Engendering Crime Prevention: International Developments and the Canadian Experience
Bibliographic record
Abstract
This article discusses the absence of gender in crime prevention in Canada and internationally. It outlines the development of parallel streams of work on violence against women and women's safety and argues that there is a need to integrate them into a concerted gendered approach, particularly at the level of municipalities. It draws on developing work on women's safety, gender, and the role of women in decision making in local government. The first part of the article is based on a review of international policy and practice on women's safety; it discusses recent trends and developments, as well as some of the problems and questions raised. These relate to the apparently separate worlds of expertise and activity that have grown up around violence against women and women's safety, the emergence of the concept of gender, and the isolation of these areas of work from mainstream crime prevention. The second part of the article evaluates Canadian performance in engendering crime prevention and makes some recommendations for embedding and sustaining engendered practice, particularly at the local level.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.039 | 0.024 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 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".