6 @@
  }
 }

-.discoverySection {
-  padding: 0.5rem 0 0.5rem;
-  text-align: center;
-}
-
-.nearMeRow {
-  display: flex;
-  flex-direction: column;
-  align-items: center;
-  gap: 0.5rem;
-  margin-bottom: 1.25rem;
-}
-
-.nearMeBtn {
-  display: inline-flex;
-  align-items: center;
-  gap: 0.5rem;
-  padding: 0.625rem 1.375rem;
-  background: var(--accent-teal, #2d7d7d);
-  color: #fff;
-  border: none;
-  border-radius: 999px;
-  font-size: 0.9375rem;
-  font-weight: 600;
-  cursor: pointer;
-  transition: background 0.2s ease, transform 0.15s ease;
-  font-family: inherit;
-}
-
-.nearMeBtn:hover:not(:disabled) {
-  background: #235f5f;
-  transform: translateY(-1px);
-}
-
-.nearMeBtn:disabled {
-  opacity: 0.7;
-  cursor: not-allowed;
-}
-
-.nearMeBtnSpinner {
-  display: inline-block;
-  width: 14px;
-  height: 14px;
-  border: 2px solid rgba(255, 255, 255, 0.35);
-  border-top-color: #fff;
-  border-radius: 50%;
-  animation: nearMeSpin 0.7s linear infinite;
-  flex-shrink: 0;
-}
-
-@keyframes nearMeSpin {
-  to { transform: rotate(360deg); }
-}
-
-.geoError {
-  font-size: 0.8125rem;
-  color: var(--accent-coral-dark, #b04a2e);
-  margin: 0;
-  max-width: 340px;
-  text-align: center;
-}
-
 .quickSearches {
  display: flex;
  align-items: center;
@@ -284,37 +284,11 @@ export function HomeView({ initialSchools, filters, totalSchools, howItWorks, ed
        filters={filters}
        isHero={!isSearchActive}
        resultFilters={initialSchools.result_filters}
+        onNearMe={handleNearMe}
+        geoState={geoState}
+        geoError={geoError}
      />

-      {/* Discovery section shown on landing page before any search */}
-      {!isSearchActive && initialSchools.schools.length === 0 && (
-        <div className={styles.discoverySection}>
-          <div className={styles.nearMeRow}>
-            <button
-              className={styles.nearMeBtn}
-              onClick={handleNearMe}
-              disabled={geoState === 'requesting'}
-            >
-              {geoState === 'requesting' ? (
-                <>
-                  <span className={styles.nearMeBtnSpinner} aria-hidden="true" />
-                  Locating you…
-                </>
-              ) : (
-                <>
-                  <svg width="15" height="15" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2.5" aria-hidden="true">
-                    <path d="M12 2a7 7 0 0 1 7 7c0 5.25-7 13-7 13S5 14.25 5 9a7 7 0 0 1 7-7z"/>
-                    <circle cx="12" cy="9" r="2.5"/>
-                  </svg>
-                  Schools near me
-                </>
-              )}
-            </button>
-            {geoError && <p className={styles.geoError} role="alert">{geoError}</p>}
-          </div>
-        </div>
-      )}
-
      {/* Admissions countdown strip — only on landing page */}
      {!isSearchActive && (
        <section className={styles.admissionsStrip}>
@@ -1543,3 +1543,18 @@
 .historyDisclosure[open] > .historyToggle::before {
    transform: rotate(90deg);
 }
+
+/* GIAS "Open, but proposed to close" notice strip */
+.closingStrip {
+  background: #fdf6e3;
+  border-left: 4px solid #e2c96f;
+  border-radius: 0 6px 6px 0;
+  padding: 0.55rem 0.9rem;
+  margin: 0.5rem 0;
+  font-size: 0.88rem;
+  color: #6e5a00;
+  max-width: 68ch;
+}
+.closingStrip strong {
+  color: #8a6200;
+}
@@ -18,7 +18,7 @@ import type {
  SchoolDeprivation, SchoolFinance, NationalAverages,
 } from '@/lib/types';
 import {
-  formatPercentage, formatProgress, formatAcademicYear,
+  formatPercentage, formatProgress, formatAcademicYear, isProposedToClose,
 } from '@/lib/utils';
 import { DeltaChip } from './DeltaChip';

@@ -313,6 +313,12 @@ export function SchoolDetailView({
                <span className={styles.metaItem}>{schoolInfo.gender}&apos;s school</span>
              )}
            </div>
+            {isProposedToClose(schoolInfo) && (
+              <div className={styles.closingStrip} role="note">
+                <strong>⚠ Proposed to close</strong> — this school is proposed for closure,
+                check with the local authority before applying.
+              </div>
+            )}
            {schoolInfo.address && (
              <p className={styles.address}>
                {schoolInfo.address}{schoolInfo.postcode && `, ${schoolInfo.postcode}`}
@@ -10,6 +10,15 @@
  height: 100dvh;
 }

+/* Fallback fullscreen (iOS Safari — no Element.requestFullscreen): the API
+   can't promote the element, so pin it over the page ourselves. Above the
+   comparison toast (3000) and the bottom nav; below modals (9999+). */
+.mapWrapper.fsFallback {
+  position: fixed;
+  inset: 0;
+  z-index: 5000;
+}
+
 .fullscreenBtn {
  position: absolute;
  top: 0.625rem;
@@ -33,22 +33,52 @@ interface SchoolMapProps {

 export function SchoolMap({ schools, center, zoom = 13, referencePoint, onMarkerClick, nationalAvgRwm, laAverages }: SchoolMapProps) {
  const wrapperRef = useRef<HTMLDivElement>(null);
-  const [isFullscreen, setIsFullscreen] = useState(false);
+  const [nativeFullscreen, setNativeFullscreen] = useState(false);
+  // iOS Safari has no Element.requestFullscreen — fall back to a fixed-position
+  // overlay driven by state instead of the Fullscreen API.
+  const [fallbackFullscreen, setFallbackFullscreen] = useState(false);
+  const isFullscreen = nativeFullscreen || fallbackFullscreen;

  // Sync state with browser fullscreen events (e.g. Escape key)
  useEffect(() => {
-    const onFsChange = () => setIsFullscreen(!!document.fullscreenElement);
+    const onFsChange = () => setNativeFullscreen(!!document.fullscreenElement);
    document.addEventListener('fullscreenchange', onFsChange);
    return () => document.removeEventListener('fullscreenchange', onFsChange);
  }, []);

+  // Lock body scroll while the fallback overlay is up.
+  useEffect(() => {
+    if (!fallbackFullscreen) return;
+    const prev = document.body.style.overflow;
+    document.body.style.overflow = 'hidden';
+    return () => { document.body.style.overflow = prev; };
+  }, [fallbackFullscreen]);
+
+  // Leaflet re-measures on window resize (trackResize). Native fullscreen fires
+  // one; the CSS fallback overlay changes size without a resize event, so nudge
+  // Leaflet after the layout settles or the map fills only part of the screen.
+  useEffect(() => {
+    const id = requestAnimationFrame(() => window.dispatchEvent(new Event('resize')));
+    return () => cancelAnimationFrame(id);
+  }, [isFullscreen]);
+
  const toggleFullscreen = useCallback(() => {
-    if (!document.fullscreenElement) {
-      wrapperRef.current?.requestFullscreen();
-    } else {
-      document.exitFullscreen();
+    if (document.fullscreenElement) {
+      document.exitFullscreen().catch(() => {});
+      return;
    }
-  }, []);
+    if (fallbackFullscreen) {
+      setFallbackFullscreen(false);
+      return;
+    }
+    const el = wrapperRef.current;
+    if (!el) return;
+    if (el.requestFullscreen) {
+      el.requestFullscreen().catch(() => setFallbackFullscreen(true));
+    } else {
+      setFallbackFullscreen(true);
+    }
+  }, [fallbackFullscreen]);

  // Calculate center if not provided
  const mapCenter: [number, number] = center || (() => {
@@ -64,7 +94,7 @@ export function SchoolMap({ schools, center, zoom = 13, referencePoint, onMarker
  })();

  return (
-    <div ref={wrapperRef} className={`${styles.mapWrapper} ${isFullscreen ? styles.fullscreen : ''}`}>
+    <div ref={wrapperRef} className={`${styles.mapWrapper} ${isFullscreen ? styles.fullscreen : ''} ${fallbackFullscreen ? styles.fsFallback : ''}`}>
      <button
        className={styles.fullscreenBtn}
        onClick={toggleFullscreen}
@@ -254,3 +254,10 @@
    justify-content: center;
  }
 }
+
+/* GIAS "Open, but proposed to close" marker */
+.attrClosing {
+  background: #fdf6e3;
+  color: #8a6200;
+  border: 1px solid #e2c96f;
+}
@@ -9,7 +9,7 @@
 */

 import type { School } from '@/lib/types';
-import { formatPercentage, calculateTrend, getPhaseStyle, schoolUrl, buildOfstedListBadge, formatAgeRange } from '@/lib/utils';
+import { formatPercentage, calculateTrend, getPhaseStyle, schoolUrl, buildOfstedListBadge, formatAgeRange, isProposedToClose } from '@/lib/utils';
 import styles from './SchoolRow.module.css';

 interface SchoolRowProps {
@@ -78,6 +78,9 @@ export function SchoolRow({
          {school.age_range && <span className={styles.attr}>{formatAgeRange(school.age_range)}</span>}
          {showDenomination && <span className={styles.attr}>{school.religious_denomination}</span>}
          {showGender && <span className={styles.attr}>{school.gender}</span>}
+          {isProposedToClose(school) && (
+            <span className={`${styles.attr} ${styles.attrClosing}`}>⚠ Proposed to close</span>
+          )}
        </div>

        {/* Line 3: Key stats */}
@@ -1099,3 +1099,18 @@
        padding: 0.75rem;
    }
 }
+
+/* GIAS "Open, but proposed to close" notice strip */
+.closingStrip {
+  background: #fdf6e3;
+  border-left: 4px solid #e2c96f;
+  border-radius: 0 6px 6px 0;
+  padding: 0.55rem 0.9rem;
+  margin: 0.5rem 0;
+  font-size: 0.88rem;
+  color: #6e5a00;
+  max-width: 68ch;
+}
+.closingStrip strong {
+  color: #8a6200;
+}
@@ -23,7 +23,7 @@ import type {
  SchoolAdmissions, SenDetail, Phonics,
  SchoolDeprivation, SchoolFinance, NationalAverages,
 } from '@/lib/types';
-import { formatPercentage, formatProgress, formatAcademicYear, formatAgeRange } from '@/lib/utils';
+import { formatPercentage, formatProgress, formatAcademicYear, formatAgeRange, isProposedToClose } from '@/lib/utils';
 import { DeltaChip } from './DeltaChip';
 import { track, getNavigationSource } from '@/lib/analytics';
 import styles from './SecondarySchoolDetailView.module.css';
@@ -98,7 +98,8 @@ export function SecondarySchoolDetailView({

  const secondaryAvg = nationalAvg?.secondary ?? {};

-  const hasSixthForm = schoolInfo.age_range?.includes('18') ?? false;
+  // GIAS OfficialSixthForm flag; missing (pipeline not yet re-run) => false.
+  const hasSixthForm = schoolInfo.has_sixth_form ?? false;
  const hasFinance = finance != null && finance.per_pupil_spend != null;
  const hasDeprivation = deprivation != null && deprivation.idaci_decile != null;
  const hasLocation = schoolInfo.latitude != null && schoolInfo.longitude != null;
@@ -236,6 +237,12 @@ export function SecondarySchoolDetailView({
                </span>
              )}
            </div>
+            {isProposedToClose(schoolInfo) && (
+              <div className={styles.closingStrip} role="note">
+                <strong>⚠ Proposed to close</strong> — this school is proposed for closure,
+                check with the local authority before applying.
+              </div>
+            )}
            {schoolInfo.address && (
              <p className={styles.address}>
                {schoolInfo.address}{schoolInfo.postcode && `, ${schoolInfo.postcode}`}
@@ -266,3 +266,9 @@
    justify-content: center;
  }
 }
+
+.closingTag {
+  background: #fdf6e3;
+  color: #8a6200;
+  border: 1px solid #e2c96f;
+}
@@ -11,7 +11,7 @@
 'use client';

 import type { School } from '@/lib/types';
-import { buildOfstedListBadge, getPhaseStyle, schoolUrl, formatAgeRange } from '@/lib/utils';
+import { buildOfstedListBadge, getPhaseStyle, schoolUrl, formatAgeRange, isProposedToClose } from '@/lib/utils';
 import styles from './SecondarySchoolRow.module.css';

 function detectAdmissionsTag(school: School): string | null {
@@ -23,7 +23,8 @@ function detectAdmissionsTag(school: School): string | null {
 }

 function hasSixthForm(school: School): boolean {
-  return school.age_range?.includes('18') ?? false;
+  // GIAS OfficialSixthForm flag; missing (pipeline not yet re-run) => false.
+  return school.has_sixth_form ?? false;
 }

 interface SecondarySchoolRowProps {
@@ -96,6 +97,9 @@ export function SecondarySchoolRow({
              {admissionsTag}
            </span>
          )}
+          {isProposedToClose(school) && (
+            <span className={`${styles.provisionTag} ${styles.closingTag}`}>⚠ Proposed to close</span>
+          )}
        </div>

