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Borough & districtMethodology recipe

Where NYC's enrollment decline is hitting hardest — and where it isn't

A reproducibility log: the data this analysis touched, the queries it ran, the outside sources it leaned on, and the steps a third party would follow to re-run it.

Summary

Per-school enrollment trajectory 2018-19 → 2024-25 (using latest_enrollment + historical snapshots in school_year_metrics where available). Computed average per-borough decline.

Data sources

  • Database tableschools

    One row per New York City public school (DBN, name, district, borough, school_type, grade_band, latest_enrollment, proclivity_decile, proclivity_score, closed_at, admission_category).

  • Database tableschool_year_metrics

    Long-format per-school per-year metric facts (school_dbn, year, metric_key, subgroup, value, suppressed). Loaded from DOE/NYSED public files via scripts/loaders/*.

Steps

  1. Per-school enrollment year-over-year; aggregate to borough and district; rank by decline.

Caveats

Enrollment shifts reflect both population change and family choice (out-migration, private/charter shifts). Our data shows the trajectory; the why is for reporting.

Reproduce

Clone the repo, set DATABASE_URL to a Postgres with the project schema loaded, run `npx tsx scripts/loaders/<source>.ts` for any not-yet-loaded data, then issue the queries in the Steps section. The story page also lists the exact `metric_key`/`subgroup`/`year` filters used. Searchable by the answer's headline number — every figure is recomputable from the queries shown.

The recipe lives at data/stories/recipes.ts in the repo. Corrections welcome.