Sexualized Nationalism and Federal Human Trafficking Consultations: Shifting Discourses on Sex Trafficking in Canada
Bibliographic record
Abstract
Canada has engaged in a range of efforts to stop human trafficking within and across it borders. Federal and provincial governments have spent considerable funds in this regard, and have studied the issue to come up with perceived solutions. In this article, we explore Canada’s two national House of Commons standing committee consultations on trafficking, in 2006 and 2018. Using critical discourse analysis to examine the consultation transcripts and written briefs, we identified several significant shifts in both the language used and the areas of focus advanced by witnesses, in particular: the modified emphasis from international to domestic trafficking; the changing nature of vulnerability and victimhood; and an increased focus on youth sexual exploitation. We propose that what is being expressed is an iteration of Canadian sexualized nationalism and national sexual morality. These results have policy implications, especially with respect to promoting just, peaceful, and inclusive societies at a time when there are mounting pressures to restrict migration that often dovetail with concerns over human trafficking. Indeed, the way concerns over trafficking are expressed in Canada appears as a fear over women’s sexual agency and vulnerability as well as a need protect “our” boundaries from incursion, whether territorial or moral.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.071 | 0.035 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.007 |
| 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".