Canadian Human Trafficking: Assessing the Government's 2019 National Strategy for Enforcement, Prevention, and Supporting Survivors.
Bibliographic record
Abstract
In 2018, the Canadian Federal Government announced the National Strategy to Combat Human Trafficking 2019-2024. The implementation of this strategy would include an investment of $75 million over 6 years towards addressing the issue of human trafficking in Canada. Of those funds, $14.51 million were earmarked for the establishment of a national hotline which could refer survivors to services, while the rest would be used to fill service gaps and enhance existing programs. The goal of this paper is to examine what impact, if any, this policy and the implementation of the hotline has had or can be expected to have on the state of human trafficking in Canada. To that end, an original study was conducted interviewing 8 expertpractitioners working either in the fields of education and advocacy or as frontline service providers helping to support survivors. Having gathered the impressions of these expertpractitioners, this MRP aims to provide some evidence that could be used to shape future policy priorities, given the consistent dearth of federal data on human trafficking in Canada. The results of this research show that expert-practitioners in Canada largely agree on what priorities the government should pursue in attempting to address the issue and share skepticism about the importance of the funding increase and implementation of the national hotline. While some respondents felt more strongly than others, they almost universally criticized the national strategy for failing to take on a survivor-centred approach, or one that would work more broadly to redresses the vulnerabilities which support human trafficking. Their responses also revealed a pervasive lack of awareness regarding the hotline and a disconnect from the federal government and its efforts. Finally, the study concluded that a long-term solution to the problem of human trafficking will require Canadians to address the role of sex work in society.
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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 | 0.013 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.018 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".