Divergence and Convergence on Police Transparency: Comparing Officers’ and Citizens’ Preferences on Body-Worn Camera Footage Release
Bibliographic record
Abstract
The adoption of body-worn cameras (BWCs) by law enforcement agencies is commonly viewed as a means of enhancing police transparency, holding officers accountable, and building trust with the communities they serve. The effectiveness of BWCs in promoting police transparency, however, is still debatable, with many jurisdictions still lacking clear BWC footage disclosure policies. Following a mixed-method design, this article investigates the perspectives of officers and citizens on police transparency and, more specifically, the divergences and convergences in their expectations regarding BWC footage release. The data were collected from 78 police officers (through interviews and focus groups) and 1,609 citizens from the province of Quebec (through phone surveys). The two groups share the belief that the public release of BWC footage is significant in promoting police transparency. Yet they hold differing views on its use to reach accurate assessments of police interventions. While citizens expressed worries about the integrity of BWC footage, officers appeared more concerned about the potential misunderstanding of events following the release of BWC footage. The variations in expectations between officers and the public highlight the multifaceted nature of police transparency, which should serve to inform future BWC footage disclosure policies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".