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Record W3092586984 · doi:10.1080/23750472.2020.1829989

All for one and one for all? Integration in high-performance sport

2020· article· en· W3092586984 on OpenAlexaff
Nancy Quinn, Laura Misener, P. David Howe

Bibliographic record

VenueManaging Sport and Leisure · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsWestern University
Fundersnot available
KeywordsThematic analysisForegroundingPerspective (graphical)EliteAthletesPsychologyCommonwealthEthnographyQualitative researchPerceptionPublic relationsApplied psychologySociologySocial psychologyPolitical scienceSocial sciencePoliticsComputer science

Abstract

fetched live from OpenAlex

Purpose : To examine the lived experiences of the integrated model of elite sport from the perspective of parasport insiders.Research design : Since 2002, an integrated model for competition has been implemented by Commonwealth Games Federation (CGF). Commonwealth Games XXI was selected as a relevant location to conduct research regarding integration. Ethnographic methods included interviews, go-along conversations and observation. Interviews were conducted with Games personnel to enhance understandings of integration in sport. Qualitative thematic analysis was conducted to determine significant themes.Findings : The findings confirmed that integration is considered the preferred model among non-athletes who were unanimous in their support. Analysis indicated that the parasport athlete experience was mixed, reflecting negative and positive experiences. Three themes were identified as impactful of the athlete experience: ableization, size of the parasport contingent, lack of unified collective voice.Practical implications : Future research that examines whose assumptions inform decision making and program delivery is necessary to determine the merits and drawbacks of integration in sport.Research contributions : By foregrounding the lived experiences of a group of parasport insiders, the research generates unique insights into the integrated model of sport from a perspective that is often missing, and credibly informs those who manage integration in sport.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.048
GPT teacher head0.294
Teacher spread0.247 · 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 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

Citations12
Published2020
Admission routes1
Has abstractyes

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