        {/* Line 3: KS4 stats */}
@@ -0,0 +1,18 @@
+.moreMeasures {
+  margin-top: 0.5rem;
+  border-top: 1px solid var(--border-light);
+  padding-top: 0.75rem;
+}
+
+.moreMeasures summary {
+  cursor: pointer;
+  font-weight: 600;
+  font-size: 0.88rem;
+  color: var(--accent-coral-dark);
+}
+
+.stripNote {
+  font-size: 0.78rem;
+  color: var(--text-muted);
+  margin: 0.5rem 0 0;
+}
@@ -0,0 +1,294 @@
+/**
+ * How children do academically — tier-1 dot strips anchored on official
+ * England averages, tier-2 "More measures" one tap away, equity row against
+ * the computed state-school benchmark. Copy verbatim from the reviewed
+ * mockups; teacher-assessed measures are labelled as such.
+ */
+
+'use client';
+
+import { latestValues, verdict } from '@/lib/compareLogic';
+import type { Benchmarks, ComparisonData, NationalAverages, School } from '@/lib/types';
+import { DotStrip } from '@/components/DotStrip';
+import { Cell, Chip, RowLabel, Section, SectionGrid, sectionStyles as s } from './sectionShared';
+import styles from './CompareAcademics.module.css';
+
+interface StripSpec {
+  label: string;
+  metric: string;
+  anchorKey?: string;
+  tip?: string;
+  min?: number;
+  max?: number;
+  unit?: string;
+}
+
+const TIER1_PRIMARY: StripSpec[] = [
+  {
+    label: 'Reading, writing & maths — expected standard',
+    metric: 'rwm_expected_pct',
+    anchorKey: 'rwm_expected_pct',
+    tip: '% of Year 6 pupils reaching the expected standard in reading, writing and maths.',
+  },
+  { label: 'Reading', metric: 'reading_expected_pct', anchorKey: 'reading_expected_pct' },
+  {
+    label: 'Writing (teacher-assessed)',
+    metric: 'writing_expected_pct',
+    anchorKey: 'writing_expected_pct',
+    tip: 'Writing is assessed by teachers, not tested.',
+  },
+  { label: 'Maths', metric: 'maths_expected_pct', anchorKey: 'maths_expected_pct' },
+  {
+    label: 'Working at a higher standard than expected',
+    metric: 'rwm_high_pct',
+    anchorKey: 'rwm_high_pct',
+    tip: 'A high score in the reading and maths tests plus “greater depth” in teacher-assessed writing.',
+  },
+];
+
+const TIER2_PRIMARY: StripSpec[] = [
+  {
+    label: 'Grammar, punctuation & spelling — expected standard',
+    metric: 'gps_expected_pct',
+    anchorKey: 'gps_expected_pct',
+  },
+  {
+    label: 'Science — expected standard (teacher-assessed)',
+    metric: 'science_expected_pct',
+    anchorKey: 'science_expected_pct',
+    tip: 'Teacher-assessed, like writing — there has been no KS2 science test since 2009, so comparisons are indicative.',
+  },
+  {
+    label: 'Average scaled score — reading',
+    metric: 'reading_avg_score',
+    anchorKey: 'reading_avg_score',
+    min: 100,
+    max: 120,
+    unit: '',
+  },
+  {
+    label: 'Average scaled score — maths',
+    metric: 'maths_avg_score',
+    anchorKey: 'maths_avg_score',
+    min: 100,
+    max: 120,
+    unit: '',
+  },
+  {
+    label: 'Average scaled score — grammar, punctuation & spelling',
+    metric: 'gps_avg_score',
+    anchorKey: 'gps_avg_score',
+    min: 100,
+    max: 120,
+    unit: '',
+  },
+];
+
+function Strip({
+  spec,
+  data,
+  urns,
+  schoolNames,
+  national,
+}: {
+  spec: StripSpec;
+  data: Record<string, ComparisonData>;
+  urns: number[];
+  schoolNames: string[];
+  national: Record<string, number> | undefined;
+}) {
+  const values = latestValues(data, urns, spec.metric).map((v) =>
+    v != null ? Math.round(v) : null,
+  );
+  const anchorValue = spec.anchorKey ? national?.[spec.anchorKey] : undefined;
+  const anchor =
+    anchorValue != null
+      ? { value: anchorValue, label: `England ${Math.round(anchorValue)}${spec.unit ?? '%'}` }
+      : null;
+  if (values.every((v) => v == null)) return null;
+  return (
+    <DotStrip
+      label={spec.label}
+      values={values}
+      schoolNames={schoolNames}
+      anchor={anchor}
+      min={spec.min ?? 0}
+      max={spec.max ?? 100}
+      unit={spec.unit ?? '%'}
+      tip={spec.tip}
+    />
+  );
+}
+
+export function CompareAcademics({
+  schools,
+  data,
+  nationalAverages,
+  benchmarks,
+  isSecondary: propIsSecondary,
+}: {
+  schools: School[];
+  data: Record<string, ComparisonData>;
+  nationalAverages?: NationalAverages;
+  benchmarks?: Benchmarks;
+  isSecondary?: boolean;
+}) {
+  const urns = schools.map((school) => school.urn);
+  const schoolNames = schools.map((school) => school.school_name);
+  const isSecondary = propIsSecondary !== undefined ? propIsSecondary : schools.some(
+    (school) => data[String(school.urn)]?.school_info?.attainment_8_score != null,
+  );
+
+  if (isSecondary) {
+    const att8 = latestValues(data, urns, 'attainment_8_score');
+    const banding = urns.map((urn) => {
+      const rows = data[String(urn)]?.yearly_data ?? [];
+      for (let i = rows.length - 1; i >= 0; i--) {
+        if (rows[i].progress_8_banding) return rows[i].progress_8_banding as string;
+      }
+      return null;
+    });
+    const grade5 = latestValues(data, urns, 'english_maths_strong_pass_pct');
+    const ebacc = latestValues(data, urns, 'ebacc_entry_pct');
+    const att8Anchor = nationalAverages?.secondary?.attainment_8_score;
+
+    return (
+      <Section
+        title="How students do academically"
+        how="GCSE results (latest year). Attainment 8 averages performance across eight subjects; Progress 8 shows how much progress students make compared with similar students nationally — the wording is DfE's own banding."
+      >
+        <SectionGrid schools={schools}>
+          <RowLabel tip="Average Attainment 8 score across eight GCSE subjects.">Attainment 8</RowLabel>
+          {schools.map((school, i) => (
+            <Cell key={school.urn} school={school} index={i}>
+              {att8[i] != null ? (
+                <>
+                  <span className={s.big}>{(att8[i] as number).toFixed(1)}</span>
+                  {att8Anchor != null && (
+                    <span className={s.small}>England average {att8Anchor.toFixed(1)}</span>
+                  )}
+                </>
+              ) : (
+                <span className={s.small}>No data</span>
+              )}
+            </Cell>
+          ))}
+
+          <RowLabel tip="DfE's own plain-English Progress 8 label.">Progress 8</RowLabel>
+          {schools.map((school, i) => (
+            <Cell key={school.urn} school={school} index={i}>
+              {banding[i] ? (
+                <Chip
+                  tone={
+                    /well above|above/i.test(banding[i] as string)
+                      ? 'good'
+                      : /well below|below/i.test(banding[i] as string)
+                        ? 'warn'
+                        : 'neutral'
+                  }
+                >
+                  {banding[i]}
+                </Chip>
+              ) : (
+                <span className={s.small}>No data</span>
+              )}
+            </Cell>
+          ))}
+
+          <RowLabel tip="% achieving grade 5 or above in both English and maths GCSEs.">
+            Grade 5+ in English &amp; maths
+          </RowLabel>
+          {schools.map((school, i) => (
+            <Cell key={school.urn} school={school} index={i}>
+              {grade5[i] != null ? `${Math.round(grade5[i] as number)}%` : <span className={s.small}>No data</span>}
+            </Cell>
+          ))}
+
+          <RowLabel tip="% entering the English Baccalaureate subject combination.">EBacc entry</RowLabel>
+          {schools.map((school, i) => (
+            <Cell key={school.urn} school={school} index={i}>
+              {ebacc[i] != null ? `${Math.round(ebacc[i] as number)}%` : <span className={s.small}>No data</span>}
+            </Cell>
+          ))}
+        </SectionGrid>
+      </Section>
+    );
+  }
+
+  const national = nationalAverages?.primary;
+  const disadvantaged = latestValues(data, urns, 'rwm_expected_disadvantaged_pct');
+  const disadvantagedAnchor = benchmarks?.primary?.disadvantaged_rwm_expected_pct ?? null;
+
+  return (
+    <Section
+      title="How children do academically"
+      how="Results from national tests and teacher assessments at the end of Year 6 — writing is assessed by teachers, not tested. Each line runs from 0–100%; the grey tick marks the England average, so dots to its right are above average."
+    >
+      <div className={s.card}>
+        {TIER1_PRIMARY.map((spec) => (
+          <Strip
+            key={spec.metric}
+            spec={spec}
+            data={data}
+            urns={urns}
+            schoolNames={schoolNames}
+            national={national}
+          />
+        ))}
+
+        <details className={styles.moreMeasures}>
+          <summary>More measures — grammar, punctuation &amp; spelling, science, average scaled scores</summary>
+          {TIER2_PRIMARY.map((spec) => (
+            <Strip
+              key={spec.metric}
+              spec={spec}
+              data={data}
+              urns={urns}
+              schoolNames={schoolNames}
+              national={national}
+            />
+          ))}
+          <p className={styles.stripNote}>
+            The scaled-score strips show the 100–120 window of the full 80–120 range; 100 is the
+            expected standard. Where an England tick is missing, the official figure isn&apos;t in
+            our dataset yet.
+          </p>
+        </details>
+      </div>
+
+      {disadvantaged.some((v) => v != null) && (
+        <SectionGrid schools={schools}>
+          <RowLabel tip="% of disadvantaged pupils (free school meals in the last 6 years, or looked after by the local authority) reaching the expected standard. Benchmark computed across state schools in our dataset. Based on smaller pupil groups, so a single pupil can move a school's figure noticeably.">
+            Children from lower-income families
+          </RowLabel>
+          {schools.map((school, i) => {
+            const value = disadvantaged[i];
+            return (
+              <Cell key={school.urn} school={school} index={i}>
+                {value != null ? (
+                  <>
+                    <span className={s.big} style={{ fontSize: '1.1rem' }}>
+                      {Math.round(value)}%
+                    </span>{' '}
+                    {disadvantagedAnchor != null && (
+                      <Chip tone={verdict(value, disadvantagedAnchor, 5) === 'below' ? 'warn' : 'good'}>
+                        {verdict(value, disadvantagedAnchor, 5) === 'above' &&
+                          `Well above the ${Math.round(disadvantagedAnchor)}% state-school average`}
+                        {verdict(value, disadvantagedAnchor, 5) === 'close' &&
+                          `Around the ${Math.round(disadvantagedAnchor)}% state-school average`}
+                        {verdict(value, disadvantagedAnchor, 5) === 'below' &&
+                          `Below the ${Math.round(disadvantagedAnchor)}% state-school average`}
+                      </Chip>
+                    )}
+                  </>
+                ) : (
+                  <span className={s.small}>No data</span>
+                )}
+              </Cell>
+            );
+          })}
+        </SectionGrid>
+      )}
+    </Section>
+  );
+}
@@ -0,0 +1,130 @@
+/**
+ * Getting a place — admissions framed the way the expert review requires:
+ * total applications are "named on N forms" (any preference rank, not
+ * head-to-head), one consistent chip metric (first-preference success),
+ * equal-preference and offers-vs-intake explanations up front.
+ */
+
+'use client';
+
+import { summariseAdmissions } from '@/lib/compareLogic';
+import type { ComparisonData, School } from '@/lib/types';
+import { CHART_COLORS } from '@/lib/utils';
+import { Cell, Chip, Measure, Section, SectionGrid, sectionStyles as s } from './sectionShared';
+
+export function CompareAdmissions({
+  schools,
+  data,
+}: {
+  schools: School[];
+  data: Record<string, ComparisonData>;
+}) {
+  const rows = schools.map((school) => data[String(school.urn)]?.admissions ?? null);
+  const anyData = rows.some(Boolean);
+  const entryYear = rows.find(Boolean)?.year;
+  const entryLabel = entryYear
+    ? `September ${String(entryYear).slice(0, 4)} entry`
+    : 'the most recent admissions round';
+
+  if (!anyData) {
+    return (
+      <Section title="Getting a place" how="No admissions data is available for these schools yet.">
+        <></>
+      </Section>
+    );
+  }
+
+  return (
+    <Section
+      title="Getting a place"
+      how={
+        <>
+          From the most recent admissions round ({entryLabel}). &quot;First choice&quot; means
+          families who ranked the school top of their application form — officially a &quot;first
+          preference&quot;. Schools never see your ranking: places are decided only by the
+          school&apos;s admission criteria, so listing a school lower down never hurts your chances.
+          These are National Offer Day offers — waiting lists and appeals can change the final
+          intake.
+        </>
+      }
+    >
+      <SectionGrid schools={schools}>
+        <Measure
+          tip="How many application forms named the school at any preference rank — not the number of families competing head-to-head for a place."
+          label="Interest in the school"
+        >
+        {schools.map((school, i) => {
+          const a = rows[i];
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {a?.total_applications != null && a?.places_offered != null ? (
+                <>
+                  Named on <strong>{a.total_applications.toLocaleString('en-GB')}</strong> forms ·{' '}
+                  <strong>{a.places_offered.toLocaleString('en-GB')}</strong> places
+                </>
+              ) : (
+                <span className={s.small}>No data</span>
+              )}
+            </Cell>
+          );
+        })}
+
+        </Measure>
+
+        <Measure label="First-choice families offered a place">
+        {schools.map((school, i) => {
+          const summary = summariseAdmissions(rows[i]);
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {summary.firstPrefPct != null ? (
+                <>
+                  <strong>{summary.firstPrefPct}%</strong>{' '}
+                  {summary.chip && summary.chip.tone === 'warn' && (
+                    <Chip tone="warn">{summary.chip.text}</Chip>
+                  )}
+                  <span className={s.barMini}>
+                    <i
+                      style={{
+                        width: `${summary.firstPrefPct}%`,
+                        background: CHART_COLORS[i % CHART_COLORS.length],
+                      }}
+                    />
+                  </span>
+                </>
+              ) : (
+                <span className={s.small}>No data</span>
+              )}
+            </Cell>
+          );
+        })}
+
+        </Measure>
+
+        <Measure label="What this means">
+        {schools.map((school, i) => {
+          const a = rows[i];
+          const summary = summariseAdmissions(a);
+          let text: string | null = null;
+          if (summary.firstPrefPct != null) {
+            if (summary.firstPrefPct >= 100) {
+              text = `Every family who put ${school.school_name} first got a place.`;
+            } else if (summary.firstPrefPct >= 90) {
+              text = `Nearly every family who put ${school.school_name} first got a place.`;
+            } else if (a?.oversubscribed) {
+              text =
+                'More first-choice applications than places — check the school’s admission criteria (for most non-faith primaries, distance decides).';
+            } else {
+              text = `${summary.firstPrefPct}% of first-choice families received an offer.`;
+            }
+          }
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {text ? <span className={s.small}>{text}</span> : <span className={s.small}>—</span>}
+            </Cell>
+          );
+        })}
+        </Measure>
+      </SectionGrid>
+    </Section>
+  );
+}
@@ -0,0 +1,193 @@
+/**
+ * At a glance — the short version of every section below it. Copy verbatim
+ * from the reviewed mockups. Report-card cells summarise by counting graded
+ * areas (best first) and always NAME problem areas; safeguarding is a
+ * separate line, never a count.
+ */
+
+'use client';
+
+import {
+  latestValues,
+  ofstedDisplay,
+  summariseAdmissions,
+  verdict,
+  type ReportCardSummary,
+} from '@/lib/compareLogic';
+import type { Benchmarks, ComparisonData, NationalAverages, School } from '@/lib/types';
+import { Cell, Chip, Measure, Section, SectionGrid, sectionStyles as s } from './sectionShared';
+
+function ReportCardChips({ summary }: { summary: ReportCardSummary }) {
+  return (
+    <>
+      <strong style={{ fontSize: '0.9rem' }}>Report card</strong>
+      <span className={s.chipStack}>
+        {summary.counts.map((c) => (
+          <Chip key={c.label} tone={c.label === 'Expected standard' ? 'neutral' : 'good'}>
+            {c.count} area{c.count === 1 ? '' : 's'} {c.label}
+          </Chip>
+        ))}
+        {summary.problems.map((p) => (
+          <Chip key={p.areaLabel} tone={p.label === 'Urgent improvement' ? 'bad' : 'warn'}>
+            {p.areaLabel}: {p.label}
+          </Chip>
+        ))}
+      </span>
+      <span className={s.small}>
+        {summary.allClear && 'No areas need attention · '}
+        {summary.safeguarding === 'met' && 'Safeguarding met'}
+        {summary.safeguarding === 'not_met' && 'Safeguarding not met'}
+      </span>
+    </>
+  );
+}
+
+export function CompareAtAGlance({
+  schools,
+  data,
+  nationalAverages,
+  benchmarks,
+  isSecondary: propIsSecondary,
+}: {
+  schools: School[];
+  data: Record<string, ComparisonData>;
+  nationalAverages?: NationalAverages;
+  benchmarks?: Benchmarks;
+  isSecondary?: boolean;
+}) {
+  const urns = schools.map((school) => school.urn);
+  const isSecondary = propIsSecondary !== undefined ? propIsSecondary : schools.some(
+    (school) => data[String(school.urn)]?.school_info?.attainment_8_score != null,
+  );
+  const headlineKey = isSecondary ? 'attainment_8_score' : 'rwm_expected_pct';
+  const headlineValues = latestValues(data, urns, headlineKey);
