feat(destinations): say what happened to a school's leavers, without republishing what DfE withheld #137
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# Destination Measures — Design
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**Date:** 2026-08-28
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**Status:** awaiting review
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**Scope:** secondary school detail pages only
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## Goal
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Say what happened to a school's leavers after they left. Two sections on the
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secondary template:
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- **After Year 11** — every secondary, from the KS4 destination measures
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- **After the sixth form** — sixth-form schools only, from the 16-18 measures
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This replaces the "Post-16 destination data coming soon" placeholder standing in
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`nextjs-app/components/school/SecondaryAdmissionsSection.tsx:117` since the exam
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phase taxonomy work, and fills the `ks5_destinations_pct` slot specified but
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never built in `2026-07-07-exam-phase-taxonomy-design.md:201`.
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Mockup, with all three data states live:
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<https://claude.ai/code/artifact/5be149d6-252f-473c-9a4f-4c36b05161b0>
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## The finding that shapes everything
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**Suppression is per cell, and the cells sum to the cohort.**
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DfE withholds a figure it considers disclosive by writing `c`. It does this at
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the level of an individual destination category, not the whole school, and it
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publishes the cohort total alongside. The categories form a clean partition. So
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where exactly one category is suppressed, subtracting the published ones from the
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cohort recovers it exactly.
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Verified against three real schools in the 2022/23 file:
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| School | URN | Withheld | Recovers to |
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|---|---|---|---|
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| North East Futures UTC | 145900 | School sixth form | **3 pupils** |
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| Whitley Bay High School | 108638 | Further education | **18 pupils** |
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| St Matthew's RC High School | 148389 | School sixth form | **4 pupils** |
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Those are the precise numbers the `c` exists to hide, and in a random 400-school
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sample **22% of mainstream secondaries** have exactly one suppressed category in
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their disadvantaged group. This is the normal case, not an edge case.
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Two rules follow, and everything else in this document is downstream of them.
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**R1 — Never render a derived remainder.** Not as a number, and not as a bar
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segment: a segment sized by the residual can be read straight off the axis. Where
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any category in a pupil group is suppressed, the page shows the published
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categories, says the rest are withheld, and stops.
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**R2 — Never aggregate across a suppression boundary.** A group total is
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publishable only when DfE published that total itself, or when the aggregate
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spans **two or more** suppressed cells. Summing published components to fill a
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gap is R1 with extra steps.
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**R3 — The three pupil groups are one disclosure surface, not three.**
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Disadvantaged and Not-known-to-be-disadvantaged partition All pupils, so
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rendering any *two* of them recovers the third. Where a category is suppressed in
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the disadvantaged group, it must therefore also be withheld from **all other
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pupils** — the all-pupils view is the primary one and keeps it.
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This costs almost nothing, because DfE already applies the same masking: across
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the sample, 493 of 498 suppressed disadvantaged cells were suppressed in the
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other group too. The mart enforces the remaining 5, which fell on 2 schools of
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262. **The all-pupils bar is unaffected** — masking the whole page wherever the
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disadvantaged group is thin would remove the bar from 80% of schools, and is not
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what this rule says.
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R1 and R2 both hold within a group and still leak across the switch, which is why
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R3 is stated separately.
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### The convention that would break this quietly
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`macros/safe_numeric.sql` coerces every EES sentinel — `z`, `c`, `x`, `q`, `u` —
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to `NULL`, deliberately and correctly for attainment, where "suppressed" and "no
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data" are equally unrenderable. Here they are not the same thing: one must print
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*withheld*, the other must print nothing at all, and the difference is what keeps
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R1 enforceable.
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**`safe_numeric` must not be used on destination counts.** The staging model
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keeps the sentinel in a companion status column. This is the single most likely
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way for this feature to regress into a disclosure, so it gets its own dbt test.
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## What is actually available
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Measured against the EES public API (open, no key). Both datasets carry
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`geographicLevel: School` with `urn` on every location option, so the join to
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`dim_school` is direct.
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| | KS4 | 16-18 |
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|---|---|---|
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| Dataset id | `019d4f41-22d1-71b2-a1a7-f3b91026815b` | `019d4e73-6440-7523-b60c-bfab1ad4a30d` |
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| Rows | 1,871,739 | 3,862,658 |
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| Institutions | 4,946 | 3,065 |
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| Time periods | 2009/10–2022/23 | 2016/17–2022/23 |
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**Destination categories (KS4).** School sixth form · Sixth form college ·
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Further education · Other education destination · Sustained apprenticeships (with
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level breakdown) · Sustained employment destination · Not recorded as a sustained
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destination · Activity not captured. Plus the aggregates `Sustained education
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destination` and `Sustained education, employment & apprenticeships`.
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**16-18 adds** UK higher education institution and FE split by level, which is
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what makes the post-16 section worth having.
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**Breakdowns.** `Disadvantage Status` gives Disadvantaged / Not known to be
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disadvantaged / Total — exactly the three-way switch. Sex, ethnicity, FSM status,
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prior attainment and SEN provision also travel in the same table; we ingest none
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of them.
