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Record W4220670026 · doi:10.3389/fpsyg.2022.832560

‘Safe Sport Is Not for Everyone’: Equity-Deserving Athletes’ Perspectives of, Experiences and Recommendations for Safe Sport

2022· article· en· W4220670026 on OpenAlexaff
Joseph Gurgis, Gretchen Kerr, Simon C. Darnell

Bibliographic record

VenueFrontiers in Psychology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAthletesPsychologyEquity (law)Social psychologySafeguardingInterpretative phenomenological analysisQualitative researchPolitical scienceSociologyMedicinePhysical therapyLaw

Abstract

fetched live from OpenAlex

There is a growing concern that the voices of athletes, and in particular, athletes from equity-deserving groups, are unaccounted for in the development and advancement of Safe Sport initiatives. The lack of consideration of the needs and experiences of diverse groups is concerning, given the existing literature outside the context of sport indicating that equity-deserving individuals experience more violence. As such, the following study sought to understand how equity-deserving athletes interpret and experience Safe Sport. Grounded within an interpretive phenomenological analysis, semi-structured interviews were used to understand how athletes with marginalised identities conceptualise and experience Safe Sport. Seven participants, including two Black male athletes, two White, gay male athletes, one Middle Eastern female athlete, one White, female athlete with a physical disability and one White, non-binary, queer, athlete with a physical disability, were asked to conceptualise and describe their experiences of Safe Sport. The findings revealed these athletes perceived Safe Sport as an unrealistic and unattainable ideal that cannot fully be experienced by those from equity-deserving groups. This interpretation was reinforced by reported experiences of discriminatory comments, discriminatory behaviours and systemic barriers, perpetrated by coaches, teammates, and resulting from structural aspects of sport. The findings draw on the human rights literature to suggest integrating principles of equity, diversity and inclusion are fundamental to safeguarding equity-deserving athletes.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score0.624

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 studies0.0010.000
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 head0.060
GPT teacher head0.397
Teacher spread0.336 · 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 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

Citations75
Published2022
Admission routes1
Has abstractyes

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