K-8 schools weathered COVID better than separate ES + MS — why?
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
Compared change-in-outcomes 2018-19 → 2024-25 between K-8 schools (single building, no transition) and separate ES + MS schools, looking at math, ELA, and absenteeism.
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
Split schools by grade_band ('K8' vs 'ES' + 'MS' separately).
For each cohort, average per-school 2018→2024 deltas on key metrics.
Caveats
K-8 schools differ from ES/MS in selection (often more screened) and population. The trajectory advantage may reflect those upstream differences, not a structural K-8 effect.
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.