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Record W3204031247 · doi:10.1123/tsp.2020-0146

Organizational Systems in British Sport and Their Impact on Athlete Development and Mental Health

2021· article· en· W3204031247 on OpenAlexaff
Zoë A. Poucher, Katherine A. Tamminen, Christopher R. D. Wagstaff

Bibliographic record

VenueThe Sport Psychologist · 2021
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAthletesThematic analysisPsychologyMental healthApplied psychologySport psychologyPerceptionPublic relationsSport managementPolitical scienceQualitative researchMedicineSociologyPhysical therapy

Abstract

fetched live from OpenAlex

Sport organizations have been noted as pivotal to the success or failure of athletes, and sport environments can impact the well-being and development of athletes. In this study, the authors explored stakeholders’ perceptions of how high-performance sport organizations support athlete development. Semistructured interviews were conducted with 18 stakeholders from the United Kingdom’s high-performance sport system and transcripts were analyzed using a semantic thematic analysis. Participants emphasized the importance of performance lifestyle advisors, sport psychologists, and financial assistance for promoting athlete development. Several stakeholders observed that despite the extensive support available to athletes, many do not engage with available support, and the prevalence of a performance narrative has led to an environment that discourages holistic development. It follows that sport organizations could develop alternative strategies for promoting athletes’ access to and engagement with available supports, while funding agencies might broaden existing funding criteria to include well-being or athlete development targets.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.772

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)0.0010.000

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 head0.023
GPT teacher head0.319
Teacher spread0.295 · 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

Citations28
Published2021
Admission routes1
Has abstractyes

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