+  const anchor = isSecondary
+    ? nationalAverages?.secondary?.attainment_8_score
+    : nationalAverages?.primary?.rwm_expected_pct;
+  const medianPupils = isSecondary
+    ? benchmarks?.secondary?.median_pupils
+    : benchmarks?.primary?.median_pupils;
+
+  return (
+    <Section title="At a glance" how="The short version — each row below is explained in its own section further down.">
+      <SectionGrid schools={schools}>
+        <Measure label="Latest Ofsted inspection">
+        {schools.map((school, i) => {
+          const display = ofstedDisplay(data[String(school.urn)]?.ofsted);
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {display.kind === 'report_card' && <ReportCardChips summary={display.summary} />}
+              {(display.kind === 'graded' || display.kind === 'carried_forward') && (
+                <>
+                  <span className={`${s.badge} ${display.grade <= 2 ? s.badgeGood : display.grade === 3 ? s.badgeWarn : s.badgeBad}`}>
+                    {display.gradeLabel}
+                  </span>
+                  {display.carriedForward && <span className={s.small}>Grade carried forward</span>}
+                </>
+              )}
+              {display.kind === 'transitional' && (
+                <>
+                  <span className={s.badge} style={{ backgroundColor: '#e2e8f0', color: '#475569' }}>
+                    No overall grade
+                  </span>
+                  <span className={s.small}>Sub-judgements only</span>
+                </>
+              )}
+              {display.kind === 'none' && <span className={s.small}>No inspection in our dataset</span>}
+            </Cell>
+          );
+        })}
+        </Measure>
+
+        <Measure
+          tip={
+            isSecondary
+              ? 'Average Attainment 8 score across GCSE subjects (latest year).'
+              : '% of Year 6 pupils reaching the expected standard in reading, writing and maths (latest year).'
+          }
+          label={isSecondary ? 'Attainment 8 score' : 'Children reaching the expected standard'}
+        >
+        {schools.map((school, i) => {
+          const value = headlineValues[i];
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {value != null ? (
+                <>
+                  <span className={s.big}>{isSecondary ? value.toFixed(1) : `${Math.round(value)}%`}</span>{' '}
+                  {anchor != null && (
+                    <Chip
+                      tone={
+                        verdict(value, anchor) === 'above'
+                          ? 'good'
+                          : verdict(value, anchor) === 'below'
+                            ? 'warn'
+                            : 'neutral'
+                      }
+                    >
+                      {verdict(value, anchor) === 'above' && 'Above England average'}
+                      {verdict(value, anchor) === 'close' && 'Close to England average'}
+                      {verdict(value, anchor) === 'below' && 'Below England average'}
+                    </Chip>
+                  )}
+                  {anchor != null && (
+                    <span className={s.small}>
+                      England average {isSecondary ? anchor.toFixed(1) : `${Math.round(anchor)}%`}
+                    </span>
+                  )}
+                </>
+              ) : (
+                <span className={s.small}>No data</span>
+              )}
+            </Cell>
+          );
+        })}
+        </Measure>
+
+        <Measure label="Getting a place">
+        {schools.map((school, i) => {
+          const summary = summariseAdmissions(data[String(school.urn)]?.admissions);
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {summary.chip ? (
+                <>
+                  <Chip tone={summary.chip.tone}>{summary.chip.text}</Chip>
+                  {summary.interest && <span className={s.small}>{summary.interest}</span>}
+                </>
+              ) : (
+                <span className={s.small}>No admissions data</span>
+              )}
+            </Cell>
+          );
+        })}
+        </Measure>
+
+        <Measure label="Size">
+        {schools.map((school, i) => {
+          const census = data[String(school.urn)]?.census;
+          const pupils = census?.total_pupils ?? school.total_pupils ?? null;
+          let sizeNote: string | null = null;
+          if (pupils != null && medianPupils != null) {
+            if (pupils >= medianPupils * 1.5) sizeNote = 'Much larger than average';
+            else if (pupils >= medianPupils * 1.1) sizeNote = 'Larger than average';
+            else if (pupils <= medianPupils * 0.66) sizeNote = 'Much smaller than average';
+            else if (pupils <= medianPupils * 0.9) sizeNote = 'Smaller than average';
+            else sizeNote = 'About average size';
+          }
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {pupils != null ? (
+                <>
+                  {pupils.toLocaleString('en-GB')} pupils
+                  {sizeNote && <span className={s.small}>{sizeNote}</span>}
+                </>
+              ) : (
+                <span className={s.small}>No data</span>
+              )}
+            </Cell>
+          );
+        })}
+        </Measure>
+      </SectionGrid>
+    </Section>
+  );
+}
@@ -0,0 +1,197 @@
+/**
+ * Who goes there — the school's community from the latest census plus GIAS
+ * facts. Benchmark chips use the computed state-school averages and must
+ * carry their provenance wording (never "England average" for computed
+ * figures). Copy verbatim from the reviewed mockups.
+ */
+
+'use client';
+
+import { verdict } from '@/lib/compareLogic';
+import type { Benchmarks, ComparisonData, School } from '@/lib/types';
+import { Cell, Chip, Measure, Section, SectionGrid, sectionStyles as s } from './sectionShared';
+
+function pctSplit(part: number | null | undefined, total: number | null | undefined): string | null {
+  if (part == null || total == null || total === 0) return null;
+  return `${Math.round((part / total) * 100)}%`;
+}
+
+export function CompareCommunity({
+  schools,
+  data,
+  benchmarks,
+  isSecondary: propIsSecondary,
+}: {
+  schools: School[];
+  data: Record<string, ComparisonData>;
+  benchmarks?: Benchmarks;
+  isSecondary?: boolean;
+}) {
+  const isSecondary = propIsSecondary !== undefined ? propIsSecondary : schools.some(
+    (school) => data[String(school.urn)]?.school_info?.attainment_8_score != null,
+  );
+  const bench = isSecondary ? benchmarks?.secondary : benchmarks?.primary;
+
+  const fsmChip = (value: number | null) => {
+    const anchor = bench?.fsm_pct ?? bench?.disadvantaged_pct ?? null;
+    if (value == null || anchor == null) return null;
+    const v = verdict(value, anchor, 3);
+    return (
+      <Chip tone="neutral">
+        {v === 'above' && `Above the state-school average (${Math.round(anchor)}%)`}
+        {v === 'close' && `About the state-school average (${Math.round(anchor)}%)`}
+        {v === 'below' && `Below the state-school average (${Math.round(anchor)}%)`}
+      </Chip>
+    );
+  };
+
+  return (
+    <Section
+      title="Who goes there"
+      how="The school's community, from the latest school census. State-school averages are computed from our dataset and shown for context — there's no “right” number here."
+    >
+      <SectionGrid schools={schools}>
+        <Measure label="Pupils on roll">
+        {schools.map((school, i) => {
+          const info = data[String(school.urn)]?.school_info as (School & { gias_total_pupils?: number | null; capacity?: number | null }) | undefined;
+          const census = data[String(school.urn)]?.census;
+          const pupils = census?.total_pupils ?? info?.gias_total_pupils ?? null;
+          const capacity = info?.capacity ?? null;
+          let capNote: string | null = null;
+          if (pupils != null && capacity != null && capacity > 0) {
+            capNote =
+              pupils >= capacity
+                ? `${capacity.toLocaleString('en-GB')} places — at or above capacity`
+                : `of ${capacity.toLocaleString('en-GB')} places (${Math.round((pupils / capacity) * 100)}% full)`;
+          }
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {pupils != null ? (
+                <>
+                  {pupils.toLocaleString('en-GB')}
+                  {capNote && <span className={s.small}>{capNote}</span>}
+                </>
+              ) : (
+                <span className={s.small}>No data</span>
+              )}
+            </Cell>
+          );
+        })}
+        </Measure>
+
+        <Measure label="Girls / boys">
+        {schools.map((school, i) => {
+          const census = data[String(school.urn)]?.census;
+          const girls = pctSplit(census?.female_pupils, census?.total_pupils);
+          const boys = pctSplit(census?.male_pupils, census?.total_pupils);
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {girls && boys ? `${girls} / ${boys}` : <span className={s.small}>No data</span>}
+            </Cell>
+          );
+        })}
+        </Measure>
+
+        <Measure
+          tip="% of pupils eligible for free school meals — a common measure of how many pupils come from lower-income families. Benchmark computed across state schools in our dataset."
+          label="Free school meals"
+        >
+        {schools.map((school, i) => {
+          const fsm = data[String(school.urn)]?.census?.fsm_pct ?? null;
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {fsm != null ? (
+                <>
+                  {Math.round(fsm)}% {fsmChip(fsm)}
+                </>
+              ) : (
+                <span className={s.small}>No data</span>
+              )}
+            </Cell>
+          );
+        })}
+        </Measure>
+
+        <Measure
+          tip="% of pupils whose first language is known or believed to be other than English. State-school average computed from our dataset."
+          label="English as an additional language"
+        >
+        {schools.map((school, i) => {
+          const eal = data[String(school.urn)]?.census?.eal_pct ?? null;
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {eal != null ? `${Math.round(eal)}%` : <span className={s.small}>No data</span>}
+            </Cell>
+          );
+        })}
+        </Measure>
+
+        <Measure
+          tip="% of pupils receiving SEN support (not including EHC plans). A high figure can mean the school hosts specialist provision — often a strength, not a warning sign. State-school average computed from our dataset."
+          label="Extra learning support (SEN)"
+        >
+        {schools.map((school, i) => {
+          const rows = data[String(school.urn)]?.yearly_data ?? [];
+          let sen: number | null = null;
+          for (let r = rows.length - 1; r >= 0; r--) {
+            if (rows[r].sen_support_pct != null) {
+              sen = rows[r].sen_support_pct;
+              break;
+            }
+          }
+          const high =
+            sen != null && bench?.sen_support_pct != null && sen >= bench.sen_support_pct * 1.75;
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {sen != null ? (
+                <>
+                  {Math.round(sen)}% {high && <Chip tone="neutral">Well above average</Chip>}
+                </>
+              ) : (
+                <span className={s.small}>No data</span>
+              )}
+            </Cell>
+          );
+        })}
+        </Measure>
+
+        <Measure label="Faith character">
+        {schools.map((school, i) => {
+          const info = data[String(school.urn)]?.school_info;
+          const faith = info?.religious_denomination;
+          const none = !faith || faith === 'Does not apply' || faith === 'None';
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {none ? 'None' : faith}
+            </Cell>
+          );
+        })}
+        </Measure>
+
+        <Measure label="Ages">
+        {schools.map((school, i) => {
+          const info = data[String(school.urn)]?.school_info;
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {info?.age_range || <span className={s.small}>No data</span>}
+            </Cell>
+          );
+        })}
+        </Measure>
+
+        <Measure label="Run by">
+        {schools.map((school, i) => {
+          const info = data[String(school.urn)]?.school_info;
+          const trust = info?.trust_name;
+          const la = info?.local_authority ?? school.local_authority;
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {trust ? trust : la ? `${la} council` : <span className={s.small}>No data</span>}
+            </Cell>
+          );
+        })}
+        </Measure>
+      </SectionGrid>
+    </Section>
+  );
+}
@@ -0,0 +1,237 @@
+/**
+ * Ofsted section — one visual grammar for inspection detail across all
+ * three regimes (legacy graded, interim carried-forward, renewed-framework
+ * report card). Copy comes verbatim from the reviewed mockups.
+ */
+
+'use client';
+
+import {
+  OFSTED_LEGACY_GRADES,
+  ofstedDisplay,
+  rcAreaLabel,
+  type OfstedDisplay,
+} from '@/lib/compareLogic';
+import type { ComparisonData, OfstedInspection, School } from '@/lib/types';
+import { Cell, Chip, Measure, Section, SectionGrid, sectionStyles as s } from './sectionShared';
+
+const GRADE_TONE: Record<number, 'good' | 'warn' | 'bad'> = {
+  1: 'good',
+  2: 'good',
+  3: 'warn',
+  4: 'bad',
+};
+
+const RC_CODE_TONE = (code: number): 'good' | 'warn' | 'bad' | 'neutral' =>
+  code <= 2 ? 'good' : code === 3 ? 'neutral' : code === 4 ? 'warn' : 'bad';
+
+function formatInspectionDate(iso: string | null): string {
+  if (!iso) return '—';
+  const d = new Date(iso);
+  if (Number.isNaN(d.getTime())) return '—';
+  return d.toLocaleDateString('en-GB', { day: 'numeric', month: 'short', year: 'numeric' });
+}
+
+function yearsSince(iso: string | null): number | null {
+  if (!iso) return null;
+  const d = new Date(iso);
+  if (Number.isNaN(d.getTime())) return null;
+  return (Date.now() - d.getTime()) / (365.25 * 24 * 3600 * 1000);
+}
+
+function ResultCell({ display }: { display: OfstedDisplay }) {
+  if (display.kind === 'none') {
+    return <span className={s.small}>No inspection outcome in our dataset</span>;
+  }
+  if (display.kind === 'report_card') {
+    return (
+      <>
+        <strong style={{ fontSize: '0.9rem' }}>Report card</strong>
+        <span className={s.small}>New-style inspection — no overall grade is given</span>
+      </>
+    );
+  }
+  if (display.kind === 'transitional') {
+    return (
+      <>
+        <span className={s.badge} style={{ backgroundColor: '#e2e8f0', color: '#475569' }}>
+          No overall grade
+        </span>
+        <span className={s.small}>
+          Inspected under transitional framework (sub-judgements only)
+        </span>
+      </>
+    );
+  }
+  return (
+    <>
+      <span className={`${s.badge} ${display.grade <= 2 ? s.badgeGood : display.grade === 3 ? s.badgeWarn : s.badgeBad}`}>
+        {display.gradeLabel}
+      </span>
+      <span className={s.small}>
+        {display.carriedForward
+          ? 'Grade carried forward from an earlier inspection (ungraded visit since)'
+          : 'Overall grade (older-style inspection)'}
+      </span>
+    </>
+  );
+}
+
+function JudgementDetailCell({
+  ofsted,
+  display,
+  schoolName,
+}: {
+  ofsted: OfstedInspection;
+  display: OfstedDisplay;
+  schoolName: string;
+}) {
+  if (display.kind === 'report_card') {
+    const entries = Object.entries(ofsted.report_card ?? {});
+    return (
+      <div className={s.rcList}>
+        {entries.map(([key, entry]) => (
+          <div key={key} className={s.rcRow}>
+            <span className={s.rcArea}>{rcAreaLabel(key)}</span>
+            <Chip tone={RC_CODE_TONE(entry.code)}>{entry.label}</Chip>
+          </div>
+        ))}
+        {ofsted.rc_safeguarding_met != null && (
+          <div className={s.rcRow}>
+            <span className={s.rcArea}>Safeguarding</span>
+            <Chip tone={ofsted.rc_safeguarding_met ? 'good' : 'bad'}>
+              {ofsted.rc_safeguarding_met ? 'Met' : 'Not met'}
+            </Chip>
+          </div>
+        )}
+      </div>
+    );
+  }
+
+  const legacyAreas: Array<[string, number | null]> = [
+    ['Quality of education', ofsted.quality_of_education],
+    ['Behaviour & attitudes', ofsted.behaviour_attitudes],
+    ['Personal development', ofsted.personal_development],
+    ['Leadership & management', ofsted.leadership_management],
+    ['Early years provision', ofsted.early_years_provision],
+  ];
+  const published = legacyAreas.filter(([, grade]) => grade != null);
+
+  if (published.length === 0) {
+    return (
+      <span className={s.small}>
+        We don&apos;t hold area-by-area detail for this inspection — see {schoolName}&apos;s
+        Ofsted page for the full report.
+      </span>
+    );
+  }
+  return (
+    <div className={s.rcList}>
+      {published.map(([label, grade]) => (
+        <div key={label} className={s.rcRow}>
+          <span className={s.rcArea}>{label}</span>
+          <Chip tone={GRADE_TONE[grade as number] ?? 'neutral'}>
+            {OFSTED_LEGACY_GRADES[grade as number] ?? String(grade)}
+          </Chip>
+        </div>
+      ))}
+    </div>
+  );
+}
+
+export function CompareOfsted({
+  schools,
+  data,
+}: {
+  schools: School[];
+  data: Record<string, ComparisonData>;
+}) {
+  const displays = schools.map((school) => ofstedDisplay(data[String(school.urn)]?.ofsted));
+  const kinds = new Set(displays.map((d) => d.kind).filter((k) => k !== 'none'));
+  const mixedRegimes = kinds.size > 1;
+
+  return (
+    <Section
+      title="Ofsted inspection"
+      how={
+        <>
+          Ofsted is the schools inspectorate. It stopped giving a single overall grade in{' '}
+          <strong>September 2024</strong>; inspections between then and November 2025 kept the
+          area-by-area judgements without an overall grade, and from <strong>November 2025</strong>{' '}
+          new inspections produce a <strong>report card</strong> rating each area of school life on
+          a five-point scale.
+          {mixedRegimes && (
