Pandemic policing: how policing changed during the COVID-19 pandemic
Bibliographic record
Abstract
Purpose Police were key to enforcing and managing COVID-19 emergency orders, but many police services were not prepared for such an emergency. In Ontario, Canada, each service was responsible for crafting its own procedures for responding to the pandemic. This study synthesizes changes documented by Ontario-based services. Design/methodology/approach We conducted a qualitative thematic analysis of COVID-19-related documents (e.g. emails, guides and recommendations, orders, directives, policies and procedures, questionnaires and checklists and strategic plans) produced by 14 municipal police services across Ontario, Canada. Findings The documents reveal ways that police services were affected by the pandemic. These changes are organized into four themes: intra-organizational changes, officer wellness, inter-agency coordination and collaboration and community-police relations. Originality/value The study works with data from multiple police services to document the range of ways that policing changed to adapt to the pandemic. Understanding how police services navigated the pandemic facilitates preparedness for future civil emergencies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".