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Record W2042522968 · doi:10.1080/17430437.2013.791156

Rugby World Cup 2011: sport mega-events and the contested terrain of space, bodies and commodities

2013· article· en· W2042522968 on OpenAlexaff
Steven J. Jackson, Jay Scherer

Bibliographic record

VenueSport in Society · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPoliticsTerrainGlobalizationMega-Space (punctuation)Sociology of sportRhetoricEvent (particle physics)SociologyPolitical scienceMedia studiesEconomyPolitical economySocial scienceGeographyEconomicsLawCartography

Abstract

fetched live from OpenAlex

This paper examines the contested terrain of sport mega-events and focuses on some recent examples from Rugby World Cup (RWC) 2011, hosted by New Zealand, a small nation of 4.3 million people. Overall, the analysis illustrates how one particular sporting event offers insights into the role of sport as part of a wider set of relations of globalization, politics, economics and cultural identity. This paper is divided into three main parts: (1) the social and cultural significance of sport mega-events as strategic sites of cultural analysis; (2) the politics and economics of the bid to host RWC 2011 and (3) the multidimensional nature of the contested terrain of RWC 2011 with respect to space, bodies and commodities. This paper concludes by contrasting the political rhetoric associated with sport mega-events with the lived realities and experience of citizens.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.013
Scholarly communication0.0080.003
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.018
GPT teacher head0.274
Teacher spread0.257 · 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

Citations30
Published2013
Admission routes1
Has abstractyes

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