The 2020 EventRights Mobility Project: investigating Atlanta’s compliance with FIFA’s human rights bidding requirement in planning and designing security and safety measures for the 2026 FIFA Men’s World Cup
Bibliographic record
Abstract
The United States, Canada, and Mexico will co-host the 2026 FIFA Men’s World Cup, marking the first trio-nation hosting since Japan-Korea 2002. Unlike previous tournaments, this event occurs amid FIFA’ s structural reforms and heightened scrutiny of human rights issues, following controversial awards to Russia and Qatar. Despite FIFA’s renewed commitment to ensure compliance with human rights and international best practices in bidding and hosting, questions remain over host nation’s compliance and applimentation. Therefore, as part of the 2020 EventRights Mobility Project funded by the Maria Sklodowska-Curie Foundation under the EU Horizon 2020 Research Programme, this research investigates human rights policy efforts in one of the host cities, Atlanta, USA. Specifically, the research examines how human rights are considered in the planning and designing of security and safety measures ahead of the World Cup. The two-month research fieldwork involved observation of the World Cup venues, interviews with policymakers, academics in Sports Management, and security personnel. Findings show that Atlanta has comprehensive policy strategies that align with FIFA’s human rights requirements, supported by a robust administrative framework. The city demonstrates a strong commitment to safeguarding fans and local communities, indicating the potential for effective integration of human rights into mega-sporting event secuirty planning.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".