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Record W3208290531 · doi:10.1093/jleo/ewab026

Who Watches the Watchmen: Evidence of the Effect of Body-Worn Cameras on New York City Policing

2021· article· en· W3208290531 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Law Economics and Organization · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsPrecinctPolice departmentLaw enforcementPsychologyCriminologyEnforcementWork (physics)Political scienceLawEngineering

Abstract

fetched live from OpenAlex

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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.310
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it