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Record W4409710968 · doi:10.1080/14413523.2025.2493430

Informing a culture shift in high performance sport in Canada: athletes’ unsafe and safe sport experiences

2025· article· en· W4409710968 on OpenAlexafffundabout
Eric MacIntosh, Alison Doherty, Shannon Kerwin

Bibliographic record

VenueSport Management Review · 2025
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsBrock UniversityWestern UniversityUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAthletesBusinessAdvertisingPsychologyPublic relationsMarketingPolitical sciencePhysical therapyMedicine

Abstract

fetched live from OpenAlex

The sport system in Canada has been over-run with allegations from athletes that expose the issues of safe sport for participants. To better understand the culture underlying this phenomenon, we explored the manifestations of unsafe and safe high performance (HP) sport, the feelings they evoked, and the values shaping those manifestations from the perspective of HP athletes. We spoke with 28 athletes (18 years+) regarding their HP sport experiences, and their feelings about unsafe and safe aspects. Athletes identified a range of behaviours and practices associated with both unsafe and safe sport conditions. The interpreted values associated with those unsafe and safe sport manifestations are discussed. The findings provide a platform for addressing the needed shift toward a safer sport culture by highlighting the feelings and values that frame unsafe and safe sport, from the athletes’ perspective.

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)0.003
metaresearch head score (Gemma)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0090.008
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.280
Teacher spread0.271 · 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

Citations7
Published2025
Admission routes3
Has abstractyes

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