Examining the impact of uniform manipulations on perceptions of police officers among Canadian university students
Bibliographic record
Abstract
It is important to understand how uniforms influence public perceptions of the police. The current study utilized a randomized design in which undergraduate students at a Canadian university were exposed to a series of photographs of officers wearing different uniform configurations (i.e., special duty vs. traditional uniform, dark vs. light shirt, dishevelled vs. tidy uniform, and uniform trousers with and without a stripe). Participants rated each officer on numerous scales including: (1) the officer’s personal qualities (e.g., helpfulness), (2) abilities or behaviors that the officer is likely to display (e.g., excessive force), and (3) the behavioral intentions of the participant toward the observed officer (e.g., willing to confide sensitive information to them). When controlling for general perceptions of police legitimacy, results suggest that, compared to the control conditions (i.e., normal operational uniform), introducing the uniform manipulations significantly influenced ratings on items related to community relations, professionalism, and officer safety. The current study speaks to the complicated relationship between the police appearing approachable and professional to the public, while also considering possible officer safety concerns associated with their uniform.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".