Body-Worn Camera Footage in the News: An Experimental Study of the Impact of Perspective and Framing on Viewer Perception
Bibliographic record
Abstract
The use of body-worn cameras (BWCs) by police organizations has increased rapidly in recent years. As a result, the use of BWC footage by mass media has also increased. While such video images can help viewers better understand complex police interventions, there are few studies of the extent to which BWC footage influences audience opinions and interpretations of police work. This article investigates the degree to which news reports of a police use-of-force event are influenced by two potential sources of cognitive bias: camera perspective and the way information about the event is framed. In a study using a three (cellphone, closed-circuit camera, and BWC perspective) by two (neutral and negative frame) experimental design, a total of 634 participants viewed and evaluated a news report of a police use-of-force event. Participant perceptions showed the influence of a BWC perspective bias, but no framing effect was found. Participants who watched the BWC footage were more likely to see the intervention as questionable or blameworthy and to believe that officers had no reasonable grounds for intervening. Results also suggest that the BWC perspective bias can be exacerbated or mitigated by the way information is presented in a news report.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".