“It Stays with You for Life”: The Everyday Nature and Impact of Police Violence in Toronto’s Inner-City
Bibliographic record
Abstract
In recent years, police violence has amassed notable international attention from the public, practitioners, and academics alike. This paper explores experiences and perceptions of police violence in Canada, documenting the impacts of direct and vicarious experiences of police violence on inner-city residents. The study employed semi-structured interviews with 45 community members across three Toronto inner-city neighbourhoods. Using a general interview prompt guide, participants were asked a range of questions about their experiences with and perceptions of police, and particularly, of police violence in their community. The interviews were audio recorded, transcribed, thematically coded, and analyzed. All participants reported direct and/or vicarious experiences of police violence, and most described experiencing long-standing, and continual fear that police contact would result in harm to them. Further, participants described a variety of serious and negative outcomes associated with experiencing and/or witnessing police violence. Police violence in Canada is a public health issue that requires an integrated public health policy approach to address the negative outcomes associated with direct and vicarious police violence exposure.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".