The protection of whose communities? : A comparative municipal case study of sex work bylaws & their enforcement in the wake of Bill C-36
Bibliographic record
Abstract
This Major Research Project (MRP) concerns the enforcement of licensed indoor sex work bylaws in Canada through a comparative analysis of two municipalities: Toronto, ON and Vancouver, BC. My MRP asserts that, in spite of the continued criminalization of many aspects of sex work at the federal level in light of the passing of Bill C-36, The Protection of Communities and Exploited Persons Act, in 2014, some municipalities in Canada have continued to condone sex work through their bylaws and enforcement mechanisms. My research finds that while there are similarities between the bylaws themselves in these two jurisdictions, the primary difference between the two cases is as a result of enforcement practices. I assert that Vancouver’s adoption of GBA+ and intersectional-informed femocratic administrative tools at the municipal governmental level is one of the primary drivers leading to the outcome of some licensed indoor sex workers in Vancouver being able to work with greater respect and less harassment than licensed indoor sex workers in Toronto. However, while aspects of Vancouver’s approach demonstrate some positive developments that correlate to benefits for some of its city’s sex workers, the findings of my MRP reveal that Canada’s two largest Anglophone cities both have a lot of work to do to better support and protect some of their most vulnerable workers.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.036 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".