Match Quality, Worker Productivity, and Worker Mobility: Direct Evidence from Teachers
Bibliographic record
Abstract
I investigate the importance of the match between teachers and schools for student achievement. I show that teacher effectiveness increases after a move to a different school, and I estimate teacher-school match effects using a mixedeffects estimator. Match quality can "explain away " a quarter of, and is as economically important as, teacher quality. Match quality is negatively correlated with turnover, and increases with experience. This paper provides the first estimates of worker-firm match quality using output data as opposed to inferring productivity from wages or employment durations. Because teacher wages are essentially unrelated to productivity, this is the compelling evidence that workers may seek high quality matches for reasons other than higher pay. The productive quality of the match between a worker and the firm plays a central role in canonical models of worker mobility (Jovanovic 1979, Mincer and Jovanovic 1981, Neal 1999, Burdett 1978, Mortensen 1998, Johnson 1978). One of the key roles of the labor market is to allocate workers to firms in the most efficient manner. The hypothesized mechanism through which this efficient allocation emerges is through workers either leaving jobs where the productivity match between the worker and the firm is low or seeking jobs where match quality is high, or both. Match quality is also used to explain the stylized facts that changing jobs is associated with rapid earnings growth (Bartel and Borjas 1981, Altonji and Shakotko 1987,
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".