Police Use of Force: Understanding its Impact on Indigenous and Black Community Members in Ontario
Bibliographic record
Abstract
Police use of force is a critical area of concern, in Canada, North America, and globally. Issues around use of force have received considerable public attention in recent years due to several high-profile police-involved deaths of civilians, particularly racialized citizens. Using a mixed methods approach, this dissertation examines police use of force in Ontario and its impact on Indigenous and Black community members. An integrated framework of minority threat and social conflict theories, police working personality and symbolic interaction theories, and the concept of reputational risk is applied to help account for the findings. I argue that police use of force and its impact on certain communities is detrimental, multi-faceted, complex, and cannot be fully explained—in large part because of the lack of information made accessible on the subject. The qualitative section involves interviews with Indigenous and Black residents in Ontario to understand their perceptions of and experiences with police use of force. A primary finding is that many community members have been victims of police use of force—though, the types of force these members reported were overwhelmingly physical in nature (e.g., punching, kicking, knee-to-neck, roughhousing). Additionally, both Indigenous and Black individuals perceive that the police use force disproportionately against members from these groups compared to others. Moreover, the quantitative section provides an expansive analysis of police use of force over a 30-year period by examining use of force across all Ontario police services, lethal force incidents, and data from the Special Investigations Unit (SIU) to identify trends, patterns, and racial disparities in cases. Overall, the findings suggest that Indigenous and Black individuals in Ontario have been over-represented in use of force incidents consistently while other groups have been under-represented. The quantitative data also validate and support the perceptions and experiences shared by the Indigenous and Black community members. Despite the findings in this dissertation that highlight racial disparities in police use of force incidents, the limited information available on use of force by police services in Ontario underscores how much we do not know about this subject in the province. Future research and policy recommendations are provided.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".