Implementation of body worn cameras:Rapid review of current research and practice
Bibliographic record
Abstract
This report provides a review of recent research and literature on the implementation and use of body worn cameras (BWCs) to address the issues of occupational violence (OV) and workplace health and safety (WHS) among frontline emergency service workers in Australia, Canada, the United Kingdom, and the United States of America. The extensive review of the literature and current research found that while there has been much written about the role out and implementation of BWCs in policing, there has been significantly less focus on paramedics or ambulance services. Research and evaluations that have been undertaken in policing or ambulance services have tended to be internal reviews, with very few independent, external studies, and even fewer peer review processes. Studies in policing have focussed on a broad range of factors including Integrity and community trust, complaints handling, use of force/violence by police officers, crime levels, evidence for criminal trials and streamlining procedural justice. However there has been limited focus on the impact of BWC on OV towards officers or WHS including physical, mental, and emotional wellbeing.
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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 | 0.027 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".