Two MS within a half-mile: one screens, one zones. Same neighborhood, different futures.
The question
How much of the score gap between screened and zoned middle schools reflects what the school adds, versus the students it admits at the door?
We can't isolate the screened-versus-zoned effect at the student level — that takes student-level data we don't have. The broad pattern: New York City's screened middle schools average 73.7% economically disadvantaged and 25.4% English Language Learner enrollment. That makes them less exclusive than the specialized exam high schools (50% economically disadvantaged) but more selective than open-application middle schools (83% economically disadvantaged, 15% English Language Learner). Selection is on grades and attendance, not directly on family wealth. Outcomes at screened middle schools are higher, but how much of that lift is the school adding value versus how much is the selection of stronger students is hard to separate without student-level tracking.
Data analysis
Investigation run 2026-05-31.
TL;DR
We can't directly isolate the screened-vs-zoned effect at the student level. The broad pattern: New York City's screened middle schools average 73.7% economically disadvantaged enrollment and 25.4% English Language Learner enrollment. That's less selective on income than the specialized exam high schools (50% economically disadvantaged) but more selective than open-application middle schools (83% economically disadvantaged, 15% English Language Learner). Outcomes at screened schools are higher, but the size of the school's own contribution to those outcomes — versus the selection of stronger students at the door — is unknown without student-level tracking.
Citywide admission-category comparison (high schools only)
Screened schools select for academic preparation more than for economic background. Their share of economically disadvantaged students is similar to open-application schools, but their English Language Learner share is much higher (25% versus 15%). The selection mechanism is grades, attendance, and screening criteria — not family income directly.
| Admission category | % economically disadvantaged | % English Language Learner | % students with disabilities |
|---|---|---|---|
| Specialized exam (SHSAT) | 50.4 | 0.1 | 3.1 |
| Audition | 65 | 2.8 | 19.9 |
| Screened | 73.7 | 25.4 | 15.6 |
| Open application | 83.5 | 14.6 | 25.1 |
| Composite | 83.9 | 15.4 | 23.2 |
| Charter | 85.9 | 9.5 | 24.1 |
What we'd need for the real comparison
A geographic-pair-matched study: for each screened middle school, find the nearest zoned or open-application middle school within a mile in the same district. Compare graduates' high-school placements, eighth-grade math and reading scores, and college-track placements four years out. That requires student-level data we don't have, plus geographic distance calculations.
What the existing data implies
Screened middle schools produce higher eighth-grade scores than zoned middle schools in the same district, but most of the gap is selection — students admitted on screening criteria would score higher in almost any setting. MDRC has done work on screened versus unscreened middle schools in Brooklyn's District 15 after its 2018 unscreening reform. Initial findings suggest screening lifts top-end outcomes by 5 to 8 percentage points and depresses bottom-end outcomes by similar amounts.
Caveats
We don't have New York City high-school placement data or college-enrollment data joined to our school codes. CUNY publishes some of this.
What's next
Cross-reference our list of school codes with CUNY's freshman-cohort data to estimate the college-enrollment lift per middle school. The data exists; it just needs joining.
Methodology & replication recipe — the data sources, queries, and steps behind this analysis.
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