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Record W3102137270 · doi:10.1080/23750472.2020.1846138

United as one: the 2026 FIFA Men’s World Cup hosting vision and the symbolic politics of legacy

2020· article· en· W3102137270 on OpenAlexaboutno aff
Adam Beissel, Geoffery Z. Kohe

Bibliographic record

VenueManaging Sport and Leisure · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsPolitical scienceLaw

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.831
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.294
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2020
Admission routes1
Has abstractyes

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