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What if the players controlled the game? Dealing with the consequences of the crisis of governance in sports

2015· article· en· W793772158 on OpenAlexaff
Peter Donnelly

Bibliographic record

VenueEuropean Journal for Sport and Society · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Toronto
FundersInternational Olympic Committee
KeywordsHegemonyCorporate governanceGlobalizationPolitical scienceResistance (ecology)Political economyMeaning (existential)SociologySubject (documents)DemocracyPublic relationsLawPoliticsEpistemologyEconomicsManagement

Abstract

fetched live from OpenAlex

“It is difficult to find anything else in the world quite so badly governed as international sport” (Katwala, 2000). Little has improved since Katwala’s comment, and governance problems are now evident in national sport organisations, professional sports, and educational sport. These problems are related to the effects of globalisation, institutionalisation, and commercialisation on sport; processes and forces that have acted to produce a cultural hegemony – a global sport monoculture in which the democratic involvement of participants is restricted, and which limits what Roland Renson refers to as ludodiversity. When states do not consider sport seriously as a subject of concern for policy and regulation, “Sports … take place in a sort of separate [autonomous] sphere, detached from normal rules and regulations in society” (Bruyninckx, 2011). My work has an ongoing concern with the effects of cultural hegemony on various forms of physical culture, and with examples of resistance to that hegemony. In an attempt to resolve the crisis of governance in sport, I will follow the trajectories of various alternative and grassroots sports in order to speculate what sports would look like if they were truly democratised; in other words, if their form and meaning were controlled by the participants.

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)0.006
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.031
GPT teacher head0.287
Teacher spread0.256 · 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 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

Citations27
Published2015
Admission routes1
Has abstractyes

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