fix(compare): census-sourced FSM/EAL benchmarks; never fall back across measure definitions

The FSM chip anchored against disadvantaged_pct (a different measure,
FSM6+CLA) whenever fsm_pct was null — which it always was, since the
performance df has no fsm_pct. New fact_census_benchmarks mart supplies
pupil-weighted FSM/EAL means per phase; the KS2-column medians that
produced a bogus 50% 'secondary disadvantaged' anchor are gone.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0146VHeLAWjDVE2B5uU67jCB

pipeline/transform/models/marts/_marts_schema.yml

@@ -133,6 +133,16 @@ models:
       - name: year
         tests: [not_null]
 
+  - name: fact_census_benchmarks
+    description: >
+      State-school context benchmarks from the pupil census — one row per
+      phase (primary/secondary), latest census year. fsm_pct/eal_pct are
+      pupil-weighted means; consumers label them "state-school average
+      (computed from our dataset)", never "England average".
+    columns:
+      - name: phase
+        tests: [not_null, unique]
+
   - name: fact_admissions
     description: School admissions — one row per URN per year
     columns:

pipeline/transform/models/marts/fact_census_benchmarks.sql

@@ -0,0 +1,39 @@
+{{ config(materialized='table') }}
+
+-- Mart: state-school context benchmarks from the pupil census — one row per
+-- phase, latest census year. Computed at import time (never per request).
+-- fsm_pct / eal_pct are pupil-weighted means, i.e. "what % of pupils", not
+-- "the median school" — this matches how DfE quotes national FSM/EAL rates.
+-- Consumers must label these "state-school average (computed from our
+-- dataset)" (spec §8.6), never "England average".
+
+with latest as (
+    select max(year) as year from {{ ref('fact_pupil_characteristics') }}
+),
+
+classified as (
+    select
+        case
+            when p.phase_type_grouping ilike '%primary%'   then 'primary'
+            when p.phase_type_grouping ilike '%secondary%' then 'secondary'
+        end as phase,
+        p.total_pupils,
+        p.fsm_pct,
+        p.eal_pct,
+        l.year
+    from {{ ref('fact_pupil_characteristics') }} p
+    join latest l on p.year = l.year
+    where p.total_pupils is not null and p.total_pupils > 0
+)
+
+select
+    phase,
+    max(year) as year,
+    round((sum(fsm_pct * total_pupils) filter (where fsm_pct is not null)
+        / nullif(sum(total_pupils) filter (where fsm_pct is not null), 0))::numeric, 1) as fsm_pct,
+    round((sum(eal_pct * total_pupils) filter (where eal_pct is not null)
+        / nullif(sum(total_pupils) filter (where eal_pct is not null), 0))::numeric, 1) as eal_pct,
+    round(percentile_cont(0.5) within group (order by total_pupils))::integer as median_pupils
+from classified
+where phase is not null
+group by phase