United as one: the 2026 FIFA Men’s World Cup hosting vision and the symbolic politics of legacy
Bibliographic record
Abstract
Rationale/Purpose: In June 2018 FIFA awarded the 2026 Men's Football World Cup tournament to a transnational bid comprising the United States, Canada and Mexico. We explore this moment of historical conjuncture to understand the interplay of football, SME processes, geopolitical symbolism, and legacy craft.Design/Methodology/Approach: Drawing on a critical document analysis of bid material, media reports, economic analysis, and secondary evaluation, we analyse how the United As One bid's core legacy tenets of certainty, opportunity and unity produced a complex narrative of economic, sporting, and political harmony and prosperity.Findings: We contend that while the bid employs common legacy tropes and axioms, United As One exposes the sustained fallacies implicit within bid constructions and paucity of legacy as a currency in the future of SME enterprise.Practical Implications: Stakeholder alliances are fundamental to sport mega-event bidding. Yet, collaborations are politically complex as each party balances benefits and risks. Accordingly, this paper forewarns all bid actors to be cogniscent of the roles they may play within the symbolism and rhetoric of bid construction.Research Contribution: Beyond the context of football, this paper adds new insights to ways sport megaevent bid visions fuse economic, socio-cultural, and public health advancement rhetoric to consolidate and masque persuasive host and legacy agendas.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".