← Back to story

Subgroup gapsMethodology recipe

Asian-American achievement in NYC schools is more variable than the stereotype suggests

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

Computed the variance of the ASIAN-subgroup math/ELA proficiency across all schools where it's reported, comparing with the variance of WHITE-subgroup proficiency at the same schools. Surfaced the spread.

Data sources

  • 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 ASIAN-subgroup math_all_proficiency for 2024-25; compute distribution.

  2. Compare with WHITE-subgroup and citywide ALL-subgroup distributions.

Caveats

The ASIAN subgroup aggregates students from very different national-origin populations (East Asian, South Asian, Southeast Asian) whose outcomes diverge in ways the school-level data can't resolve.

References

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.