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Record W4408237723 · doi:10.1051/sm/2024038

Olympic bidding and social license: a micro analysis of a public debate

2025· article· en· W4408237723 on OpenAlexaffabout
Harry H. Hiller

Bibliographic record

VenueMovement & Sport Sciences - Science & Motricité · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLicenseBiddingBusinessPublic administrationPolitical scienceMarketingLaw

Abstract

fetched live from OpenAlex

Social license or public approval is often a major issue in the bid phase of the Olympic cycle and is typically sought through a referendum. Instead of the macro factors usually utilized to explain referendum outcomes, this paper adds to the literature by taking a micro approach that focuses on how local residents encounter the prospect of hosting the Games. Building from the work of economists who have examined the role of announcements about bidding as “news shocks” and “sentiment shocks” in a potential host community, this paper takes a more sociological approach by showing how bidding stimulates interaction and debate at the grassroots and utilizes extensive empirical research from two Winter Olympic cities, Calgary, and Vancouver. Local residents encounter the intrusive nature of an Olympic bid that is filled with prospective unknowns and that exists as a political policy option. Bidding stimulates and provokes conflict and debate through face-to-face verbal and non-verbal communication around six major themes, and the competing narratives that develop around costs, the IOC industry, and local priorities. It will be shown how local citizens struggle to determine their own responses to Olympic initiatives in interaction with others which contributes to the volatility of referendum outcomes.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics, Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.022
Science and technology studies0.0030.005
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.042
GPT teacher head0.350
Teacher spread0.308 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations2
Published2025
Admission routes2
Has abstractyes

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