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Punching above expectationFull briefing

Which Title I dollars actually moved the needle?

The longer form of the briefing for this story: the original thesis, the supporting findings the data team flagged, and the reporting directions a journalist could follow. For the short version and the data analysis, see the main story page.

Thesis

NYC distributes federal Title I funding to high-poverty schools. By cross-referencing per-pupil spending with proclivity-adjusted outcomes, we can identify which schools get Title I money AND outperform expectations — and which don't. Not a 'gotcha' on spending, but a how-effective-is-the-money piece.

Supporting findings

  • Need: NYC DOE Galaxy or School Allocation Memos (SAM) data on per-pupil spending — not in our DB yet.
  • Once joined, plot per-pupil spend × outcome residual (residual = actual - predicted-by-proclivity).
  • Identify the top-right quadrant: high spend + high residual = effective dollar.
  • Identify the bottom-right: high spend + negative residual = where money isn't moving.
  • Title I funding formulas favor concentration — schools with the most need get the most $.
  • Across schools matched on demographics, does an extra $1,000/student translate to measurable outcome lift?
  • Cross-reference with Renewal Schools (2014-2019) — billions spent, outcomes mixed.
  • Look at single-year vs multi-year funding stability — do schools that got steady $ outperform those with feast-or-famine?
  • Survey teachers at high-spend low-outcome schools — what isn't working?
  • Compare with Massachusetts' weighted student funding research (Berkeley + MIT papers).

Reporting directions

  • Ingest NYC DOE School Allocation Memo data (Galaxy budget extracts).
  • Build per-pupil-spend × residual scatter, highlight high-Title-I districts.
  • Interview Sean Reardon (Stanford) on best-practices for matched-funding analysis.
  • Compare with NYC's 'Fair Student Funding' policy effects.

See the data analysis →