+            <> A report card and an older overall grade aren&apos;t directly comparable.</>
+          )}{' '}
+          (Ofsted&apos;s &quot;Expected standard&quot; rating is unrelated to the KS2 &quot;expected
+          standard&quot; test measure further down this page.)
+        </>
+      }
+    >
+      <SectionGrid schools={schools}>
+        <Measure label="Result">
+        {schools.map((school, i) => (
+          <Cell key={school.urn} school={school} index={i}>
+            <ResultCell display={displays[i]} />
+          </Cell>
+        ))}
+        </Measure>
+
+        <Measure label="Inspected">
+        {schools.map((school, i) => {
+          const ofsted = data[String(school.urn)]?.ofsted;
+          const age = yearsSince(ofsted?.inspection_date ?? null);
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {formatInspectionDate(ofsted?.inspection_date ?? null)}{' '}
+              {age != null && age > 4 && <Chip tone="neutral">4+ years ago</Chip>}
+            </Cell>
+          );
+        })}
+
+        </Measure>
+
+        <Measure
+          tip="Older-style inspections: one rating per judgement area, where published. New-style inspections: the full report card, one rating per area of school life."
+          label="Judgement detail"
+        >
+        {schools.map((school, i) => {
+          const ofsted = data[String(school.urn)]?.ofsted;
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              {ofsted ? (
+                <JudgementDetailCell
+                  ofsted={ofsted}
+                  display={displays[i]}
+                  schoolName={school.school_name}
+                />
+              ) : (
+                <span className={s.small}>No inspection in our dataset</span>
+              )}
+            </Cell>
+          );
+        })}
+
+        </Measure>
+
+        <Measure
+          tip="Links to the school's page on ofsted.gov.uk, where all its inspection reports are listed."
+          label="Ofsted page"
+        >
+        {schools.map((school, i) => {
+          const url =
+            data[String(school.urn)]?.ofsted?.ofsted_page_url ??
+            `https://reports.ofsted.gov.uk/provider/21/${school.urn}`;
+          return (
+            <Cell key={school.urn} school={school} index={i}>
+              <a className={s.link} href={url} target="_blank" rel="noopener noreferrer">
+                {school.school_name}&apos;s Ofsted page →
+              </a>
+            </Cell>
+          );
+        })}
+        </Measure>
+      </SectionGrid>
+    </Section>
+  );
+}
@@ -0,0 +1,77 @@
+.explore {
+  margin-top: 1rem;
+}
+
+.explore summary {
+  cursor: pointer;
+  font-weight: 600;
+  color: var(--accent-coral-dark);
+  padding: 0.85rem 1.1rem;
+  background: var(--bg-card);
+  border: 1px solid var(--border-light);
+  border-radius: 8px;
+}
+
+.explore[open] summary {
+  border-radius: 8px 8px 0 0;
+}
+
+.inner {
+  border: 1px solid var(--border-light);
+  border-top: none;
+  border-radius: 0 0 8px 8px;
+  background: var(--bg-card);
+  padding: 1.25rem 1.5rem;
+}
+
+.picker {
+  display: flex;
+  align-items: center;
+  gap: 0.6rem;
+  margin-bottom: 1rem;
+  flex-wrap: wrap;
+}
+
+.picker label {
+  font-size: 0.85rem;
+  font-weight: 600;
+  color: var(--text-secondary);
+}
+
+.picker select {
+  font-family: inherit;
+  font-size: 0.9rem;
+  padding: 0.4rem 0.6rem;
+  border-radius: 8px;
+  border: 1px solid var(--border-light);
+  background: var(--bg-card);
+  color: var(--text-primary);
+  max-width: 100%;
+}
+
+.desc {
+  font-size: 0.78rem;
+  color: var(--text-muted);
+}
+
+.progressNote {
+  font-size: 0.8rem;
+  color: var(--text-muted);
+  margin: 0 0 1rem;
+}
+
+/* ComparisonChart runs Chart.js with maintainAspectRatio:false, so it fills
+   its container's height — which must be *definite*. A min-height alone does
+   not resolve the chart wrapper's height:100%, leaving Chart.js to fall back
+   to its ~150px default (a squashed sliver). Give it a real height. */
+.chartBox {
+  height: 420px;
+}
+
+@media (max-width: 640px) {
+  /* Taller on mobile: the mobile-only school chips sit above the canvas and
+     wrap to two rows for 3+ schools, so the plot keeps a usable height. */
+  .chartBox {
+    height: 360px;
+  }
+}
@@ -0,0 +1,128 @@
+/**
+ * Explore trends — the full grouped metric catalogue (nothing from the old
+ * compare page is lost; spec §4's tier 3) driving the year-by-year chart with
+ * its England reference line. Matches the mockup: a measure picker and the
+ * chart only (no data table).
+ */
+
+'use client';
+
+import dynamic from 'next/dynamic';
+
+import type { ComparisonData, MetricDefinition, NationalAverages, School } from '@/lib/types';
+import { track } from '@/lib/analytics';
+import { Section } from './sectionShared';
+import styles from './TrendsExplorer.module.css';
+
+const ComparisonChart = dynamic(
+  () => import('../ComparisonChart').then((m) => m.ComparisonChart),
+  { ssr: false },
+);
+
+const PRIMARY_OPTGROUPS: { label: string; category: string }[] = [
+  { label: 'Expected Standard', category: 'expected' },
+  { label: 'Higher Standard', category: 'higher' },
+  { label: 'Progress Scores', category: 'progress' },
+  { label: 'Average Scores', category: 'average' },
+  { label: 'Gender Performance', category: 'gender' },
+  { label: 'Equity (Disadvantaged)', category: 'equity' },
+  { label: 'School Context', category: 'context' },
+  { label: 'Absence', category: 'absence' },
+  { label: '3-Year Trends', category: 'trends' },
+];
+
+const SECONDARY_OPTGROUPS: { label: string; category: string }[] = [
+  { label: 'GCSE Performance', category: 'gcse' },
+];
+
+export const PRIMARY_CATEGORIES = PRIMARY_OPTGROUPS.map((g) => g.category);
+export const SECONDARY_CATEGORIES = SECONDARY_OPTGROUPS.map((g) => g.category);
+
+export function TrendsExplorer({
+  schools,
+  data,
+  metrics,
+  metric,
+  onMetricChange,
+  isPrimaryPhase,
+  nationalAverages,
+}: {
+  schools: School[];
+  data: Record<string, ComparisonData>;
+  metrics: MetricDefinition[];
+  /** Controlled: the page owns the metric so the URL contract survives. */
+  metric: string;
+  onMetricChange: (metric: string) => void;
+  isPrimaryPhase: boolean;
+  nationalAverages?: NationalAverages;
+}) {
+  const allowedCategories = isPrimaryPhase ? PRIMARY_CATEGORIES : SECONDARY_CATEGORIES;
+  const optgroups = isPrimaryPhase ? PRIMARY_OPTGROUPS : SECONDARY_OPTGROUPS;
+  const filteredMetrics = metrics.filter((m) => allowedCategories.includes(m.category));
+  const metricDef = metrics.find((m) => m.key === metric);
+  const metricLabel = metricDef?.label || metric;
+
+  const nationalByYear: Record<number, number | null> = {};
+  for (const entry of nationalAverages?.by_year ?? []) {
+    const block = isPrimaryPhase ? entry.primary : entry.secondary;
+    nationalByYear[entry.year] = block?.[metric] ?? null;
+  }
+
+  const handleMetricChange = (next: string) => {
+    track('compare_metric_changed', { metric: next, phase: isPrimaryPhase ? 'primary' : 'secondary' });
+    onMetricChange(next);
+  };
+
+  return (
+    <Section
+      title="Explore trends"
+      how="The full year-by-year explorer for any measure, with the England average as a dashed reference line where official figures exist."
+    >
+      <details className={styles.explore} open>
+        <summary>Year-by-year trends</summary>
+        <div className={styles.inner}>
+          <div className={styles.picker}>
+            <label htmlFor="trends-metric-select">Measure:</label>
+            <select
+              id="trends-metric-select"
+              value={metric}
+              onChange={(e) => handleMetricChange(e.target.value)}
+            >
+              {optgroups.map(({ label, category }) => {
+                const group = filteredMetrics.filter((m) => m.category === category);
+                if (group.length === 0) return null;
+                return (
+                  <optgroup key={category} label={label}>
+                    {group.map((m) => (
+                      <option key={m.key} value={m.key}>
+                        {m.label}
+                      </option>
+                    ))}
+                  </optgroup>
+                );
+              })}
+            </select>
+            {metricDef?.description && <span className={styles.desc}>{metricDef.description}</span>}
+          </div>
+
+          {metric.includes('progress') && (
+            <p className={styles.progressNote}>
+              Progress scores measure pupils&apos; progress from KS1 to KS2. A score of 0 equals the
+              national average. DfE stopped publishing KS2 progress after 2022/23 (no KS1 baseline).
+            </p>
+          )}
+
+          <div className={styles.chartBox}>
+            <ComparisonChart
+              comparisonData={data}
+              schools={schools}
+              metric={metric}
+              metricLabel={metricLabel}
+              nationalByYear={nationalByYear}
+            />
+          </div>
+        </div>
+      </details>
+    </Section>
+  );
+}
@@ -0,0 +1,264 @@
+/* Shared layout for the compare screen's measure-first sections.
+   Mobile base: each row-label becomes a measure header and each school cell
+   stacks under it (colour-coded via the cell's ::before school tag).
+   Desktop (≥761px): the mockups' grid — 200px row-label column + one column
+   per school (2–4 columns supported via --school-count). */
+
+.section {
+  margin-top: 3rem;
+}
+
+.sectionTitle {
+  font-family: var(--font-playfair), 'Playfair Display', Georgia, serif;
+  font-size: 1.45rem;
+  font-weight: 700;
+  margin: 0;
+  padding-left: 0.75rem;
+  border-left: 3px solid var(--accent-coral-dark);
+}
+
+.how {
+  font-size: 0.85rem;
+  color: var(--text-muted);
+  margin: 0.35rem 0 0 0.95rem;
+  max-width: 70ch;
+}
+
+.grid {
+  display: grid;
+  grid-template-columns: 1fr;
+  gap: 0;
+  margin-top: 1.25rem;
+}
+
+/* Mobile base: each measure is a card; each cell is a school row led by a
+   colour dot + short name. `display: contents` at ≥761px dissolves the card
+   back into the shared grid. */
+.measure {
+  background: var(--bg-card);
+  border: 1px solid var(--border-light);
+  border-radius: 12px;
+  box-shadow: var(--shadow-soft);
+  padding: 0.75rem 0.85rem;
+  margin-bottom: 0.6rem;
+}
+
+.rowLabel {
+  font-size: 0.85rem;
+  font-weight: 600;
+  color: var(--text-primary);
+  display: flex;
+  align-items: center;
+  gap: 0.35rem;
+  padding: 0 0 0.1rem;
+}
+
+.cell {
+  display: flex;
+  align-items: baseline;
+  gap: 0.35rem 0.5rem;
+  flex-wrap: wrap;
+  padding: 0.5rem 0;
+  border-top: 1px solid var(--border-light);
+  margin-top: 0.5rem;
+  font-size: 0.95rem;
+}
+
+/* The school name gets its own full-width line above the value — real
+   school names are long and varied, so a fixed-width name column truncated
+   them ("Our Lady Queen of H…") or crowded the value. */
+.cellTag {
+  display: inline-flex;
+  align-items: center;
+  gap: 0.4rem;
+  flex-basis: 100%;
+  font-size: 0.8rem;
+  font-weight: 600;
+  color: var(--sc, var(--text-secondary));
+  margin-bottom: 0.15rem;
+}
+
+.cellDot {
+  width: 9px;
+  height: 9px;
+  border-radius: 50%;
+  background: var(--dot, var(--text-muted));
+  flex: none;
+}
+
+.big {
+  font-size: 1.05rem;
+  font-weight: 700;
+  font-variant-numeric: tabular-nums;
+}
+
+.small {
+  display: block;
+  flex-basis: 100%;
+  font-size: 0.8rem;
+  color: var(--text-muted);
+  margin-top: 0;
+}
+
+.chip {
+  display: inline-block;
+  font-size: 0.75rem;
+  font-weight: 600;
+  border-radius: 999px;
+  padding: 0.15rem 0.6rem;
+  white-space: nowrap;
+}
+
+.chipGood {
+  background: rgba(45, 125, 125, 0.14);
+  color: var(--accent-teal);
+}
+
+.chipWarn {
+  background: var(--accent-gold-bg);
+  color: var(--accent-gold-text);
+}
+
+.chipBad {
+  background: var(--accent-coral-bg);
+  color: var(--accent-coral-dark);
+}
+
+.chipNeutral {
+  background: var(--bg-secondary);
+  color: var(--text-secondary);
+}
+
+.help {
+  display: inline-flex;
+  width: 15px;
+  height: 15px;
+  border-radius: 50%;
+  border: 1px solid var(--text-muted);
+  color: var(--text-muted);
+  font-size: 0.65rem;
+  align-items: center;
+  justify-content: center;
+  cursor: help;
+  flex: none;
+}
+
+.badge {
+  display: inline-block;
+  font-weight: 700;
+  border-radius: 6px;
+  padding: 0.25rem 0.7rem;
+  font-size: 0.9rem;
+}
+
+.badgeGood {
+  background: rgba(45, 125, 125, 0.14);
+  color: var(--accent-teal);
+}
+
+.badgeWarn {
+  background: var(--accent-gold-bg);
+  color: var(--accent-gold-text);
+}
+
+.badgeBad {
+  background: var(--accent-coral-bg);
+  color: var(--accent-coral-dark);
+}
+
+.rcList {
+  display: flex;
+  flex-direction: column;
+  gap: 0.3rem;
+  margin-top: 0.2rem;
+}
+
+.rcRow {
+  display: flex;
+  justify-content: space-between;
+  align-items: center;
+  gap: 0.5rem;
+  font-size: 0.8rem;
+}
+
+.rcArea {
+  color: var(--text-secondary);
+}
+
+.chipStack {
+  display: flex;
+  gap: 0.3rem;
+  flex-wrap: wrap;
+  flex-basis: 100%;
+  margin-top: 0.3rem;
+}
+
+.barMini {
+  display: block;
+  height: 8px;
+  border-radius: 4px;
+  background: var(--bg-secondary);
+  overflow: hidden;
+  margin-top: 0.3rem;
+  max-width: 140px;
+}
+
+.barMini > i {
+  display: block;
+  height: 100%;
+  border-radius: 4px;
+}
+
+.card {
+  background: var(--bg-card);
+  border: 1px solid var(--border-light);
+  border-radius: 16px;
+  box-shadow: var(--shadow-soft);
+  padding: 1.25rem 1.5rem;
+  margin-top: 1rem;
+}
+
+.link {
+  color: var(--accent-coral-dark);
+}
+
+@media (min-width: 761px) {
+  .grid {
+    grid-template-columns: 200px repeat(var(--school-count, 3), 1fr);
+    gap: 0 0.75rem;
+  }
+
+  /* Dissolve the per-measure card so its label + cells become grid items of
+     .grid, keeping columns aligned across every measure. */
+  .measure {
+    display: contents;
+  }
+
+  .cellTag {
+    display: none;
+  }
+
+  .rowLabel {
+    color: var(--text-secondary);
+    padding: 0.85rem 0.5rem 0.85rem 0;
+    border-bottom: 1px solid var(--border-light);
+  }
+
+  .cell {
+    display: block;
+    padding: 0.85rem 0.25rem;
+    border-top: none;
+    border-bottom: 1px solid var(--border-light);
+    margin-top: 0;
+  }
+
+  .big {
+    font-size: 1.35rem;
+  }
+
+  .small {
+    flex-basis: auto;
+    padding-left: 0;
+    margin-top: 0.1rem;
+  }
+}
@@ -0,0 +1,130 @@
+/**
+ * Small shared pieces for the compare sections: the section shell, the
+ * row-label + per-school-cell grid, and tone-mapped chips. Copy passed into
+ * these comes verbatim from the reviewed mockups
+ * (docs/superpowers/specs/mockups/) — do not paraphrase it here.
+ */
+
+'use client';
+
+import type { CSSProperties, ReactNode } from 'react';
+
+import type { School } from '@/lib/types';
+import { CHART_COLORS, CHART_TEXT_COLORS, shortName } from '@/lib/utils';
+import styles from './compareSections.module.css';
+
+export function Section({
+  title,
+  how,
+  children,
+}: {
+  title: string;
+  how?: ReactNode;
+  children: ReactNode;
+}) {
+  return (
+    <section className={styles.section}>
+      <h2 className={styles.sectionTitle}>{title}</h2>
+      {how && <p className={styles.how}>{how}</p>}
+      {children}
+    </section>
+  );
+}
+
+export function SectionGrid({
+  schools,
+  children,
+}: {
+  schools: School[];
+  children: ReactNode;
+}) {
+  return (
+    <div
+      className={styles.grid}
+      style={{ '--school-count': schools.length } as CSSProperties}
+    >
+      {children}
+    </div>
+  );
+}
+
+export function RowLabel({ children, tip }: { children: ReactNode; tip?: string }) {
+  return (
+    <div className={styles.rowLabel}>
+      {children}
+      {tip && (
+        <span className={styles.help} title={tip} aria-label={tip}>
+          ?
+        </span>
+      )}
+    </div>
+  );
+}
+
+/**
+ * One measure = its row label plus a cell per school. `display: contents` on
+ * desktop (see CSS) makes these flow into the section grid as if this wrapper
+ * weren't here, keeping columns aligned across measures; on mobile the wrapper
+ * becomes a card so each measure reads as its own block.
+ */
+export function Measure({
+  label,
+  tip,
+  children,
+}: {
+  label: ReactNode;
+  tip?: string;
+  children: ReactNode;
+}) {
+  return (
+    <div className={styles.measure}>
+      <RowLabel tip={tip}>{label}</RowLabel>
+      {children}
+    </div>
+  );
+}
+
+export function Cell({
+  school,
+  index,
+  children,
+}: {
+  school: School;
+  index: number;
+  children: ReactNode;
+}) {
+  return (
+    <div
+      className={styles.cell}
+      style={
+        {
+          '--sc': CHART_TEXT_COLORS[index % CHART_TEXT_COLORS.length],
+          '--dot': CHART_COLORS[index % CHART_COLORS.length],
+        } as CSSProperties
+      }
+    >
+      {/* Mobile-only per-school tag (dot + short name); hidden on desktop,
+          where the column header identifies the school. */}
+      <span className={styles.cellTag}>
+        <span className={styles.cellDot} aria-hidden="true" />
+        {shortName(school.school_name)}
+      </span>
+      {children}
+    </div>
+  );
+}
+
+export type ChipTone = 'good' | 'warn' | 'bad' | 'neutral';
+
+const CHIP_TONE_CLASS: Record<ChipTone, string> = {
+  good: styles.chipGood,
+  warn: styles.chipWarn,
+  bad: styles.chipBad,
+  neutral: styles.chipNeutral,
+};
+
+export function Chip({ tone, children }: { tone: ChipTone; children: ReactNode }) {
+  return <span className={`${styles.chip} ${CHIP_TONE_CLASS[tone]}`}>{children}</span>;
+}
+
+export const sectionStyles = styles;
@@ -1,50 +1,18 @@
 /**
- * Custom hook for managing school comparison state
- * Uses shared context for real-time updates across components
+ * Custom hook for managing school comparison state.
+ *
+ * This hook is mounted on every page via the global Navigation and
+ * ComparisonToast, so it must stay cheap — it exposes basket state only.
+ * The compare page fetches `/api/compare` itself (ComparisonView); nothing
+ * ever read the comparison payload from here, so the previous per-page SWR
+ * fetch (which fired on every page whenever the basket was non-empty) was
+ * dead weight and has been removed.
 */