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**Indicators.** Both counts and percentages, plus the cohort size. Bar widths use
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the counts — the published percentages do not sum to 100.
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### Coverage, and what degrades
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Random 400-school sample, 2022/23, mainstream secondaries (n=262):
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| View | Published | Consequence |
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|---|---|---|
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| All pupils, all categories | **100%** | Full bar works everywhere |
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| Disadvantaged, headline rate | 95% | Gap panel works |
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| Disadvantaged, three grouped cards | 68% | Degrades card by card |
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| Disadvantaged, all six categories | **20%** | Bar unusable for this group |
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Special schools and alternative provision are far worse: 13% and 41% respectively
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have the whole cohort suppressed even for all pupils. The empty state is
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load-bearing, not defensive.
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## The display
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Question-led. Three cards over one bar, with the cards acting as a lens on the
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bar rather than a summary beside it — hovering a card dims the bar, table and
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England reference to the categories that card is built from. The full mockup is
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linked above; what matters for implementation:
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**The headline is not the sustained rate.** That figure sits between 92% and 97%
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for nearly every school in England. The mix is what varies, so the mix leads.
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**The grouping is ours, not DfE's.** "Academic route" = school sixth form +
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sixth-form college; "College" = FE and other colleges; "Work" = apprenticeship +
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employment. This is the most arguable thing on the page, so it lives in one place
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in `lib/destinations.ts`, is explained in a tooltip, and is reversible in one
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edit.
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**The absence is hatched neutral, never a colour.** "Activity not captured" means
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no record in the sources DfE holds — it includes independent schools, moving
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abroad and private training. Colouring it as a bad outcome would be a factual
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error rendered in CSS. The hatch also fixes a real contrast problem: neutral
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against the employment blue failed CVD separation at ΔE 7.6, and texture is the
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secondary encoding that rescues it. Every other adjacent pair clears ΔE 10.9
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under protanopia.
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**Colour tokens.** Education is one hue in three steps (school-like to
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college-like); apprenticeship and employment are separate hues. Six new tokens in
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`globals.css`, defined in both themes, per the existing token discipline.
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**The disadvantage split rides the same control.** One visualisation serving
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three cohorts, with the England reference repointing to the matching national
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group. The gap statement stays visible below the bar whatever is selected,
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because a gap nobody clicks on is a gap nobody sees.
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## Data model
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### Extraction
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A new `tap-uk-ees-destinations` extractor, separate from `tap-uk-ees`. The
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existing tap downloads a release ZIP and reads a CSV inside it; the destinations
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files are far larger than we need and the query API filters server-side, so this
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one POSTs to `/v1/data-sets/{id}/query` and pages through results.
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With every dimension pinned — destination measures, disadvantage status, sex
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Total, characteristic topic Total — one year returns **252,610 rows** across all
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geographic levels. Three school-level years is comfortably tractable.
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Pinning is mandatory, not an optimisation: leaving the characteristic dimensions
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unconstrained returned 45 rows where 9 were wanted, because every breakdown
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shares one table.
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The tap emits the raw value as text. **It does not coerce `c`.**
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### Staging
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`stg_ees_ks4_destinations` / `stg_ees_ks5_destinations`. Each raw value becomes
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two columns:
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```sql
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case when raw ~ '^-?[0-9]+(\.[0-9]+)?$' then raw::numeric end as pupils,
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case
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when raw ~ '^-?[0-9]+(\.[0-9]+)?$' then 'published'
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when lower(trim(raw)) = 'c' then 'suppressed'
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else 'not_applicable'
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end as status
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```
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### Marts
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`fact_ks4_destinations` and `fact_ks5_destinations`, **long format**:
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```
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urn, year, pupil_group, destination_category, cohort_pupils, pupils, percentage, status
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```
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This departs from the wide house pattern (`fact_ks4_performance` and friends) on
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purpose. `pupil_group` is a genuine third dimension; going wide would need three
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sets of every column, and R2 is far easier to test on rows than on columns.
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Roughly 8 categories × 3 groups × 4,946 schools × 3 years ≈ 356k rows.
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`fact_destination_national` carries the same grain for England, so the page's
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England reference repoints with the switch.
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### dbt tests
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- `assert_destinations_no_derived_remainder` — for every (urn, year,
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pupil_group) with exactly one suppressed category, assert no aggregate row
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exists that would let the residual be recovered. **This is the R1 guard.**
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- `assert_destinations_group_masking` — for every (urn, year, category), if the
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disadvantaged group carries `suppressed`, so does the other-pupils group.
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**This is the R3 guard**, applied in the mart so no consumer can reach an
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unmasked combination.
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- `assert_destination_status_null_agreement` — `pupils is null` wherever
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`status != 'published'`, and never null where it is.
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- `assert_destinations_join_dim_school` — no orphaned URNs, matching the
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existing `assert_no_orphaned_facts` pattern.
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## API
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`GET /api/schools/{urn}` gains a `destinations` block:
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```json
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{
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"ks4": {
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"cohort_year": "2022/23",
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"published": "2026-04",
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"groups": {
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"all": { "cohort": 180, "categories": [ … ], "aggregates": { … } },
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"disadvantaged": { … },
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"other": { … }
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}
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},
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"ks5": { … }
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}
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```
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Each category carries `pupils`, `percentage` and `status`. **The serialiser never
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emits a computed remainder**, and a backend test asserts that a group containing a
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suppressed category serialises no total that closes the gap.
