chore: remove the code the legacy CSV importer left behind

`backend/migration.py` and `scripts/migrate_csv_to_db.py` import `School`,
`SchoolResult`, `init_db` and `set_db_schema_version` — names that no longer
exist. `scripts/geocode_schools.py` imports the same removed ORM model. None of
the three can be imported against the current backend, so they were not dormant
utilities anyone could fall back on; they were files that would fail on the
first line. `backend/version.py` existed only to hand `SCHEMA_VERSION` to that
importer, and the FastAPI lifespan performs no version-triggered import.

Three symbols go with them, each confirmed to have no caller: the unvectorised
`haversine_distance`, superseded by the inline NumPy calculation in search;
`fetcher`, an SWR helper for a dependency this project does not install; and
`kmToMiles`. `calculateDistance` stays — CutoffMapPanel uses it.

Two comments pointed at `migrate_csv_to_db.py --drop` to explain why Payload
owns its own schema. The reason survives the script: blog content must stay
clear of the school marts and Airflow's metadata. Reworded rather than deleted,
so the constraint keeps its justification.

docs/LEGACY_CODE.md records what was removed and where to find it in history. It
also records what was deliberately *not* removed, which is the more useful half:
unused UI components awaiting a design decision, manual data utilities whose
operators a repository search cannot see, and fallbacks that look obsolete but
are load-bearing — `data_loader.py`'s older-mart branches, the generated GIAS
dictionary copies, and the `legacy`-named dbt models that annual DAG selectors
explicitly include. A zero-import count is evidence, not a verdict.

The scripts that fetch DfE CSVs are marked historical and kept, pending
confirmation that nobody runs them by hand.

Checked: 190 backend tests, 429 frontend tests, `tsc --noEmit` clean.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016y2J6bs8gbuSJbH18w7Tan

backend/data_loader.py

@@ -188,16 +188,6 @@ def geocode_single_postcode(postcode: str) -> Optional[Tuple[float, float]]:
     return None
 
 
-def haversine_distance(lat1: float, lon1: float, lat2: float, lon2: float) -> float:
-    """Calculate great-circle distance between two points (miles)."""
-    from math import radians, cos, sin, asin, sqrt
-    lat1, lon1, lat2, lon2 = map(radians, [lat1, lon1, lat2, lon2])
-    dlat = lat2 - lat1
-    dlon = lon2 - lon1
-    a = sin(dlat / 2) ** 2 + cos(lat1) * cos(lat2) * sin(dlon / 2) ** 2
-    return 2 * asin(sqrt(a)) * 3956
-
-
 # =============================================================================
 # MAIN DATA LOAD — joins dim_school + dim_location + fact_performance
 # fact_performance is a merged KS2+KS4 table (one row per URN per year).