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

backend/app.py

@@ -677,6 +677,7 @@ async def compare_schools(
         "deprivation": None,
     }
     supplementary_by_urn: dict = {}
+    census_benchmarks = None
     db = None
     try:
         db = database.SessionLocal()
@@ -688,6 +689,31 @@ async def compare_schools(
                 key: supp.get(key, default)
                 for key, default in _EMPTY_SUPPLEMENTARY.items()
             }
+        # Import-time census context benchmarks (fact_census_benchmarks);
+        # absent mart → None, and compute_benchmarks leaves those fields null.
+        try:
+            from .models import CensusBenchmark
+
+            rows = db.query(CensusBenchmark).all()
+            by_phase = {
+                r.phase: {
+                    "year": r.year,
+                    "fsm_pct": r.fsm_pct,
+                    "eal_pct": r.eal_pct,
+                    "median_pupils": r.median_pupils,
+                }
+                for r in rows
+                if getattr(r, "phase", None) in ("primary", "secondary")
+            }
+            if by_phase:
+                census_benchmarks = by_phase
+        except Exception:
+            # Missing mart (or a stubbed session in tests) must never break
+            # the compare payload — and not every session has rollback().
+            try:
+                db.rollback()
+            except Exception:
+                pass
     except Exception:
         supplementary_by_urn = {}
     finally:
@@ -728,7 +754,7 @@ async def compare_schools(
         # 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),
+        "benchmarks": compute_benchmarks(df, census_benchmarks=census_benchmarks),
     }