Rights, not rescue: trafficking (in)securities at the sport mega-event
Bibliographic record
Abstract
We examine the impact of fantasies used in the redevelopment of sport mega-event cities on host communities; particularly as related to the male-dominated FIFA World Cup and forced prostitution. We start with a discussion of event fantasies, particularly those that circulate in relation to humanitarian aid and the alleged involvement of women and children in forced labour and sexual exploitation. We trace these fantasies across several FIFA host cities since the 2006 FIFA World Cup, hosted in Germany, to leverage continual and perpetuate attention (and profit) through the non-profit industrial complex. These fantasies have facilitated and coordinated collaborative consensus amongst state authorities and allies to act in a meaningful manner even as the evidence of forced prostitution is still scant-while the realities of people that continue to be subjected to violent and exploitative labour in the construction of stadia, athlete recruitment, or equipment and apparel industries are seldom addressed. We do this to question the lived impact of policies and personalities of rescue on people engaged, consensually, in erotic labour within host cities, that are often made target of rescue intervention. The figure of the proverbial sex slave, as a highly racialized and hypersexualized trope, is mobilized through the sport mega-event to further police the bodies of all women in labour and migration. We end with a cautious message to future host cities, particularly cities implicated in the 2026 FIFA World Cup within Mexico, Canada, and the United States, of the highly-profitable and politically-advantageous rhetoric of damsel in distress.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".