 'use client';

-import useSWR from 'swr';
-import { fetcher } from '@/lib/api';
 import { useComparisonContext } from '@/context/ComparisonContext';
-import type { ComparisonResponse } from '@/lib/types';

 export function useComparison() {
-  const {
-    selectedSchools,
-    addSchool,
-    removeSchool,
-    replaceSchools,
-    clearAll,
-    isSelected,
-    canAddMore,
-    isInitialized,
-  } = useComparisonContext();
-
-  // Fetch comparison data for selected schools
-  const urns = selectedSchools.map((s) => s.urn).join(',');
-  const { data, error, isLoading, mutate } = useSWR<ComparisonResponse>(
-    selectedSchools.length > 0 ? `/compare?urns=${urns}` : null,
-    fetcher,
-    {
-      revalidateOnFocus: false,
-      dedupingInterval: 10000,
-    }
-  );
-
-  return {
-    selectedSchools,
-    comparisonData: data?.comparison,
-    isLoading,
-    error,
-    addSchool,
-    removeSchool,
-    replaceSchools,
-    clearAll,
-    isSelected,
-    canAddMore,
-    isInitialized,
-    mutate,
-  };
+  return useComparisonContext();
 }
@@ -0,0 +1,102 @@
+/**
+ * Pure series-building for the comparison trend chart, extracted from
+ * ComparisonChart so it is unit-testable without a canvas.
+ *
+ * Chart truthfulness rules (spec §8.1): every academic year between the
+ * first and last data point appears on the axis — cancelled test years
+ * (2019/20, 2020/21) and the unpublished 2021/22 school-level year render
+ * as real gaps, never as compressed time; school lines never bridge gaps.
+ */
+
+import type { ComparisonData } from './types';
+
+/** 201819 → 201920 (academic-year arithmetic on YYYYYY codes). */
+function nextAcademicYear(year: number): number {
+  const start = Math.floor(year / 100);
+  const end = year % 100;
+  return (start + 1) * 100 + (end + 1);
+}
+
+/** Every academic year from min(years) to max(years), inclusive. */
+export function fillAcademicYears(years: number[]): number[] {
+  if (years.length === 0) return [];
+  const ints = [...new Set(years.map((y) => Math.trunc(y)))].sort((a, b) => a - b);
+  const out: number[] = [];
+  let y = ints[0];
+  const last = ints[ints.length - 1];
+  while (y <= last && out.length < 50) {
+    out.push(y);
+    y = nextAcademicYear(y);
+  }
+  return out;
+}
+
+export interface CompareChartSeries {
+  label: string;
+  data: Array<number | null>;
+  /** Index into CHART_COLORS / point styles. */
+  schoolIndex: number;
+  spanGaps: false;
+}
+
+export interface EnglandSeries {
+  label: 'England average';
+  data: Array<number | null>;
+  borderDash: [number, number];
+  spanGaps: false;
+}
+
+export interface CompareChart {
+  years: number[];
+  schoolDatasets: CompareChartSeries[];
+  englandDataset: EnglandSeries | null;
+  /** True when England published a 2021/22 figure but no school has one —
+   * the UI shows: "DfE didn't publish school-level figures for 2021/22". */
+  showUnpublished202122Note: boolean;
+}
+
+export function buildCompareChart(
+  comparisonData: Record<string, ComparisonData>,
+  schools: Array<{ urn: number; school_name: string }>,
+  metric: string,
+  nationalByYear?: Record<number, number | null | undefined>,
+): CompareChart {
+  const rawYears = schools.flatMap(
+    (s) => comparisonData[String(s.urn)]?.yearly_data.map((d) => Math.trunc(d.year)) ?? [],
+  );
+  const years = fillAcademicYears(rawYears);
+
+  const schoolDatasets: CompareChartSeries[] = schools.map((school, schoolIndex) => {
+    const rows = comparisonData[String(school.urn)]?.yearly_data ?? [];
+    const byYear = new Map<number, Record<string, unknown>>();
+    for (const row of rows) byYear.set(Math.trunc(row.year), row as unknown as Record<string, unknown>);
+    return {
+      label: school.school_name,
+      data: years.map((year) => {
+        const v = byYear.get(year)?.[metric];
+        return typeof v === 'number' && !Number.isNaN(v) ? v : null;
+      }),
+      schoolIndex,
+      spanGaps: false,
+    };
+  });
+
+  let englandDataset: EnglandSeries | null = null;
+  if (nationalByYear) {
+    const data = years.map((year) => {
+      const v = nationalByYear[year];
+      return typeof v === 'number' && !Number.isNaN(v) ? v : null;
+    });
+    if (data.some((v) => v != null)) {
+      englandDataset = { label: 'England average', data, borderDash: [5, 4], spanGaps: false };
+    }
+  }
+
+  const idx202122 = years.indexOf(202122);
+  const showUnpublished202122Note =
+    idx202122 >= 0 &&
+    englandDataset?.data[idx202122] != null &&
+    schoolDatasets.every((ds) => ds.data[idx202122] == null);
+
+  return { years, schoolDatasets, englandDataset, showUnpublished202122Note };
+}
@@ -0,0 +1,250 @@
+/**
+ * Comprehension rules for the compare screen, kept pure and unit-tested.
+ *
+ * These encode the expert-review requirements (spec §8 of the compare
+ * redesign): report-card summaries count graded areas only (safeguarding is
+ * a separate binary judgement), problem areas are always NAMED rather than
+ * folded into counts, grade labels pass through from the API (live-sampled
+ * Ofsted vocabulary — never invented here), admissions chips use one
+ * consistent metric, and progress bands follow DfE's confidence-interval
+ * methodology instead of thresholding point estimates.
+ */
+
+import type { OfstedInspection, SchoolAdmissions } from './types';
+
+// ---------------------------------------------------------------------------
+// Verdicts against an anchor (England average or state-school benchmark)
+// ---------------------------------------------------------------------------
+
+export type Verdict = 'above' | 'close' | 'below';
+
+export function verdict(value: number, anchor: number, tolerance = 2): Verdict {
+  if (value >= anchor + tolerance) return 'above';
+  if (value <= anchor - tolerance) return 'below';
+  return 'close';
+}
+
+// ---------------------------------------------------------------------------
+// Ofsted — three regimes, one display model
+// ---------------------------------------------------------------------------
+
+export const OFSTED_LEGACY_GRADES: Record<number, string> = {
+  1: 'Outstanding',
+  2: 'Good',
+  3: 'Requires improvement',
+  4: 'Inadequate',
+};
+
+/** rc_ key → the area label used across the reviewed mockups. */
+const RC_AREA_LABELS: Record<string, string> = {
+  rc_inclusion: 'Inclusion',
+  rc_curriculum_teaching: 'Curriculum & teaching',
+  rc_achievement: 'Achievement',
+  rc_attendance_behaviour: 'Attendance & behaviour',
+  rc_personal_development: 'Personal development',
+  rc_leadership_governance: 'Leadership & governance',
+  rc_early_years: 'Early years',
+  rc_sixth_form: 'Sixth form',
+};
+
+export function rcAreaLabel(key: string): string {
+  return RC_AREA_LABELS[key] ?? key;
+}
+
+export interface ReportCardSummary {
+  /** Graded areas only, grouped by label, best grade first. */
+  counts: Array<{ label: string; count: number }>;
+  /** Areas rated Needs attention / Urgent improvement — always named. */
+  problems: Array<{ areaLabel: string; label: string }>;
+  safeguarding: 'met' | 'not_met' | null;
+  /** True when every graded area is Expected standard or better and
+   * safeguarding is not "not met". */
+  allClear: boolean;
+}
+
+const PROBLEM_CODES = new Set([4, 5]);
+
+export function summariseReportCard(ofsted: OfstedInspection): ReportCardSummary {
+  const entries = Object.entries(ofsted.report_card ?? {});
+  const byCode = new Map<number, { label: string; count: number }>();
+  const problems: ReportCardSummary['problems'] = [];
+
+  for (const [key, entry] of entries) {
+    if (PROBLEM_CODES.has(entry.code)) {
+      problems.push({ areaLabel: rcAreaLabel(key), label: entry.label });
+    } else {
+      const existing = byCode.get(entry.code);
+      if (existing) existing.count += 1;
+      else byCode.set(entry.code, { label: entry.label, count: 1 });
+    }
+  }
+
+  const counts = [...byCode.entries()]
+    .sort(([a], [b]) => a - b)
+    .map(([, v]) => v);
+
+  const safeguarding =
+    ofsted.rc_safeguarding_met === true
+      ? 'met'
+      : ofsted.rc_safeguarding_met === false
+        ? 'not_met'
+        : null;
+
+  return {
+    counts,
+    problems,
+    safeguarding,
+    allClear: entries.length > 0 && problems.length === 0 && safeguarding !== 'not_met',
+  };
+}
+
+export type OfstedDisplay =
+  | { kind: 'none' }
+  | { kind: 'graded'; grade: number; gradeLabel: string; carriedForward: false }
+  | { kind: 'carried_forward'; grade: number; gradeLabel: string; carriedForward: true }
+  | { kind: 'transitional' }
+  | { kind: 'report_card'; summary: ReportCardSummary };
+
+export function ofstedDisplay(
+  ofsted: OfstedInspection | null | undefined,
+): OfstedDisplay {
+  if (!ofsted) return { kind: 'none' };
+
+  // A report card is the newest inspection format; when present it wins —
+  // never derive or prefer an overall grade alongside it.
+  if (ofsted.report_card && Object.keys(ofsted.report_card).length > 0) {
+    return { kind: 'report_card', summary: summariseReportCard(ofsted) };
+  }
+
+  const grade = ofsted.overall_effectiveness;
+  const gradeLabel = grade != null ? OFSTED_LEGACY_GRADES[grade] : undefined;
+  if (grade == null || gradeLabel === undefined) {
+    if (ofsted.inspection_date) {
+      return { kind: 'transitional' };
+    }
+    return { kind: 'none' };
+  }
+
+  if (ofsted.grade_source === 'ungraded_carried_forward') {
+    return { kind: 'carried_forward', grade, gradeLabel, carriedForward: true };
+  }
+  return { kind: 'graded', grade, gradeLabel, carriedForward: false };
+}
+
+// ---------------------------------------------------------------------------
+// Admissions — one consistent chip metric (first-preference success)
+// ---------------------------------------------------------------------------
+
+export interface AdmissionsSummary {
+  firstPrefPct: number | null;
+  chip: { tone: 'good' | 'warn' | 'neutral'; text: string } | null;
+  /** e.g. "Named on 457 forms · 180 places" — total preferences at any rank,
+   * deliberately not phrased as head-to-head applications. */
+  interest: string | null;
+}
+
+export function summariseAdmissions(
+  a: SchoolAdmissions | null | undefined,
+): AdmissionsSummary {
+  if (!a) return { firstPrefPct: null, chip: null, interest: null };
+
+  const pct =
+    a.first_preference_offer_pct != null
+      ? Math.round(a.first_preference_offer_pct)
+      : null;
+
+  let chip: AdmissionsSummary['chip'] = null;
+  if (pct != null) {
+    if (pct >= 100) {
+      chip = { tone: 'good', text: 'All first choices offered' };
+    } else if (pct < 75) {
+      chip = { tone: 'warn', text: 'Over 1 in 4 first choices missed out' };
+    } else {
+      chip = { tone: pct >= 90 ? 'good' : 'neutral', text: `${pct}% of first choices offered` };
+    }
+  }
+
+  const interest =
+    a.total_applications != null && a.places_offered != null
+      ? `Named on ${a.total_applications.toLocaleString('en-GB')} forms · ${a.places_offered.toLocaleString('en-GB')} places`
+      : null;
+
+  return { firstPrefPct: pct, chip, interest };
+}
+
+// ---------------------------------------------------------------------------
+// Progress bands — DfE confidence-interval methodology
+// ---------------------------------------------------------------------------
+
+export function progressBand(
+  score: number | null,
+  lower: number | null,
+  upper: number | null,
+): 'above' | 'average' | 'below' | null {
+  if (score == null || lower == null || upper == null) return null;
+  if (lower > 0) return 'above';
+  if (upper < 0) return 'below';
+  return 'average';
+}
+
+// ---------------------------------------------------------------------------
+// Dot-strip geometry
+// ---------------------------------------------------------------------------
+
+export interface StripPoint {
+  /** 0–100 percentage position along the track. */
+  pos: number;
+  labelAbove: boolean;
+  value: number;
+  schoolIndex: number;
+}
+
+/** Labels within 4% of the domain of a lower neighbour flip above the strip
+ * (the reviewed mockups' collision nudge). */
+export function stripPositions(
+  values: Array<number | null>,
+  min = 0,
+  max = 100,
+): StripPoint[] {
+  const span = max - min;
+  const points = values
+    .map((value, schoolIndex) => ({ value, schoolIndex }))
+    .filter((p): p is { value: number; schoolIndex: number } => p.value != null)
+    .map((p) => ({
+      value: p.value,
+      schoolIndex: p.schoolIndex,
+      pos: Math.min(100, Math.max(0, ((p.value - min) / span) * 100)),
+      labelAbove: false,
+    }));
+
+  const nudge = span * 0.04;
+  let lastBelow = -Infinity;
+  for (const p of [...points].sort((a, b) => a.value - b.value)) {
+    if (p.value - lastBelow < nudge) {
+      p.labelAbove = true;
+    } else {
+      lastBelow = p.value;
+    }
+  }
+  return points;
+}
+
+// ---------------------------------------------------------------------------
+// Metric extraction
+// ---------------------------------------------------------------------------
+
+/** Latest non-null yearly value of `metricKey` per school, in `urns` order. */
+export function latestValues(
+  data: Record<string, { yearly_data: Array<{ year: number }> }>,
+  urns: number[],
+  metricKey: string,
+): Array<number | null> {
+  return urns.map((urn) => {
+    const rows = data[String(urn)]?.yearly_data ?? [];
+    for (let i = rows.length - 1; i >= 0; i--) {
+      const v = (rows[i] as Record<string, unknown>)[metricKey];
+      if (typeof v === 'number' && !Number.isNaN(v)) return v;
+    }
+    return null;
+  });
+}
@@ -17,6 +17,8 @@ export interface School {
  school_type_code: string | null;
  religious_denomination: string | null;
  age_range: string | null;
+  has_sixth_form?: boolean | null;
+  status?: string | null; // GIAS establishment status ("Open" / "Open, but proposed to close")

  // Address
  address1: string | null;
@@ -97,6 +99,21 @@ export interface OfstedInspection {
  rc_leadership_governance: number | null;
  rc_early_years: number | null;
  rc_sixth_form: number | null;
+  /** Where the effective overall grade came from: a graded (Section 5)
+   * inspection, or carried forward from an ungraded (Section 8) outcome. */
+  grade_source?: 'graded' | 'ungraded_carried_forward' | null;
+  /** Renewed-framework (Nov 2025) area judgements, coded + labelled by the
+   * backend from the live-sampled Ofsted vocabulary. Empty when the school
+   * has no report-card inspection. Safeguarding is never included here. */
+  report_card?: Record<string, ReportCardEntry>;
+  /** The school's page on ofsted.gov.uk (never a deep report link). */
+  ofsted_page_url?: string;
+  report_url?: string | null;
+}
+
+export interface ReportCardEntry {
+  code: number;
+  label: string;
 }

 export interface SchoolCensus {
@@ -127,6 +144,12 @@ export interface SchoolAdmissions {
  /** 1st-preference applications per place offered (>1 means oversubscribed). */
  oversubscription_ratio?: number | null;
  oversubscribed: boolean | null;
+  total_offers?: number | null;
+  second_preference_offers?: number | null;
+  third_preference_offers?: number | null;
+  /** Applications naming this school from families in another LA, and offers to them. */
+  cross_la_applications?: number | null;
+  cross_la_offers?: number | null;
 }

 export interface SenDetail {
@@ -170,6 +193,22 @@ export interface SchoolResult {
  school_id: number;
  year: number;

+  // Progress confidence intervals + writing working-towards (published for
+  // years with progress measures, i.e. up to 2022/23)
+  reading_progress_lower_ci?: number | null;
+  reading_progress_upper_ci?: number | null;
+  writing_progress_lower_ci?: number | null;
+  writing_progress_upper_ci?: number | null;
+  writing_working_towards_pct?: number | null;
+  maths_progress_lower_ci?: number | null;
+  maths_progress_upper_ci?: number | null;
+
+  // KS4 banding and disadvantage gaps
+  /** DfE's own plain-English Progress 8 label, e.g. "Well above average". */
+  progress_8_banding?: string | null;
+  attainment_8_disadvantage_gap?: number | null;
+  progress_8_disadvantage_gap?: number | null;
+
  // Pupil numbers
  total_pupils: number | null;
  eligible_pupils: number | null;
@@ -306,10 +345,48 @@ export interface SchoolDetailsResponse {
 export interface ComparisonData {
  school_info: School;
  yearly_data: SchoolResult[];
+  // Supplementary blocks (additive; absent on an old backend)
+  ofsted?: OfstedInspection | null;
+  census?: SchoolCensus | null;
+  admissions?: SchoolAdmissions | null;
+  admissions_history?: SchoolAdmissions[];
+  deprivation?: SchoolDeprivation | null;
+}
+
+export interface BenchmarkBlock {
+  eal_pct: number | null;
+  sen_support_pct: number | null;
+  disadvantaged_pct: number | null;
+  fsm_pct?: number | null;
+  median_pupils: number | null;
+  /** Primary only — weighted by cohort size. */
+  disadvantaged_rwm_expected_pct?: number | null;
+}
+
+/** Computed from our dataset — NOT official DfE figures. UI copy must say
+ * "state-school average (computed from our dataset)" (the `source` string). */
+export interface Benchmarks {
+  source: string;
+  year: number;
+  primary: BenchmarkBlock;
+  secondary: BenchmarkBlock;
+}
+
+export interface NationalAverages {
+  year: number;
+  primary: Record<string, number>;
+  secondary: Record<string, number>;
+  by_year: Array<{
+    year: number;
+    primary: Record<string, number>;
+    secondary: Record<string, number>;
+  }>;
 }

 export interface ComparisonResponse {
  comparison: Record<string, ComparisonData>;
+  national_averages?: NationalAverages;
+  benchmarks?: Benchmarks;
 }

 export interface RankingItem {
@@ -59,6 +59,24 @@ export function truncate(text: string, maxLength: number): string {
  return text.slice(0, maxLength).trim() + '...';
 }

+/**
+ * A compact school label for tight spaces (mobile compare rows, chip bars):
+ * drop the trailing establishment-type words so "Barclay Primary School" →
+ * "Barclay", "St Mary's Catholic Primary School" → "St Mary's". Falls back to
+ * a length-capped truncation for names that don't carry a type suffix.
+ */
+export function shortName(name: string, maxLength = 32): string {
+  let s = name
+    .replace(
+      /\s+(primary|junior|infant|nursery|community|foundation|catholic|academy|school|college)\b.*$/i,
+      '',
+    )
+    .trim();
+  if (!s) s = name;
+  if (s.length > maxLength) s = s.slice(0, maxLength - 1).trim() + '…';
+  return s;
+}
+
 /**
 * Format a school's age range for display, e.g. "3-11" → "Ages 3–11".
 * Display-only — leaves the raw `age_range` field (used for sixth-form
@@ -718,3 +736,18 @@ export function buildOfstedListBadge(school: {

  return { label: 'Not yet inspected', cssClass: 'ofstedPending' };
 }
+
+// ============================================================================
+// Establishment status
+// ============================================================================
+
+export const PROPOSED_TO_CLOSE_STATUS = 'Open, but proposed to close';
+
+/**
+ * GIAS lists some operating schools as "Open, but proposed to close".
+ * They remain open (and may stay open if the proposal is withdrawn), but the
+ * UI marks them so families check with the local authority before applying.
+ */
+export function isProposedToClose(school: { status?: string | null }): boolean {
+  return school.status === PROPOSED_TO_CLOSE_STATUS;
+}
@@ -38,6 +38,31 @@ default_args = {
    "retry_delay": timedelta(minutes=5),
 }

+# The backend caches the marts DataFrame at startup; after any rebuild the
+# cache must be invalidated or the API serves stale (or empty) data until the
+# container restarts.
+INVALIDATE_CACHE_CMD = """
+set -e
+BACKEND_URL="${BACKEND_URL:-http://backend:80}"
+ADMIN_KEY="${ADMIN_API_KEY:-changeme}"
+
+echo "Calling $BACKEND_URL/api/admin/reload ..."
+
+response=$(curl -s -o /tmp/reload_response.json -w "%{http_code}" \\
+    --connect-timeout 10 --max-time 120 \\
+    -X POST "$BACKEND_URL/api/admin/reload" \\
+    -H "X-API-Key: $ADMIN_KEY" \\
+    -H "Content-Type: application/json")
+
+echo "HTTP status: $response"
+cat /tmp/reload_response.json
+
+if [ "$response" != "200" ]; then
+    echo "ERROR: backend cache reload failed (HTTP $response)"
+    exit 1
+fi
+"""
+

 # ── Daily DAG (GIAS + downstream) ──────────────────────────────────────

@@ -83,7 +108,7 @@ print(f'Validation passed: {{count}} GIAS rows')

    dbt_build = BashOperator(
        task_id="dbt_build",
-        bash_command=f"cd {PIPELINE_DIR}/transform && {DBT_BIN} build --profiles-dir . --target production --select stg_gias_establishments+ stg_gias_links+ --exclude int_ks2_with_lineage+ int_ks4_with_lineage+",
+        bash_command=f"cd {PIPELINE_DIR}/transform && {DBT_BIN} build --profiles-dir . --target production --select stg_gias_establishments+ stg_gias_links+ gias_code_names+ --exclude int_ks2_with_lineage+ int_ks4_with_lineage+",
    )

    sync_typesense = BashOperator(
@@ -91,7 +116,12 @@ print(f'Validation passed: {{count}} GIAS rows')
        bash_command=f"cd {PIPELINE_DIR} && python scripts/sync_typesense.py",
    )

-    extract_group >> validate_raw >> dbt_build >> sync_typesense
+    invalidate_cache = BashOperator(
+        task_id="invalidate_cache",
+        bash_command=INVALIDATE_CACHE_CMD,
+    )
+
+    extract_group >> validate_raw >> dbt_build >> sync_typesense >> invalidate_cache


 # ── Monthly DAG (Ofsted) ───────────────────────────────────────────────
@@ -121,7 +151,12 @@ with DAG(
        bash_command=f"cd {PIPELINE_DIR} && python scripts/sync_typesense.py",
    )

-    extract_ofsted >> dbt_build_ofsted >> sync_typesense_ofsted
+    invalidate_cache_ofsted = BashOperator(
+        task_id="invalidate_cache",
+        bash_command=INVALIDATE_CACHE_CMD,
+    )
+
+    extract_ofsted >> dbt_build_ofsted >> sync_typesense_ofsted >> invalidate_cache_ofsted


 # ── Annual DAG (EES: KS2, KS4, Census, Admissions) ───────────────────
@@ -153,7 +188,12 @@ with DAG(
        bash_command=f"cd {PIPELINE_DIR} && python scripts/sync_typesense.py",
    )

-    extract_ees_group >> dbt_build_ees >> sync_typesense_ees
+    invalidate_cache_ees = BashOperator(
+        task_id="invalidate_cache",
+        bash_command=INVALIDATE_CACHE_CMD,
+    )
+
+    extract_ees_group >> dbt_build_ees >> sync_typesense_ees >> invalidate_cache_ees


 # ── Annual DAG (IDACI Deprivation) ────────────────────────────────────
@@ -178,4 +218,9 @@ with DAG(
        bash_command=f"cd {PIPELINE_DIR}/transform && {DBT_BIN} build --profiles-dir . --target production --select stg_idaci+ fact_deprivation+",
    )

-    extract_idaci >> dbt_build_idaci
+    invalidate_cache_idaci = BashOperator(
+        task_id="invalidate_cache",
+        bash_command=INVALIDATE_CACHE_CMD,
+    )
+
+    extract_idaci >> dbt_build_idaci >> invalidate_cache_idaci
@@ -49,6 +49,9 @@ plugins:
        - name: mi_url
          kind: string
          description: Ofsted Management Information download URL
+        - name: independent_mi_url
+          kind: string
+          description: Ofsted Independent Schools Management Information download URL

