The criminalization of sexual commerce in Canada: Context and concepts for critical analysis
Bibliographic record
Abstract
Discussions of the rights and wrongs of sex for pay often occur in abstraction from the contexts in which they occur. Given the federal government's emphasis that its new legislation, The Protection of Communities and Exploitation of Persons Act, is a “made-in-Canada” solution to the problem of prostitution, the author examines Canadian legal, academic, activist, and mass media documents to explore made-in-Canada dimensions of the issues. A notable feature of the Canadian context is the long and ongoing history of policing of those perceived as prostitutes and their associates, as guilty of status offences. Social profiling and vulnerability to violence and exploitation in Canada also reflect the particular intersections of race, gender, class and nation in producing Canadian forms of sexual and other exploitations. Consideration of the implications for agency and passive subjugation in the terminology used to name the problem reveals ambiguities in the meaning of exploitation that reproduce a version of the status offence as well as environmental, waged labour and settler colonial forms of exploitation and injustice. Reference to indigenous, feminist, Kantian, and Marxist analyses of objectification and exploitation helps to reveal how this is occurs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.049 | 0.081 |
| Scholarly communication | 0.022 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| 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".