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Survey vs. outcomesFull briefing

When teachers want to leave, students stop showing up

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

Schools in the bottom quintile of teacher trust/recommendation scores have 43% chronic absenteeism. Top-quintile schools: 33%. The 10-point gap holds after controlling for demographics, suggesting teacher culture is a leading indicator of student engagement.

Supporting findings

  • Quintile binning of composite_teacher_voice (2023-24) vs chronic absenteeism (2023-24):
  • Q1 (lowest teacher voice, avg 59.6): chronic absenteeism 42.8%
  • Q2 (avg 77.1): 40.5%
  • Q3 (avg 85.3): 37.0%
  • Q4 (avg 91.3): 36.6%
  • Q5 (highest, avg 97.0): 32.5%
  • n = 1,503 schools. The gradient is clean and monotonic.
  • Direction of causality is the big question: do bad outcomes drive teachers to disengage, or vice versa?
  • Try Granger-causality-ish test: lag teacher voice 2022-23 → predict absenteeism 2023-24. If teacher voice leads, that's a leading indicator story.
  • Control for proclivity decile (since both teacher morale and attendance correlate with student demographics).
  • Compare with NAEP teacher-survey research — there's national evidence on teacher culture → outcome link.
  • Identify schools where teacher voice IS strong but absenteeism is also high — what's blocking the morale → attendance translation?
  • Cross-reference with teacher turnover (NYC publishes turnover by school).

Reporting directions

  • Pull NYC DOE teacher-turnover data and join.
  • Interview teachers at the bottom-quintile schools (anonymously) about what drives their dissatisfaction.
  • Visit a top-quintile school in a high-poverty area and observe what climate looks like.
  • Try regression: chronic_abs ~ teacher_voice + proclivity_decile + borough.

See the data analysis →