Examining the development of human rights strategies for large-scale sport events: the case of the United Bid for the FIFA Men’s World Cup 2026
Bibliographic record
Abstract
Research question Criticism of human rights issues associated with large-scale sport events has led event rights holders to incorporate human rights into bidding and hosting requirements. Bids for FIFA World Cups (men’s and women’s) now require the inclusion of a human rights strategy. Given that these requirements are relatively new, there is limited understanding of how these strategies are developed. This study drew on strategy formulation and contingency theory to examine human rights strategy development of the United Bid – a joint bid between Canada, Mexico, and the United States for the 2026 FIFA Men’s World Cup.Research methods A qualitative instrumental case study was employed using archival data and 12 semi-structured interviews with United Bid members and key stakeholders. Data were analyzed using qualitative content analysis, resulting in three themes.Results and findings Findings highlight the critical roles of stakeholder engagement and individuals with event experience in developing human rights strategies. The novelty of FIFA’s human rights requirements and late delivery of the bid guidelines presented significant challenges for the bid committee.Implications This research advances contingency theory by suggesting the approach to the development of human rights strategies is dependent on prospective hosts’ overall bid strategy. In this case, the bid focused on human rights at the country level and deferred assessment of human rights at the host city level until after the bid was won. This insight can guide prospective host nations in accounting for and integrating human rights into their bids.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".