En jämförande analys av prostitutionspolitik och omfattningen av människohandel i sexuella ändamål i Sverige, Kanada, Tyskland och Nederländerna
Bibliographic record
Abstract
This comparative study examines the relationship between prostitution policies and human trafficking for sexual purposes in Sweden, Canada, Germany, and the Netherlands. By analyzing statistics and applying rational choice theory and deterrence theory, the study investigates whether different laws have measurable effects on reported human trafficking cases. The findings show no clear connection between the chosen policy model and trafficking levels. Countries using the Nordic model have seen increases in reported cases despite making it illegal to buy sex, while countries with legalized or decriminalized prostitution showdifferent patterns, with Germany showing consistent decreases and the Netherlands showing more complex trends. These results suggest that the design of laws alone is not enough to explain differences in human trafficking. The theoretical frameworks of rational choice and deterrence theory are useful but have limitations, as they don't capture the full complexity of institutional structures, cultural factors, and challenges in measuring statistics. The study concludes that fighting human trafficking requires evidence-based approaches that consider how laws are implemented, institutional capacity, and contextual factors rather than ideologically driven policy choices. A key insight is that official crime statistics must be interpreted carefully, as reported cases reflect law enforcement capacity, resources, priorities, and reporting practices rather than the actual extent of trafficking. The study shows that the quality of implementation and institutional resources are at least as important as the formal legal frameworks. Effective anti-traffickingefforts require coordinated interventions across multiple agencies and adequate resources for investigation,victim protection, and prevention.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".