    - name: tap-uk-fbit
      namespace: uk_fbit
@@ -31,15 +31,22 @@ class GIASEstablishmentsStream(Stream):
    schema = th.PropertiesList(
        th.Property("URN", th.IntegerType, required=True),
        th.Property("EstablishmentName", th.StringType),
+        th.Property("TypeOfEstablishment (code)", th.StringType),
        th.Property("TypeOfEstablishment (name)", th.StringType),
+        th.Property("PhaseOfEducation (code)", th.StringType),
        th.Property("PhaseOfEducation (name)", th.StringType),
+        th.Property("OfficialSixthForm (code)", th.StringType),
+        th.Property("OfficialSixthForm (name)", th.StringType),
        th.Property("LA (code)", th.StringType),
        th.Property("LA (name)", th.StringType),
        th.Property("EstablishmentNumber", th.StringType),
+        th.Property("EstablishmentStatus (code)", th.StringType),
        th.Property("EstablishmentStatus (name)", th.StringType),
        th.Property("Postcode", th.StringType),
        th.Property("Gender (name)", th.StringType),
+        th.Property("ReligiousCharacter (code)", th.StringType),
        th.Property("ReligiousCharacter (name)", th.StringType),
+        th.Property("AdmissionsPolicy (code)", th.StringType),
        th.Property("AdmissionsPolicy (name)", th.StringType),
        th.Property("SchoolCapacity", th.StringType),
        th.Property("NumberOfPupils", th.StringType),
@@ -2,6 +2,7 @@

 from __future__ import annotations

+from datetime import datetime
 import io
 import re

@@ -14,20 +15,28 @@ GOV_UK_PAGE = (
    "monthly-management-information-ofsteds-school-inspections-outcomes"
 )

+INDEPENDENT_GOV_UK_PAGE = (
+    "https://www.gov.uk/government/statistical-data-sets/"
+    "non-association-independent-schools-inspections-and-outcomes-management-information"
+)
+
 # Column name → internal field, in priority order (first match wins).
 # Handles both current and older file formats.
 COLUMN_PRIORITY = {
    "urn": ["URN", "Urn", "urn"],
    "inspection_date": [
        "Inspection start date of latest OEIF graded inspection",
+        "Inspection start date of latest OEIF standard inspection",
        "Inspection start date",
        "Inspection date",
    ],
    "inspection_type": [
        "Inspection type of latest OEIF graded inspection",
+        "Inspection type of latest OEIF standard inspection",
        "Inspection type",
    ],
    "event_type_grouping": [
+        "Event type grouping of latest OEIF standard inspection",
        "Event type grouping",
        "Inspection type grouping",
    ],
@@ -52,10 +61,12 @@ COLUMN_PRIORITY = {
        "Effectiveness of leadership and management",
    ],
    "early_years_provision": [
+        "Latest OEIF early years provision (where applicable)",
        "Latest OEIF early years provision",
        "Early years provision (where applicable)",
    ],
    "sixth_form_provision": [
+        "Latest OEIF sixth form provision (where applicable)",
        "Latest OEIF sixth form provision",
        "Sixth form provision (where applicable)",
    ],
@@ -68,6 +79,21 @@ COLUMN_PRIORITY = {
    "ungraded_inspection_date": [
        "Date of latest ungraded inspection",
    ],
+    # Report Card fields (post-Nov 2025 framework).
+    "rc_safeguarding_met": ["Safeguarding standards"],
+    "rc_inclusion": ["Inclusion"],
+    "rc_curriculum_teaching": ["Curriculum and teaching"],
+    "rc_achievement": ["Achievement"],
+    "rc_attendance_behaviour": ["Attendance and behaviour"],
+    "rc_personal_development": ["Personal development and wellbeing"],
+    "rc_leadership_governance": ["Leadership and governance"],
+    "rc_early_years": ["Early years (where applicable)"],
+    "rc_sixth_form": ["Post-16 provision (where applicable)"],
+    "report_url": [
+        "Web Link (opens in new window)",
+        "Web link to Ofsted provider page",
+        "Web link",
+    ],
 }


@@ -90,6 +116,51 @@ def discover_csv_url() -> str | None:
    return matches[0] if matches else None


+def discover_independent_csv_url() -> str | None:
+    """Scrape GOV.UK page to find the latest independent schools MI CSV download link."""
+    resp = requests.get(INDEPENDENT_GOV_UK_PAGE, timeout=30)
+    resp.raise_for_status()
+    # Look for CSV attachment links
+    csv_links = re.findall(
+        r'href="(https://assets\.publishing\.service\.gov\.uk/[^"]+\.csv)"',
+        resp.text,
+    )
+    if not csv_links:
+        # Fall back to ODS
+        csv_links = re.findall(
+            r'href="(https://assets\.publishing\.service\.gov\.uk/[^"]+\.ods)"',
+            resp.text,
+        )
+
+    months = {
+        'january': 1, 'february': 2, 'march': 3, 'april': 4, 'may': 5, 'june': 6,
+        'july': 7, 'august': 8, 'september': 9, 'october': 10, 'november': 11, 'december': 12
+    }
+
+    parsed_links = []
+    for link in csv_links:
+        normalized_link = link.lower().replace('-', '_')
+        if 'most_recent' not in normalized_link:
+            continue
+
+        match = re.search(r'as_at_(\d{1,2})_([a-z]+)_(\d{4})', normalized_link)
+        if match:
+            day, month_str, year = match.groups()
+            month = months.get(month_str)
+            if month:
+                try:
+                    dt = datetime(int(year), month, int(day))
+                    parsed_links.append((dt, link))
+                except ValueError:
+                    continue
+
+    parsed_links.sort(reverse=True)
+    if parsed_links:
+        return parsed_links[0][1]
+
+    return csv_links[0] if csv_links else None
+
+
 class OfstedInspectionsStream(Stream):
    """Stream: Ofsted inspection records."""

@@ -111,6 +182,15 @@ class OfstedInspectionsStream(Stream):
        th.Property("sixth_form_provision", th.StringType),
        th.Property("ungraded_outcome", th.StringType),
        th.Property("ungraded_inspection_date", th.StringType),
+        th.Property("rc_safeguarding_met", th.StringType),
+        th.Property("rc_inclusion", th.StringType),
+        th.Property("rc_curriculum_teaching", th.StringType),
+        th.Property("rc_achievement", th.StringType),
+        th.Property("rc_attendance_behaviour", th.StringType),
+        th.Property("rc_personal_development", th.StringType),
+        th.Property("rc_leadership_governance", th.StringType),
+        th.Property("rc_early_years", th.StringType),
+        th.Property("rc_sixth_form", th.StringType),
        th.Property("report_url", th.StringType),
    ).to_dict()

@@ -124,15 +204,8 @@ class OfstedInspectionsStream(Stream):
                    break
        return mapping

-    def get_records(self, context):
-        import pandas as pd
-
-        url = self.config.get("mi_url") or discover_csv_url()
-        if not url:
-            self.logger.error("Could not discover Ofsted MI download URL")
-            return
-
-        self.logger.info("Downloading Ofsted MI: %s", url)
+    def _fetch_and_parse_url(self, url: str, pd) -> list[dict]:
+        """Download file and parse records."""
        resp = requests.get(url, timeout=120)
        resp.raise_for_status()

@@ -148,8 +221,6 @@ class OfstedInspectionsStream(Stream):
            lines = text.split("\n")
            header_idx = 0
            for i, line in enumerate(lines[:20]):
-                # Match lines where URN appears as a CSV field (start or after comma),
-                # not as a substring of words like "turn" or "return".
                if re.search(r'(?:^|,)\s*URN\s*(?:,|$)', line):
                    header_idx = i
                    break
@@ -167,16 +238,38 @@ class OfstedInspectionsStream(Stream):
        for _, row in df.iterrows():
            record = {}
            for field, col in col_map.items():
-                record[field] = row.get(col, None)
+                val = row.get(col, None)
+                if pd.isna(val):
+                    val = None
+                record[field] = val

            # Cast URN
            try:
-                record["urn"] = int(record["urn"])
+                record["urn"] = int(record.get("urn"))
            except (ValueError, KeyError, TypeError):
                continue

            yield record

+    def get_records(self, context):
+        import pandas as pd
+
+        # 1. State-funded schools
+        state_url = self.config.get("mi_url") or discover_csv_url()
+        if state_url:
+            self.logger.info("Downloading Ofsted state-funded MI: %s", state_url)
+            yield from self._fetch_and_parse_url(state_url, pd)
+        else:
+            self.logger.error("Could not discover Ofsted state-funded MI download URL")
+
+        # 2. Independent schools
+        ind_url = self.config.get("independent_mi_url") or discover_independent_csv_url()
+        if ind_url:
+            self.logger.info("Downloading Ofsted independent MI: %s", ind_url)
+            yield from self._fetch_and_parse_url(ind_url, pd)
+        else:
+            self.logger.error("Could not discover Ofsted independent MI download URL")
+

 class TapUKOfsted(Tap):
    """Singer tap for UK Ofsted Management Information."""
@@ -185,6 +278,7 @@ class TapUKOfsted(Tap):

    config_jsonschema = th.PropertiesList(
        th.Property("mi_url", th.StringType, description="Direct URL to Ofsted MI file"),
+        th.Property("independent_mi_url", th.StringType, description="Direct URL to Ofsted Independent Schools MI file"),
    ).to_dict()

