From Cuffs to Compassion: The Impact of Relational Policing De-escalation Approaches on Public Perceptions of Safety, Satisfaction, Procedural Justice, and Police Legitimacy.
Bibliographic record
Abstract
Academics, policy makers, and the public have called for the prioritization of de- escalation training and use in public-police interactions to reduce police use of force (PUoF) (e.g., Dubé, 2016; Iacobucci, 2014; Todak, 2017; Wortley et al., 2021). In response to various calls to action, the Ministry of the Solicitor General launched the Ontario Public-Police Interactions Training Aid Framework in 2023, which emphasizes the importance of utilizing a relational policing approach in public-police interactions (see Lavoie et al., 2022). However, despite changes in police training frameworks, relatively little is known about PUoF in Canada (Wortley et al., 2021), with similarly minimal research evaluating public perceptions of police de-escalation (Todak & White, 2019). This experimental study therefore focused on examining public perceptions of police following the observation of a brief, animated, ambiguous public- police interaction involving elevated risks to public safety. This study consisted of a 2x2 factorial design (suspect threat: weapon present, weapon absent; policing approach: relational, standard authoritative) to evaluate whether the type of police approach, namely a relational or standard authoritative approach, given variations in the presence of safety risks, shaped participants’ perceptions of safety, police legitimacy, procedural justice, and satisfaction in public-police interactions. The sample consisted of 217 participants, who completed a 42-question survey related to the dependent measures and participant demographic information. Results indicated that participants perceived relational policing to be a more safe, legitimate, procedurally just, and satisfactory policing approach, compared to a standard authoritative approach in an ambiguous public-police interaction with elevated risks to public safety. These findings present optimistic opportunities to enhance public perceptions of the police and foster more positive public-police interactions in the future, using relational policing approaches.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".