Ethical Procurement In The 2026 FIFA Men's World Cup: Toronto's Efforts In Combating Sweatshop Labour
Bibliographic record
Abstract
The anti-sweatshop movement has long committed to abolishing sweatshop labour and ensuring workers’ rights for all. There is an established body of literature on sport and the anti-sweatshop movement on the roles played by a range of actors concerning the mega-sporting events, which have been plagued with abuses of workers’ lives in the name of the sport spectacle. In effort to move past this troubled history, FIFA has embedded internationally recognized human and labour rights into their 2026 bid process. This study evaluates how the City of Toronto, Canada Soccer Association, and FIFA have considered ethical procurement and sweatshop labour as part of their bid for co-hosting the 2026 FIFA Men’s World Cup. Employing a critical theoretical approach, this study finds that despite the varying levels of considerations given to ethical (anti-sweatshop) procurement, the efforts remain insufficient. This is attributed to the unequal power dynamics that prioritize a discourse of (neoliberal capitalist) development for soft power.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.027 | 0.025 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".