    def discover_streams(self):
@@ -0,0 +1,305 @@
+"""Diagnose the three data gaps blocking the compare-screen redesign.
+
+Run from repo root (network access required, no DB needed):
+    uv run --with singer-sdk --with pandas --with requests \
+        python pipeline/scripts/diagnose_compare_gaps.py
+
+(singer_sdk is a transitive import of tap_uk_ees.tap / tap_uk_ofsted.tap and
+is not part of the repo's default environment, hence the `uv run --with`.)
+"""
+import io
+import re
+import sys
+
+import pandas as pd
+import requests
+
+sys.path.insert(0, "pipeline/plugins/extractors/tap-uk-ees")
+sys.path.insert(0, "pipeline/plugins/extractors/tap-uk-ofsted")
+from tap_uk_ees.tap import (  # noqa: E402
+    _KS2_NATIONAL_COL_MAP,
+    _KS2_NATIONAL_CSV_URL,
+    download_release_zip,
+    get_all_releases,
+)
+from tap_uk_ofsted.tap import discover_csv_url  # noqa: E402
+
+TIMEOUT = 120
+
+
+def check_national_gps_science():
+    print("\n=== (a) National catalogue CSV: GPS/science columns ===")
+    resp = requests.get(_KS2_NATIONAL_CSV_URL, timeout=TIMEOUT)
+    resp.raise_for_status()
+    df = pd.read_csv(io.BytesIO(resp.content), dtype=str, keep_default_na=False)
+    df.columns = [c.strip().lower() for c in df.columns]
+    for csv_col in ("pt_gps_exp", "pt_scita_exp", "avg_readscore", "avg_matscore", "avg_gpsscore"):
+        status = "PRESENT" if csv_col in df.columns else "MISSING"
+        print(f"  {csv_col}: {status}")
+    gps_like = [c for c in df.columns if "gps" in c or "scita" in c or "sci" in c]
+    print(f"  all gps/science-ish columns: {gps_like}")
+    if "geographic_level" in df.columns:
+        nat = df[df["geographic_level"].str.strip().str.lower() == "national"]
+    else:
+        print("  geographic_level column missing — cannot isolate national rows")
+        return
+    print(f"  national rows time_periods: {sorted(nat['time_period'].unique())}")
+    # Sample the values our map would read for the latest year
+    latest = nat[nat["time_period"] == nat["time_period"].max()]
+    for csv_col, field in _KS2_NATIONAL_COL_MAP.items():
+        val = latest.iloc[0].get(csv_col, "<col missing>") if len(latest) else "<no row>"
+        print(f"  {field} <- {csv_col} = {val!r}")
+
+
+def check_ks2_attainment_years_subjects():
+    print("\n=== (b) EES KS2 attainment: years & subject labels ===")
+    releases = get_all_releases("key-stage-2-attainment")
+    print(f"  releases found: {[r['time_period'] for r in releases]}")
+    for release in releases:
+        try:
+            zf = download_release_zip(release["id"])
+        except Exception as e:
+            print(f"  {release['time_period']}: DOWNLOAD FAILED: {e}")
+            continue
+        name = next((n for n in zf.namelist()
+                     if "ks2_school_attainment_data" in n and n.endswith(".csv")), None)
+        if not name:
+            print(f"  {release['time_period']}: NO school attainment CSV in ZIP")
+            print(f"    all CSVs in zip: {[n for n in zf.namelist() if n.endswith('.csv')]}")
+            continue
+        with zf.open(name) as f:
+            df = pd.read_csv(f, dtype=str, keep_default_na=False, nrows=200000)
+        years = sorted(df["time_period"].unique())
+        subjects = sorted(df["subject"].unique())
+        print(f"  release {release['time_period']}: time_periods={years}")
+        print(f"    subjects={subjects}")
+
+
+def check_ofsted_report_card_columns():
+    print("\n=== (c) Ofsted MI CSV: report-card columns ===")
+    url = discover_csv_url()
+    print(f"  MI file: {url}")
+    if url is None or not url.lower().endswith(".csv"):
+        print(f"  URL is not a CSV (likely ODS) — stopping this section. url={url!r}")
+        return
+    resp = requests.get(url, timeout=TIMEOUT)
+    resp.raise_for_status()
+    df = pd.read_csv(io.BytesIO(resp.content), dtype=str, keep_default_na=False, nrows=5)
+    rc_like = [c for c in df.columns
+               if re.search(r"report card|inclusion|curriculum|achievement|safeguard|well.?being|governance", c, re.I)]
+    print(f"  candidate report-card columns ({len(rc_like)}):")
+    for c in rc_like:
+        print(f"    - {c!r}")
+    print(f"  all columns ({len(df.columns)}):")
+    for c in df.columns:
+        print(f"    - {c!r}")
+
+
+if __name__ == "__main__":
+    check_national_gps_science()
+    check_ks2_attainment_years_subjects()
+    check_ofsted_report_card_columns()
+
+
+# FINDINGS 2026-07-12: run via
+#   uv run --with singer-sdk --with pandas --with requests \
+#       python pipeline/scripts/diagnose_compare_gaps.py
+#
+# (a) National catalogue CSV (GPS/science) — NOT a source-data problem.
+#     pt_gps_exp, pt_scita_exp, avg_readscore, avg_matscore, avg_gpsscore are
+#     all PRESENT in the catalogue CSV and hold real numeric values for the
+#     latest national row (time_period 202425: pt_gps_exp='72.6' ->
+#     gps_expected_pct; pt_scita_exp='81.6' -> science_expected_pct).
+#     national time_periods present: 201516, 201617, 201718, 201819, 201920,
+#     202021, 202122, 202223, 202324, 202425 (COVID years 201920/202021 are
+#     present as rows but suppressed with 'x' per the module docstring, not
+#     absent). So _KS2_NATIONAL_COL_MAP is correct and the extractor's own
+#     read of the source is fine end-to-end -- the NULLs in
+#     marts.fact_ks2_national_averages are NOT caused by a missing/renamed
+#     source column. The gap must be introduced downstream of the tap
+#     (staging/mart SQL, a stale/incomplete load, or a dbt model not
+#     selecting these two columns) -- Task 5/6 should look at the dbt
+#     staging model for ees_ks2_national and the mart definition, not the
+#     tap/column-map.
+#
+# (b) EES KS2 attainment (school-level, "key-stage-2-attainment" publication)
+#     releases found (via get_all_releases): [None, '202425', '202324',
+#     '202223', '202122']. The `None` entry is the *current/latest* release
+#     (its slug doesn't parse to a 6-digit time_period by _slug_to_time_period,
+#     but the CSV inside carries time_period='202425' -- same data as the
+#     202425-labelled release).
+#
+#     Only two of the four releases contain a school-level attainment CSV
+#     matching "ks2_school_attainment_data*.csv":
+#       - release None (latest):  HAS IT -> time_periods=['202425']
+#           subjects=['Grammar, punctuation and spelling', 'Maths', 'Reading',
+#                      'Reading, writing and maths', 'Science', 'Writing']
+#       - release 202324:         HAS IT -> time_periods=['202324']
+#           subjects= same 6 labels as above
+#       - release 202223:         NO school attainment CSV in ZIP. This
+#           release's ZIP instead contains only LA/regional/national/MAT-level
+#           files (e.g. ks2_regional_and_local_authority_*, ks2_multi_academy
+#           _trusts_*, ks2_national_*); no data/*school*attainment*.csv file
+#           exists at all in this release's package. This CONFIRMS the
+#           "subject-level 2022/23 is NULL in prod" symptom: the source
+#           release literally does not publish a school-level attainment file
+#           for 202223 under this filename pattern -- it's not a tap bug.
+#       - release 202122:         NO school attainment CSV in ZIP. Same
+#           situation: ZIP has only LA/regional/national-level files (e.g.
+#           ks2_regional_and_local_authority_2016_to_2022_revised.csv,
+#           ks2_national_school_characteristics_2016_to_2022_revised.csv);
+#           no school-level attainment CSV present. This CONFIRMS "school-level
+#           2021/22 is absent" -- again a genuine source-data absence, not an
+#           extractor bug.
+#     Implication for Tasks 5/6/7: 202122 and 202223 school-level attainment
+#     cannot be backfilled from the "key-stage-2-attainment" EES publication
+#     via this filename pattern -- those two years must either be sourced
+#     from a different EES dataset/file (e.g. one of the *_school_location_
+#     and_pupil_characteristics or *_school_type_and_pupil_characteristics
+#     files present in those ZIPs, which may carry school-level rows under a
+#     different filename), left NULL with an explicit "source unavailable"
+#     note, or backfilled from the legacy DfE "Compare School Performance"
+#     wide-format CSVs referenced elsewhere in tap.py. Subject labels to use
+#     when a source *is* found for 202324/202425:
+#       'Grammar, punctuation and spelling', 'Maths', 'Reading',
+#       'Reading, writing and maths', 'Science', 'Writing'
+#     (Reading, writing and maths spans reading+writing+maths combined --
+#     this is the RWM row.)
+#
+# (c) Ofsted MI CSV (report-card columns) — confirmed PRESENT.
+#     discover_csv_url() resolved to (as at run time, latest inspections
+#     31 May 2026):
+#       https://assets.publishing.service.gov.uk/media/6a27c45be13080622db38815/
+#       Management_information_-_state-funded_schools_-_latest_inspections_as_at_31_May_2026.csv
+#     This is a real .csv (not .ods) so section (c) ran to completion.
+#     Exact report-card column headers (7 grade columns + their paired date
+#     columns, all present verbatim, case/spacing exactly as below):
+#       'Safeguarding standards'                 / 'Safeguarding standards - date of grade'
+#       'Inclusion'                               / 'Inclusion - date of grade'
+#       'Curriculum and teaching'                 / 'Curriculum and teaching - date of grade'
+#       'Achievement'                             / 'Achievement - date of grade'
+#       'Attendance and behaviour'                / 'Attendance and behaviour - date of grade'
+#       'Personal development and wellbeing'      / 'Personal development and wellbeing - date of grade'
+#       'Leadership and governance'               / 'Leadership and governance - date of grade'
+#     Plus a related pass/fail-style field:
+#       'Latest OEIF  safeguarding is effective?' (note: double space in the
+#       header, verbatim from source -- preserve exactly when mapping)
+#     These are the new-style "report card" single-word-area grades
+#     (introduced alongside the "Attendance and behaviour" split from
+#     "Personal development"); they coexist in the same CSV with the legacy
+#     5-judgement OEIF columns ('Latest OEIF overall effectiveness',
+#     'Latest OEIF quality of education', 'Latest OEIF behaviour and
+#     attitudes', 'Latest OEIF personal development', 'Latest OEIF
+#     effectiveness of leadership and management'). Task 7 should map the 7
+#     report-card columns above (grade + date pairs, 6 of them, plus the
+#     safeguarding-effective flag) rather than inventing new column names.
+
+# TASK 6 VERIFICATION 2026-07-12: 2021/22 legacy KS2 school-level archive
+#
+# RESULT: BLOCKED at the source-data level. School-level KS2 attainment for
+# academic year 2021/22 was never published anywhere publicly by DfE -- not
+# in EES (confirmed by Task 1's finding (b) above), not in the legacy
+# "Compare School Performance" download wizard, and not as a standalone
+# performance-tables archive/ODS on assets.publishing.service.gov.uk. This
+# is a deliberate DfE decision, not a gap in our extraction logic.
+#
+# Confirming quote (Key stage 2 attainment 2021/22 release notes, via
+# https://explore-education-statistics.service.gov.uk/find-statistics/
+# key-stage-2-attainment/2021-22):
+#   "We will not publish key stage 2 data for academic year 2021/22 in
+#   performance tables (also known as Compare School and College
+#   Performance)." ... "The Department will, however, still produce the
+#   normal suite of key stage 2 accountability measures at school and
+#   multi-academy trust level and share these securely with primary
+#   schools, academy trusts and local authorities to inform school
+#   improvement discussions."
+# (i.e. school-level 202122 KS2 results exist internally at DfE but were
+# withheld from every public channel: performance tables/CSCP, EES, and by
+# extension the legacy DfE archives the current legacy_ks2_urls entries in
+# meltano.yml were sourced from.)
+#
+# What was tried:
+#  1. Direct download URL pattern from the task brief:
+#       https://www.compare-school-performance.service.gov.uk/download-data?download=true&regions=0&filters=KS2&fileformat=csv&year=2021-2022&meta=false
+#     -> HTTP 404, HTML error page (not a CSV/ZIP). Saved response inspected;
+#     confirmed 404 via response headers (`content-type: text/html`).
+#  2. Walked the actual multi-step download wizard at
+#     https://www.compare-school-performance.service.gov.uk/download-data
+#     with a browser User-Agent and a cookie jar, replicating the GET-based
+#     form steps: currentstep=year (downloadYear=2021-2022) -> currentstep=
+#     region (regiontype=all&la=0) -> currentstep=datatypes. On the final
+#     "datatypes" step, the checkbox list for 2021-2022 has NO "ks2" (or
+#     "ks2mats") option at all -- only ks4/ks4prov/ks4underlying/ks5* /
+#     pupil-destination/absence/census/mats checkboxes are present.
+#     Control check: repeating the same wizard walk for downloadYear=
+#     2018-2019, 2022-2023 and 2023-2024 shows a "ks2" (and "ks2mats")
+#     checkbox present in all three; downloadYear=2020-2021 (COVID-cancelled
+#     KS2 SATs year) also has NO ks2 checkbox, matching the pattern for a
+#     year where school-level KS2 genuinely isn't published. 2021-2022
+#     behaves identically to the cancelled 2020-2021 year, not like the
+#     normal 2018-2019/2022-2023/2023-2024 years.
+#  3. Web search for a standalone KS2 2022 performance-tables archive
+#     (e.g. "england_ks2final" for 2022) on assets.publishing.service.gov.uk
+#     found no such file; only unrelated 2022/2023-dated documents.
+#
+#  No ZIP was ever obtained -- /tmp/dfe-2021-2022-ks2.zip contains the 404
+#  HTML error page from attempt (1) above, not a real archive. It contains
+#  no england_ks2final.csv (there is no ZIP to look inside).
+#
+# Column-map check (brief's Step 1): NOT RUN -- there is no 2021/22
+# england_ks2final.csv to check headers against. This is moot until/unless
+# a non-public source (e.g. a manual/internal DfE extract) becomes
+# available; _LEGACY_KS2_COLUMN_MAP itself is unchanged and untested here.
+#
+# Recommendation: mark 202122 school-level KS2 as a genuine, permanent
+# source-data gap (not a backfill candidate) unless the project can obtain
+# the internal DfE extract DfE says it shared "securely with primary
+# schools, academy trusts and local authorities" -- that is not a route
+# available to this pipeline. Task 6's meltano.yml change (Step 2) and the
+# filebrowser upload should NOT proceed for 202122; there is nothing to
+# upload.
+
+# TASK 7 VALUE SAMPLE 2026-07-12: live value_counts() over the 7 report-card
+# columns (plus the related safeguarding-effective flag) in the same MI CSV
+# resolved by discover_csv_url() as at run time (31 May 2026 inspections
+# file). Blank cells read as the literal string 'NULL' (matches
+# keep_default_na=False in tap.py). Observed non-blank values, verbatim:
+#
+#   'Safeguarding standards':                 'Met' (1319), 'Not met' (10)
+#   'Inclusion':                               'Expected standard' (710),
+#       'Strong standard' (447), 'Needs attention' (130), 'Exceptional' (23),
+#       'Urgent improvement' (19)
+#   'Curriculum and teaching':                 'Expected standard' (797),
+#       'Needs attention' (287), 'Strong standard' (206),
+#       'Urgent improvement' (28), 'Exceptional' (11)
+#   'Achievement':                             'Expected standard' (701),
+#       'Needs attention' (364), 'Strong standard' (207),
+#       'Urgent improvement' (39), 'Exceptional' (18)
+#   'Attendance and behaviour':                'Expected standard' (699),
+#       'Strong standard' (405), 'Needs attention' (188),
+#       'Urgent improvement' (21), 'Exceptional' (16)
+#   'Personal development and wellbeing':      'Expected standard' (728),
+#       'Strong standard' (504), 'Needs attention' (66), 'Exceptional' (23),
+#       'Urgent improvement' (8)
+#   'Leadership and governance':               'Expected standard' (813),
+#       'Strong standard' (292), 'Needs attention' (172),
+#       'Urgent improvement' (34), 'Exceptional' (18)
+#   'Latest OEIF  safeguarding is effective?' (note double space, not used by
+#   Task 7 -- kept for completeness): 'Yes' (12970), 'No' (96)
+#
+# So the 6 graded report-card columns share exactly one 5-value vocabulary:
+# {'Exceptional', 'Strong standard', 'Expected standard', 'Needs attention',
+# 'Urgent improvement'} -- no 'Attention needed' variant was observed
+# anywhere, so parse_report_card_grade.sql does NOT need that speculative
+# branch from the task brief. 'Safeguarding standards' is a separate
+# two-value vocabulary {'Met', 'Not met'}.
+#
+# Collision check: 'Achievement' matches by EXACT list-membership
+# (`candidate in df_columns`, a Python list containment check against the
+# full column-name list, not a substring/regex match) against only
+# ['Achievement', 'Achievement - date of grade'] -- the date-paired column
+# has a different exact string and is never selected. Same check for
+# 'Safeguarding standards' found only itself, its own date-of-grade column,
+# and the unrelated 'Latest OEIF  safeguarding is effective?' column (not
+# mapped to any rc_* field). No legacy OEIF column is accidentally consumed
+# by an rc_ mapping.
@@ -0,0 +1,144 @@
+"""Generate GIAS code->name dictionaries from the live bulk CSV.
+
+Writes:
+  - backend/gias_codes.py                        (canonical Python module)
+  - pipeline/scripts/gias_codes.py               (byte-identical copy)
+  - pipeline/transform/seeds/gias_code_names.csv (dbt seed for drift test)
+
+Run from the repo root whenever the dbt drift test warns that DfE
+added/renamed a value:  python pipeline/scripts/generate_gias_codes.py
+"""
+
+from __future__ import annotations
+
+import io
+import sys
+from datetime import date, timedelta
+from pathlib import Path
+
+import pandas as pd
+import requests
+
+GIAS_URL = (
+    "https://ea-edubase-api-prod.azurewebsites.net"
+    "/edubase/downloads/public/edubasealldata{date}.csv"
+)
+
+# (CSV code column, CSV name column, python dict name, seed field key)
+FIELDS = [
+    ("TypeOfEstablishment (code)", "TypeOfEstablishment (name)", "SCHOOL_TYPE", "school_type"),
+    ("EstablishmentStatus (code)", "EstablishmentStatus (name)", "ESTABLISHMENT_STATUS", "establishment_status"),
+    ("PhaseOfEducation (code)", "PhaseOfEducation (name)", "PHASE_OF_EDUCATION", "phase_of_education"),
+    ("OfficialSixthForm (code)", "OfficialSixthForm (name)", "OFFICIAL_SIXTH_FORM", "official_sixth_form"),
+    ("ReligiousCharacter (code)", "ReligiousCharacter (name)", "RELIGIOUS_CHARACTER", "religious_character"),
+    ("AdmissionsPolicy (code)", "AdmissionsPolicy (name)", "ADMISSIONS_POLICY", "admissions_policy"),
+]
+
+MODULE_HEADER = '''"""GIAS code -> name dictionaries.
+
+GENERATED by pipeline/scripts/generate_gias_codes.py from the GIAS bulk CSV
+— do not edit by hand; rerun the script when the dbt drift test warns.
+The canonical file is backend/gias_codes.py; pipeline/scripts/gias_codes.py
+must be byte-identical (enforced by backend/tests/test_gias_codes.py).
+"""
+
+from __future__ import annotations
+
+import logging
+import math
+
+logger = logging.getLogger(__name__)
+
+'''
+
+MODULE_FOOTER = '''
+
+def translate(code, mapping: dict[int, str]) -> str | None:
+    """Translate a GIAS code to its display name.
+
+    None/NaN -> None (column absent or suppressed). Unknown codes degrade to
+    "Unknown (<code>)" with a warning so a new DfE value never blanks the UI.
+    """
+    if code is None or (isinstance(code, float) and math.isnan(code)):
+        return None
+    code = int(code)
+    if code not in mapping:
+        logger.warning("Unknown GIAS code %s (not in dictionary)", code)
+        return f"Unknown ({code})"
+    return mapping[code]
+'''
+
+
+def download_csv() -> pd.DataFrame:
+    for day in (date.today(), date.today() - timedelta(days=1)):
+        url = GIAS_URL.format(date=day.strftime("%Y%m%d"))
+        print(f"Downloading {url}")
+        resp = requests.get(url, timeout=300)
+        if resp.status_code == 404:
+            continue
+        resp.raise_for_status()
+        return pd.read_csv(
+            io.StringIO(resp.content.decode("latin-1")),
+            dtype=str, keep_default_na=False,
+        )
+    sys.exit("GIAS CSV not available for today or yesterday")
+
+
+def main() -> None:
+    repo = Path(__file__).resolve().parents[2]
+    df = download_csv()
+
+    module_parts = [MODULE_HEADER]
+    seed_rows: list[tuple[str, int, str]] = []
+
+    for code_col, name_col, dict_name, field_key in FIELDS:
+        pairs = (
+            df[[code_col, name_col]]
+            .loc[lambda d: d[code_col] != ""]
+            .drop_duplicates()
+        )
+        by_code: dict[int, set] = {}
+        for c, n in pairs.itertuples(index=False):
+            by_code.setdefault(int(c), set()).add(n)
+        mapping = []
+        for code, names in sorted(by_code.items()):
+            named = sorted(n for n in names if n != "")
+            if len(named) > 1:
+                sys.exit(f"{code_col}: code {code} maps to multiple names {named} — investigate before generating")
+            # Codes that only ever appear with a blank (name) are GIAS
+            # "not recorded" sentinels (e.g. ReligiousCharacter 99,
+            # AdmissionsPolicy 9). Map them to "" so the API serves the same
+            # empty string the old name pipeline did — the "Unknown (<code>)"
+            # path is reserved for genuinely new codes.
+            mapping.append((code, named[0] if named else ""))
+        lines = [f"{dict_name}: dict[int, str] = {{"]
+        for code, name in mapping:
+            escaped = name.replace('"', '\\"')
+            lines.append(f'    {code}: "{escaped}",')
+        lines.append("}\n")
+        module_parts.append("\n".join(lines))
+        seed_rows += [(field_key, code, name) for code, name in mapping]
+
+    module = "\n".join(module_parts) + MODULE_FOOTER
+
+    (repo / "backend" / "gias_codes.py").write_text(module)
+    (repo / "pipeline" / "scripts" / "gias_codes.py").write_text(module)
+
+    seed_path = repo / "pipeline" / "transform" / "seeds" / "gias_code_names.csv"
+    with open(seed_path, "w", newline="") as fh:
+        import csv
+        w = csv.writer(fh)
+        w.writerow(["field", "code", "name"])
+        w.writerows(seed_rows)
+
+    print(f"Wrote backend/gias_codes.py, pipeline/scripts/gias_codes.py, {seed_path.name}")
+    print("\nKey codes for the dbt work (Task 3):")
+    for field in ("establishment_status", "phase_of_education", "official_sixth_form"):
+        print(f"  {field}:")
+        for f, code, name in seed_rows:
+            if f == field:
+                print(f"    {code} = {name}")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,155 @@
+"""GIAS code -> name dictionaries.
+
+GENERATED by pipeline/scripts/generate_gias_codes.py from the GIAS bulk CSV
+— do not edit by hand; rerun the script when the dbt drift test warns.
+The canonical file is backend/gias_codes.py; pipeline/scripts/gias_codes.py
+must be byte-identical (enforced by backend/tests/test_gias_codes.py).
+"""
+
+from __future__ import annotations
+
+import logging
+import math
+
+logger = logging.getLogger(__name__)
+
+
+SCHOOL_TYPE: dict[int, str] = {
+    1: "Community school",
+    2: "Voluntary aided school",
+    3: "Voluntary controlled school",
+    5: "Foundation school",
+    6: "City technology college",
+    7: "Community special school",
+    8: "Non-maintained special school",
+    10: "Other independent special school",
+    11: "Other independent school",
+    12: "Foundation special school",
+    14: "Pupil referral unit",
+    15: "Local authority nursery school",
+    18: "Further education",
+    24: "Secure units",
+    25: "Offshore schools",
+    26: "Service children's education",
+    27: "Miscellaneous",
+    28: "Academy sponsor led",
+    29: "Higher education institutions",
+    30: "Welsh establishment",
+    31: "Sixth form centres",
+    32: "Special post 16 institution",
+    33: "Academy special sponsor led",
+    34: "Academy converter",
+    35: "Free schools",
+    36: "Free schools special",
+    37: "British schools overseas",
+    38: "Free schools alternative provision",
+    39: "Free schools 16 to 19",
+    40: "University technical college",
+    41: "Studio schools",
+    42: "Academy alternative provision converter",
+    43: "Academy alternative provision sponsor led",
+    44: "Academy special converter",
+    45: "Academy 16-19 converter",
+    46: "Academy 16 to 19 sponsor led",
+    49: "Online provider",
+    56: "Institution funded by other government department",
+    57: "Academy secure 16 to 19",
+}
+
+ESTABLISHMENT_STATUS: dict[int, str] = {
+    1: "Open",
+    2: "Closed",
+    3: "Open, but proposed to close",
+    4: "Proposed to open",
+}
+
+PHASE_OF_EDUCATION: dict[int, str] = {
+    0: "Not applicable",
+    1: "Nursery",
+    2: "Primary",
+    3: "Middle deemed primary",
+    4: "Secondary",
+    5: "Middle deemed secondary",
+    6: "16 plus",
+    7: "All-through",
+}
+
+OFFICIAL_SIXTH_FORM: dict[int, str] = {
+    0: "Not applicable",
+    1: "Has a sixth form",
+    2: "Does not have a sixth form",
+    9: "",
+}
+
+RELIGIOUS_CHARACTER: dict[int, str] = {
+    0: "Does not apply",
+    2: "Church of England",
+    3: "Roman Catholic",
+    4: "Methodist",
+    5: "Jewish",
+    6: "None",
+    7: "Muslim",
+    8: "Seventh Day Adventist",
+    9: "Church of England/Methodist",
+    10: "Methodist/Church of England",
+    11: "Church of England/Roman Catholic",
+    12: "Church of England/United Reformed Church",
+    13: "Roman Catholic/Church of England",
+    14: "Quaker",
+    15: "Christian",
+    16: "United Reformed Church",
+    17: "Congregational Church",
+    18: "Free Church",
+    19: "Church of England/Free Church",
+    20: "Church of England/Christian",
+    21: "Sikh",
+    22: "Greek Orthodox",
+    24: "Buddhist",
+    25: "Hindu",
+    26: "Moravian",
+    28: "Inter- / non- denominational",
+    29: "Multi-faith",
+    30: "Church of England/Methodist/United Reform Church/Baptist",
+    31: "Anglican",
+    32: "Anglican/Christian",
+    33: "Anglican/Evangelical",
+    34: "Anglican/Church of England",
+    35: "Catholic",
+    36: "Charadi Jewish",
+    37: "Christian/Evangelical",
+    38: "Christian Science",
+    39: "Christian/Methodist",
+    40: "Christian/non-denominational",
+    41: "Church of England/Evangelical",
+    42: "Islam",
+    43: "Orthodox Jewish",
+    44: "Plymouth Brethren Christian Church",
+    45: "Protestant",
+    46: "Protestant/Evangelical",
+    47: "Reformed Baptist",
+    48: "Roman Catholic/Anglican",
+    49: "Sunni Deobandi",
+    99: "",
+}
+
+ADMISSIONS_POLICY: dict[int, str] = {
+    0: "Not applicable",
+    2: "Selective",
+    4: "Non-selective",
+    9: "",
+}
+
+
+def translate(code, mapping: dict[int, str]) -> str | None:
+    """Translate a GIAS code to its display name.
+
+    None/NaN -> None (column absent or suppressed). Unknown codes degrade to
+    "Unknown (<code>)" with a warning so a new DfE value never blanks the UI.
+    """
+    if code is None or (isinstance(code, float) and math.isnan(code)):
+        return None
+    code = int(code)
+    if code not in mapping:
+        logger.warning("Unknown GIAS code %s (not in dictionary)", code)
+        return f"Unknown ({code})"
+    return mapping[code]
@@ -19,6 +19,8 @@ import psycopg2
 import psycopg2.extras
 import typesense

