Flawed research on the impact of law reform: The case of legal prostitution and sex trafficking, a research note
Bibliographic record
Abstract
Abstract This research note examines a finding that contradicts previously well‐established knowledge in the field of organized crime, as well as studies of the effects of legalizing vice. Unlike research on the aftermath of Prohibition in the United States post‐1933, decriminalization of casino gambling in Nevada post‐1931, and legalization of cannabis, little is known about the effects of legalizing prostitution. Here, I offer a critique of some influential research that purports to find a relationship between legalization of prostitution and an increased magnitude of sex trafficking. After identifying serious flaws in these studies’ conception and execution, I briefly show that their problematic findings have become the conventional wisdom regarding the relationship between trafficking and legalized prostitution—as reflected in news reports, legislative debates, Google's topline assessment, and the outcome of a constitutional challenge to Canada's current prostitution law.
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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 | 0.046 | 0.096 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.010 | 0.054 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.011 | 0.014 |
| 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".