Unpacking the Power of Legal Definition: Changing the Legal Narrative Around Sex Trafficking and Sex Work in Canada
Bibliographic record
Abstract
Human Trafficking is a growing crime worldwide, 71% of which is dominated by the crime of sex trafficking. With recent Canadian legal cases such as Canada (Attorney General) v Bedford, there is growing debate about sex trafficking and sex work. This paper will discuss legal and societal prejudice against sex trafficking and sex work in Canada using prior research and will discuss current statistics surrounding sex trafficking, human trafficking prosecutions, and police responses to sex trafficking and sex work. Using a sociolegal lens, this article will discuss how society’s wide-ranging perceptions of sex work have influenced the law in recent decades, and how the law has come to shape society’s current legal and moral prejudice against sex trafficking and sex work. Further, this paper will discuss how these perceptions have helped or hindered the work of law enforcement, crown attorneys and judges and will discuss how the law is not evolving at the same pace as the crime of human trafficking.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.067 | 0.035 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".