+from gias_codes import PHASE_OF_EDUCATION, RELIGIOUS_CHARACTER, SCHOOL_TYPE, translate
+
 COLLECTION_SCHEMA = {
    "fields": [
        {"name": "urn", "type": "int32"},
@@ -44,10 +46,10 @@ QUERY_BASE = """
    SELECT
        s.urn,
        s.school_name,
-        s.phase,
-        s.school_type,
+        s.phase_code,
+        s.school_type_code,
        l.local_authority_name as local_authority,
-        s.religious_character,
+        s.religious_character_code,
        s.ofsted_grade,
        l.postcode,
        s.headteacher_name,
@@ -85,14 +87,15 @@ def build_document(row: dict) -> dict:
        "id": str(row["urn"]),
        "urn": row["urn"],
        "school_name": row["school_name"] or "",
-        "phase": row["phase"] or "",
-        "school_type": row["school_type"] or "",
+        "phase": translate(row["phase_code"], PHASE_OF_EDUCATION) or "",
+        "school_type": translate(row["school_type_code"], SCHOOL_TYPE) or "",
        "local_authority": row["local_authority"] or "",
        "postcode": row["postcode"] or "",
    }

-    if row.get("religious_character"):
-        doc["religious_character"] = row["religious_character"]
+    religious_character = translate(row.get("religious_character_code"), RELIGIOUS_CHARACTER)
+    if religious_character:
+        doc["religious_character"] = religious_character
    if row.get("ofsted_grade"):
        doc["ofsted_rating"] = OFSTED_LABELS.get(row["ofsted_grade"], "")
    if row.get("headteacher_name"):
@@ -0,0 +1,17 @@
+-- Macro: Parse Ofsted Report Card grade (post-Nov 2025 framework) from text
+-- into the 5-point scale. Real values confirmed via a live sample of the MI
+-- CSV (see pipeline/scripts/diagnose_compare_gaps.py's
+-- "TASK 7 VALUE SAMPLE 2026-07-12" note) -- unrecognised text (including the
+-- 'NULL' sentinel used by the source CSV for blanks) parses to NULL, never
+-- errors.
+
+{% macro parse_report_card_grade(column_name) %}
+    case lower(trim(nullif({{ column_name }}, 'NULL')))
+        when 'exceptional' then 1
+        when 'strong standard' then 2
+        when 'expected standard' then 3
+        when 'needs attention' then 4
+        when 'urgent improvement' then 5
+        else null
+    end
+{% endmacro %}
@@ -15,8 +15,11 @@ current_ks2 as (
        year, total_pupils, eligible_pupils,
        rwm_expected_pct, rwm_high_pct,
        reading_expected_pct, reading_high_pct, reading_avg_score, reading_progress,
+        reading_progress_lower_ci, reading_progress_upper_ci,
        writing_expected_pct, writing_high_pct, writing_progress,
+        writing_progress_lower_ci, writing_progress_upper_ci, writing_working_towards_pct,
        maths_expected_pct, maths_high_pct, maths_avg_score, maths_progress,
+        maths_progress_lower_ci, maths_progress_upper_ci,
        gps_expected_pct, gps_high_pct, gps_avg_score, science_expected_pct,
        reading_absence_pct, writing_absence_pct, maths_absence_pct, gps_absence_pct, science_absence_pct,
        rwm_expected_boys_pct, rwm_high_boys_pct, rwm_expected_girls_pct, rwm_high_girls_pct,
@@ -33,8 +36,11 @@ predecessor_ks2 as (
        ks2.year, ks2.total_pupils, ks2.eligible_pupils,
        ks2.rwm_expected_pct, ks2.rwm_high_pct,
        ks2.reading_expected_pct, ks2.reading_high_pct, ks2.reading_avg_score, ks2.reading_progress,
+        ks2.reading_progress_lower_ci, ks2.reading_progress_upper_ci,
        ks2.writing_expected_pct, ks2.writing_high_pct, ks2.writing_progress,
+        ks2.writing_progress_lower_ci, ks2.writing_progress_upper_ci, ks2.writing_working_towards_pct,
        ks2.maths_expected_pct, ks2.maths_high_pct, ks2.maths_avg_score, ks2.maths_progress,
+        ks2.maths_progress_lower_ci, ks2.maths_progress_upper_ci,
        ks2.gps_expected_pct, ks2.gps_high_pct, ks2.gps_avg_score, ks2.science_expected_pct,
        ks2.reading_absence_pct, ks2.writing_absence_pct, ks2.maths_absence_pct, ks2.gps_absence_pct, ks2.science_absence_pct,
        ks2.rwm_expected_boys_pct, ks2.rwm_high_boys_pct, ks2.rwm_expected_girls_pct, ks2.rwm_high_girls_pct,
@@ -18,7 +18,8 @@ current_ks4 as (
        english_maths_strong_pass_pct, english_maths_standard_pass_pct,
        ebacc_entry_pct, ebacc_strong_pass_pct, ebacc_standard_pass_pct, ebacc_avg_score,
        gcse_grade_91_pct,
-        sen_pct, sen_support_pct, sen_ehcp_pct
+        sen_pct, sen_support_pct, sen_ehcp_pct,
+        progress_8_banding, attainment_8_disadvantage_gap, progress_8_disadvantage_gap
    from all_ks4
 ),

@@ -34,7 +35,8 @@ predecessor_ks4 as (
        ks4.english_maths_strong_pass_pct, ks4.english_maths_standard_pass_pct,
        ks4.ebacc_entry_pct, ks4.ebacc_strong_pass_pct, ks4.ebacc_standard_pass_pct, ks4.ebacc_avg_score,
        ks4.gcse_grade_91_pct,
-        ks4.sen_pct, ks4.sen_support_pct, ks4.sen_ehcp_pct
+        ks4.sen_pct, ks4.sen_support_pct, ks4.sen_ehcp_pct,
+        ks4.progress_8_banding, ks4.attainment_8_disadvantage_gap, ks4.progress_8_disadvantage_gap
    from all_ks4 ks4
    inner join {{ ref('int_school_lineage') }} lin
        on ks4.urn = lin.predecessor_urn
@@ -8,18 +8,46 @@ models:
        tests: [not_null, unique]
      - name: school_name
        tests: [not_null]
-      - name: phase
+      - name: phase_code
        description: >
-          Primary / Secondary / All-through etc. May be null for a small number
+          GIAS PhaseOfEducation code (2 = Primary, 4 = Secondary, 7 = All-through,
+          etc. — see seeds/gias_code_names.csv). May be null for a small number
          of independent schools where GIAS publishes "Not Applicable", no
          statutory age range, and the school name gives no hint.
        tests:
          - not_null:
              severity: warn
-      - name: status
+      - name: has_sixth_form
+        description: >
+          Authoritative sixth-form flag from GIAS OfficialSixthForm.
+          "Has a sixth form" => true; "Does not have a sixth form" and
+          "Not applicable" => false; blank GIAS value falls back to
+          statutory_high_age >= 18. Replaces the age_range-contains-"18"
+          heuristic (spec 2026-07-07 §3).
+        tests:
+          - not_null
+          - accepted_values:
+              values: [true, false]
+      - name: status_code
+        description: GIAS EstablishmentStatus code (1 = Open, 3 = Open but proposed to close)
        tests:
          - accepted_values:
-              values: ["Open"]
+              values: [1, 3]
+      - name: school_type_code
+        tests:
+          - accepted_values:
+              severity: warn
+              values: [1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 14, 15, 18, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 49, 56, 57]
+      - name: religious_character_code
+        tests:
+          - accepted_values:
+              severity: warn
+              values: [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 99]
+      - name: admissions_policy_code
+        tests:
+          - accepted_values:
+              severity: warn
+              values: [0, 2, 4, 9]

  - name: dim_location
    description: School location dimension with PostGIS geometry
@@ -58,6 +86,13 @@ models:
        tests: [not_null]
      - name: year
        tests: [not_null]
+      - name: reading_progress_lower_ci
+      - name: reading_progress_upper_ci
+      - name: writing_progress_lower_ci
+      - name: writing_progress_upper_ci
+      - name: writing_working_towards_pct
+      - name: maths_progress_lower_ci
+      - name: maths_progress_upper_ci
    tests:
      - unique:
          column_name: "urn || '-' || year"
@@ -69,6 +104,15 @@ models:
        tests: [not_null]
      - name: year
        tests: [not_null]
+      - name: progress_8_banding
+        tests:
+          - accepted_values:
+              values: ['Well above average', 'Above average', 'Average', 'Below average', 'Well below average']
+              config:
+                where: "progress_8_banding is not null"
+                severity: warn
+      - name: attainment_8_disadvantage_gap
+      - name: progress_8_disadvantage_gap
    tests:
      - unique:
          column_name: "urn || '-' || year"
@@ -96,6 +140,11 @@ models:
        tests: [not_null]
      - name: year
        tests: [not_null]
+      - name: second_preference_offers
+      - name: third_preference_offers
+      - name: cross_la_applications
+      - name: cross_la_offers
+      - name: total_offers

  - name: fact_finance
    description: School financial data — one row per URN per year
@@ -111,6 +160,12 @@ models:
      - name: year
        tests: [not_null, unique]

+  - name: fact_ks4_national_averages
+    description: Computed national KS4 averages (means across state schools in our dataset — not official DfE figures) — one row per academic year
+    columns:
+      - name: year
+        tests: [not_null, unique]
+
  - name: fact_deprivation
    description: IDACI deprivation index — one row per URN
    columns:
@@ -31,4 +31,5 @@ select
        else null
    end as longitude
 from {{ ref('stg_gias_establishments') }} s
-where s.status = 'Open'
+-- Must match dim_school's status filter exactly (the API inner-joins the two).
+where s.status_code in (1, 3)
@@ -19,16 +19,17 @@ select
    s.urn,
    s.local_authority_code * 1000 + s.establishment_number as laestab,
    s.school_name,
+    -- Phase in GIAS code space (see seeds/gias_code_names.csv):
+    -- 2 = Primary, 4 = Secondary, 7 = All-through, 0 = Not applicable.
    case
-        -- 1. Trust GIAS phase when it's a real value (not the catch-all "Not Applicable")
-        when s.phase is not null
-             and lower(trim(s.phase)) not in ('not applicable', '', 'unknown')
-            then s.phase
+        -- 1. Trust GIAS phase when it's a real value (0 = the catch-all "Not Applicable")
+        when s.phase_code is not null and s.phase_code != 0
+            then s.phase_code
        -- 2. Infer from statutory age range (independent schools still publish these)
-        when s.statutory_high_age is not null and s.statutory_high_age <= 11 then 'Primary'
-        when s.statutory_low_age is not null and s.statutory_low_age >= 11 then 'Secondary'
+        when s.statutory_high_age is not null and s.statutory_high_age <= 11 then 2
+        when s.statutory_low_age is not null and s.statutory_low_age >= 11 then 4
        when s.statutory_low_age is not null and s.statutory_high_age is not null
-             and s.statutory_low_age < 11 and s.statutory_high_age > 11 then 'All-through'
+             and s.statutory_low_age < 11 and s.statutory_high_age > 11 then 7
        -- 3. Fallback: infer from school name (covers independents with missing ages)
        when s.school_name ilike '%primary%'
             or s.school_name ilike '%infant%'
@@ -36,22 +37,29 @@ select
             or s.school_name ilike '%preparatory%'
             or s.school_name ilike '% prep school%'
             or s.school_name ilike '% prep %'
-            then 'Primary'
+            then 2
        when s.school_name ilike '%secondary%'
             or s.school_name ilike '%high school%'
             or s.school_name ilike '%grammar%'
             or s.school_name ilike '%senior school%'
             or s.school_name ilike '%upper school%'
-            then 'Secondary'
-        -- 4. Give up — leave phase null so the UI renders no pill
+            then 4
+        -- 4. Give up — null renders no phase pill
        else null
-    end as phase,
-    s.school_type,
+    end as phase_code,
+    s.school_type_code,
    s.academy_trust_name,
    s.academy_trust_uid,
-    s.religious_character,
+    s.religious_character_code,
    s.gender,
    s.statutory_low_age || '-' || s.statutory_high_age as age_range,
+    -- GIAS OfficialSixthForm in code space: 1 = has, 2 = does not, 0 = N/A.
+    -- Null (rare, new establishments) falls back to the statutory age range.
+    case
+        when s.official_sixth_form_code = 1 then true
+        when s.official_sixth_form_code in (0, 2) then false
+        else coalesce(s.statutory_high_age >= 18, false)
+    end as has_sixth_form,
    s.capacity,
    s.total_pupils,
    concat_ws(' ', s.head_title, s.head_first_name, s.head_last_name) as headteacher_name,
@@ -59,9 +67,9 @@ select
    s.telephone,
    s.open_date,
    s.close_date,
-    s.status,
+    s.status_code,
    s.nursery_provision,
-    s.admissions_policy,
+    s.admissions_policy_code,

    -- Latest Ofsted (populated after monthly Ofsted pipeline runs)
    {% if ofsted_relation is not none %}
@@ -80,4 +88,6 @@ from schools s
 {% if ofsted_relation is not none %}
 left join {{ ref('int_ofsted_latest') }} o on s.urn = o.urn
 {% endif %}
-where s.status = 'Open'
+-- 1 = Open; 3 = Open, but proposed to close (still operating; drops out when
+-- GIAS flips to Closed — marts fully rebuild each run).
+where s.status_code in (1, 3)
@@ -5,9 +5,14 @@ select
    year,
    school_phase,
    places_offered,
+    total_offers,
    total_applications,
    first_preference_applications,
    first_preference_offers,
+    second_preference_offers,
+    third_preference_offers,
+    cross_la_applications,
+    cross_la_offers,
    first_preference_offer_pct,
    oversubscription_ratio,
    oversubscribed,
@@ -15,13 +15,20 @@ select
    reading_high_pct,
    reading_avg_score,
    reading_progress,
+    reading_progress_lower_ci,
+    reading_progress_upper_ci,
    writing_expected_pct,
    writing_high_pct,
    writing_progress,
+    writing_progress_lower_ci,
+    writing_progress_upper_ci,
+    writing_working_towards_pct,
    maths_expected_pct,
    maths_high_pct,
    maths_avg_score,
    maths_progress,
+    maths_progress_lower_ci,
+    maths_progress_upper_ci,
    gps_expected_pct,
    gps_high_pct,
    gps_avg_score,
@@ -0,0 +1,25 @@
+{{ config(materialized='table') }}
+
+-- Mart: Computed national KS4 averages — one row per academic year.
+-- Unlike fact_ks2_national_averages (official DfE figures), DfE publishes no
+-- KS4 national-headline dataset we ingest yet, so these are means computed
+-- across the state schools in our dataset. Computed once at build time so the
+-- API never has to aggregate the full performance table per request.
+-- Semantics match the API's previous per-request computation: rows where
+-- attainment_8_score is non-null; per-column means ignore NULLs.
+
+select
+    year,
+    round(avg(attainment_8_score)::numeric, 2)               as attainment_8_score,
+    round(avg(progress_8_score)::numeric, 2)                 as progress_8_score,
+    round(avg(english_maths_standard_pass_pct)::numeric, 2)  as english_maths_standard_pass_pct,
+    round(avg(english_maths_strong_pass_pct)::numeric, 2)    as english_maths_strong_pass_pct,
+    round(avg(ebacc_entry_pct)::numeric, 2)                  as ebacc_entry_pct,
+    round(avg(ebacc_standard_pass_pct)::numeric, 2)          as ebacc_standard_pass_pct,
+    round(avg(ebacc_strong_pass_pct)::numeric, 2)            as ebacc_strong_pass_pct,
+    round(avg(ebacc_avg_score)::numeric, 2)                  as ebacc_avg_score,
+    round(avg(gcse_grade_91_pct)::numeric, 2)                as gcse_grade_91_pct
+from {{ ref('fact_ks4_performance') }}
+where attainment_8_score is not null
+group by year
+order by year
@@ -16,6 +16,9 @@ select
    progress_8_score,
    progress_8_lower_ci,
    progress_8_upper_ci,
+    progress_8_banding,
+    attainment_8_disadvantage_gap,
+    progress_8_disadvantage_gap,
    progress_8_english,
    progress_8_maths,
    progress_8_ebacc,
@@ -25,13 +25,20 @@ select
    ks2.reading_high_pct,
    ks2.reading_avg_score,
    ks2.reading_progress,
+    ks2.reading_progress_lower_ci,
+    ks2.reading_progress_upper_ci,
    ks2.writing_expected_pct,
    ks2.writing_high_pct,
    ks2.writing_progress,
+    ks2.writing_progress_lower_ci,
+    ks2.writing_progress_upper_ci,
+    ks2.writing_working_towards_pct,
    ks2.maths_expected_pct,
    ks2.maths_high_pct,
    ks2.maths_avg_score,
    ks2.maths_progress,
+    ks2.maths_progress_lower_ci,
+    ks2.maths_progress_upper_ci,
    ks2.gps_expected_pct,
    ks2.gps_high_pct,
    ks2.gps_avg_score,
@@ -61,6 +68,9 @@ select
    ks4.progress_8_maths,
    ks4.progress_8_ebacc,
    ks4.progress_8_open,
+    ks4.progress_8_banding,
+    ks4.attainment_8_disadvantage_gap,
+    ks4.progress_8_disadvantage_gap,
    ks4.english_maths_strong_pass_pct,
    ks4.english_maths_standard_pass_pct,
    ks4.ebacc_entry_pct,
--- a/Show More
+++ b/Show More