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Record W4402326345 · doi:10.7302/23781

Developing Human Rights Strategies for Large-Scale Sport Events: An Examination of the United Bid and Planning Phase of the 2026 FIFA World Cup

2024· article· en· W4402326345 on OpenAlexaboutno aff
Christine Maleske

Bibliographic record

VenueDeep Blue (University of Michigan) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsScale (ratio)Phase (matter)BusinessOperations researchGeographyEngineeringCartographyChemistry

Abstract

fetched live from OpenAlex

Human rights concerns associated with large-scale sport events have prompted event rights holders to integrate human rights considerations into their bidding and hosting requirements. For instance, bids for events sanctioned by the Fédération Internationale de Football Association (FIFA) (e.g., Men’s World Cup) must devise a human rights strategy that assesses existing and potential human rights risks and proposes measures to address them. However, a lack of comprehensive understanding of how prospective hosts and host cities develop these strategies remains. Therefore, this dissertation examines the formulation of human rights strategies during large-scale sport events’ bidding and planning phases. To achieve this, two separate qualitative case studies were conducted focusing on the bid and planning stages of the 2026 FIFA World Cup. The first paper focuses on the United Bid—a joint bid between Canada, Mexico, and the United States (US) awarded the 2026 FIFA World Cup in 2018. Utilizing strategy formulation and contingency theory, the paper examines factors that shape the development of human rights strategies among prospective hosts of large-scale sport events. Employing a qualitative instrumental case study with archival data and 12 semi-structured interviews, four themes were identified: initial member associations’ decisions, the learning curve, the experience of the bid committee, and stakeholder engagement. Findings identified challenges, including time constraints, the complexity of a multinational bid, and delayed guidelines that shaped the formulation of the human rights strategy. Some challenges stemmed from decisions made by member associations. Others arose from FIFA and the United Bid having to learn to demonstrate their commitment to human rights during the bid process, resulting in delayed guidelines and the conflation of terms that shaped strategy development. The paper underscores the United Bid’s efforts to address these challenges through the dedication and expertise of the bid committee’s staff, consultants, and leadership, along with stakeholder engagement. Despite these efforts, the expedited timeline and the bid’s overall strategy may have hindered city-level engagement. The second paper examines the early planning phase for the 2026 FIFA World Cup and focuses on four US host cities: Dallas, Houston, Los Angeles, and Miami. This paper examines how these host cities developed human rights objectives. Drawing on social event leverage and sensemaking research, a multiple qualitative instrumental case study was employed consisting of archival data and 12 additional semi-structured interviews. Within-case and cross-case analyses yielded three themes: coordination, stakeholder engagement, and complacency of existing capacities. The findings identified three types of coordinating entities and their roles in shaping human rights objectives in each city. Designating a leader within these entities and involving stakeholders in a structured manner could improve objective development. However, the absence of a coordinating entity and the timing of objective development may have hindered meaningful objective establishment in some cities. Additionally, some cities overemphasized existing capacities, potentially neglecting event-specific human rights risks and opportunities. Overall, this dissertation contributes to large-scale sport event and human rights research. The first paper examines the bid phase, highlighting interconnected factors shaping prospective hosts’ human rights strategies and approaches taken by bid committees to address challenges during strategy formulation. The second paper provides insights into the methods used by host cities to scan, interpret, and subsequently develop human rights objectives during the early planning phase. The dissertation advocates for future research involving longitudinal studies and a broader range of sport events.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.010
Scholarly communication0.0090.006
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.316
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

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