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Record W1920253737 · doi:10.1080/17430437.2013.838352

Introduction

2013· article· en· W1920253737 on OpenAlexaboutno aff
Katie Liston, Paddy Dolan

Bibliographic record

VenueSport in Society · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupNationalismGender studiesRace (biology)DisciplineSociologyPolitical scienceMedia studiesLawPolitics

Abstract

fetched live from OpenAlex

It appears that rarely before has there been a more opportune time to consider the full extent of the interplay of race, ethnicity and sport in the modern world. Such issues associated with sport and ethnic/nationalist rapprochement since the end of the Sri Lankan Civil War, ethnic/nationalist conflict in Tibet in the lead-up to the Beijing Games, the IOC’s apparent impotency over human rights and the question of Pacific Islanders having their own team at the 2011 Rugby World Cup foreground questions of ethnic identity and the critical role of sport in this regard. And if the proliferation of books, conference papers and peer-reviewed articles on sport, race and ethnicity is taken as a reasonable proxy, then we can safely say that there has also been a concomitant sea change in the academy’s view of, and approach to, the interplay between sport, race and ethnicity. This special issue reports from the fourth international conference on sport, race and ethnicity that was held at the Belfast campus of the University of Ulster, Northern Ireland, in June 2012. Readers will find here a stimulating array of papers that capture varied aspects of the sport, race and ethnicity nexus around the world. The journey takes us as far afield as Australia, New Zealand, Canada, Ghana and the USA and, in so doing, we draw on a range of disciplinary approaches that converge or diverge by degrees. Such diversity is to be welcomed in an academic field characterized less by uniformity and more by the potential richness of people’s experiences of sport, race and ethnicity within various cultural contexts. Included here are papers from a range of disciplines and approaches including sociology, politics, sports feminisms, critical race theory, a strengths perspective, Kaupapa Ma ori Theory, history and sports development.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.287
Teacher spread0.273 · 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.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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