Police Shootings in Canada: An Empirical Analysis and Call for Data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We analyzed police shootings in Canada (except Québec) between 2017 and 2019. Drawing upon media reports and information provided by police oversight agencies, we attempted to identify all incidents where on-duty police officers discharged their firearm with the intent to strike a person. Findings indicated that such incidents occurred an average of 58 times per year. Approximately 39% of police shootings were fatal, 48% were non-fatal, and 12% were non-injurious. Most occurred in public spaces and were initiated by civilian requests for police service, typically for crime-related reasons. We discuss our findings with respect to both research and practice. We also call for official, incident-level data regarding police shootings to address concerns that otherwise exist about these incidents among civilians, practitioners, researchers, and policymakers.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it