Who Watches the Watchmen: Evidence of the Effect of Body-Worn Cameras on New York City Policing
Bibliographic record
Abstract
Abstract We present a multi-year study of the rollout of Body-Worn Cameras (BWCs) to the New York City Police Department (NYPD). Our study adds to the prior body of work by clarifying some of the discord within it, particularly with respect to large urban police departments. We estimate the effect of BWC deployment on precinct volumes of citizen stops, arrests, complaints against officers, and use-of-force incidents. Results indicate that BWCs drive significant increases in stops and decreases in arrests and citizen complaints. We observe no effect on use of force. We also document heterogeneity in affected stops and complaints. Our findings speak to three potential benefits of BWCs in urban law enforcement: an increase in legitimate stops made by police; a decrease in complaints alleging officers’ abuse of authority; and a reduction in arrests (which appears beneficial, regardless of whether this results from improved behavior among police or citizens).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".