'My Wife Has Endured a Torrent of Abuse': Gender, Safety, and Anti-Squeegee Discourses in Toronto, 1998-2000
Bibliographic record
Abstract
This paper explores the intersections between gender, safety and fear of crime as these were played out in public debates about squeegee kids in Toronto, 1998-2000. The role played by women and, even more tellingly, by gendered conceptions of urban space, safety and mobility have yet to receive detailed attention in analyses of the Toronto squeegee kid “crisis” and the ensuing Ontario Safe Streets Act 1999. Drawing on Toronto newspaper articles and letters to the editor, along with legislative debates, this paper argues that women’s concerns for safety, and concerns for women’s safety were appropriated to legitimate a right-wing law and order response to visible poverty in urban spaces. In so doing, these debates facilitated the emergence of a protective masculinity that was inscribed onto the neo-liberal security state.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.034 | 0.029 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| 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 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".