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`null` for the whole block where nothing is published — the frontend renders the
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empty state from its absence, not from a sentinel.
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## Frontend
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| File | Kind | Job |
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|---|---|---|
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| `lib/destinations.ts` | pure | Category list, the academic/college/work grouping, `canAggregate()` enforcing R2, percentage derivation from counts |
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| `components/school/DestinationsSection.tsx` | server | Section shell, renders **all pupils** into the HTML |
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| `components/school/DestinationsView.tsx` | client | Cohort switch, card↔bar linkage |
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| `components/school/Post16DestinationsSection.tsx` | server | Year 13 section, sixth-form schools only |
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| `app/globals.css` | tokens | Six destination colours, both themes |
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Server-first matches the directory's existing discipline — every component in
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`components/school/` is a server component except `AdmissionsViewToggle`, which
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is the precedent this follows. All-pupils figures are in the HTML for crawlers
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and for no-JS; only the switch and the hover linkage need the client.
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`lib/schoolSections.ts` gains `hasKs4Destinations` / `hasKs5Destinations` flags
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and the nav items, following the existing `computeSchoolFlags` pattern.
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**Placement** on the secondary template: GCSE results → After Year 11 → After the
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sixth form → admissions. Destinations follow attainment because they answer "and
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then what happened".
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**Dating.** The latest destination year is 2022/23, published April 2026, while
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the site's newest KS4 year is 2024/25. The section header states its own cohort
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year, or it reads as stale data next to the GCSE section above it.
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## Edge states
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| State | Frequency | Behaviour |
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|---|---|---|
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| Whole cohort suppressed | 13% of special, 41% of AP | Section renders the explanation, no chart |
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| Some categories withheld | 80% of disadvantaged views | Cards degrade individually; **no bar**; table marks withheld rows |
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| Disadvantaged group suppressed entirely | 5% | Switch drops to two options, gap panel not rendered |
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| No sixth form | — | Post-16 section not rendered at all — absence is correct, a "no data" placeholder would imply something is missing |
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| School too new | — | "First figures expected in 2026", not a bare no |
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## Testing
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Per CLAUDE.md, user-facing behaviour extends `e2e/` in the same PR.
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**Unit** — `lib/destinations.ts` is where R1 and R2 live, so it carries the
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heaviest tests: `canAggregate()` refuses a group containing one suppressed cell,
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allows one spanning two, and the bar builder refuses to emit segments for any
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group with suppression. These are the tests that must fail loudly if someone
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later "fixes" a gap in the chart.
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**dbt** — the three tests above.
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**Backend** — the serialiser emits no closing total for a partially suppressed
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group.
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**E2E** — a school with full data renders three cards and a bar; a school with a
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partially suppressed disadvantaged group renders the withheld state and **no bar
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element**; a suppressed school renders the explanation; a school with no sixth
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form renders no post-16 section.
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Note the staging caveat: mart changes are inert until the Airflow pipeline runs,
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and the staging E2E gate runs post-merge.
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## Out of scope
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- **Compare view and rankings.** The long mart shape supports both; neither is
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built here. Flagged because "% to a school sixth form" is a plausible rankings
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metric and the mart shape should not have to change to allow it.
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- **Ethnicity, sex, SEN and prior-attainment breakdowns.** Available in the same
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file, ingested deliberately not at all — each is a separate editorial decision
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about what a school page should assert.
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- **Longer term destinations** (3 and 5 years out) and **Progression to higher
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education** — separate publications, worth a later look for sixth forms.
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- **Primary schools.** No KS2 destination measures publication exists; DfE
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tracking starts at KS4. Naming the secondaries a primary's leavers go to needs
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the National Pupil Database, which is not publishable at that grain.
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## Risks
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**A later change reintroduces the disclosure.** The likeliest route is someone
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applying `safe_numeric` to a destination column for consistency, or adding a
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`coalesce` in a mart. Mitigation is the dbt test plus the unit tests on
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`canAggregate()` — the rule has to be executable, not documentary.
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**The two-year lag reads as staleness.** Mitigated by dating the cohort in the
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section header rather than only in a tooltip.
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**Sixth-form retention will be misread.** "41% went to a school sixth form" says
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nothing about *which* school. The published file reports destination type, never
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destination institution. Copy must never imply "stayed on here", and the tooltip
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should say so.
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**Section length.** The secondary template is already long and this adds two
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sections. If it becomes a problem the post-16 section is the one to collapse
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behind a disclosure, not the Year 11 one.
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## Open questions
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1. Is the disadvantage split its own section or a sub-block inside the
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destinations section? Modelled as a sub-block; it is the most differentiating
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figure on the page and the most easily misread on a small cohort.
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2. Do we ingest the apprenticeship level breakdown (intermediate / advanced /
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higher) now, or collapse to one apprenticeship figure and revisit? Collapsed
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in this design.
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Reference in new issue
Block a user