The Expansion of Conducted Energy Weapon Use in Ontario: Pacification and Policy Development
Bibliographic record
Abstract
This thesis examines the Ontario government's decision to allow for the expansion of Conducted Energy Weapons (CEWs) to all front-line police officers.I utilize a framework of pacification strategies that illustrate the way in which police services, particularly the Ottawa Police Service, should implement a CEW policy for the deployment of the weapon in order to achieve effective police-community partnerships.The decision to expand CEWs demonstrates an abdication of responsibility on the part of the province to local police agencies and the new policy provides little guidance.It is important that local agencies develop strong and effective CEW policies for the purpose of enhancing public and police safety as well as ensuring meaningful accountability in Ontario.I analyze several provincial and agency CEW guidelines in order to facilitate the development of effective CEW guidelines at the agency level and, importantly, to ensure accountability for when these weapons are deployed.v Chapter 5: Conclusion 109 5.1.Implications…………………………………………...……………………………109 5.2.Recommendations for Ontario………………………...…………………………...110 5.3.Recommendations for the Ottawa Police Service…………………………………111 5.4.Limitations to Research……………………………………………...…………….1135.5.Future Research……………………………………………………...…………….
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".