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Record W4401717395 · doi:10.1123/iscj.2023-0103

A Qualitative Exploration of Coaches’ Perceived Challenges and Recommendations Relating to Social Justice in Canadian High School Sport

2024· article· en· W4401717395 on OpenAlexaffabout
Evan Bishop, Martin Camiré

Bibliographic record

VenueInternational Sport Coaching Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsEconomic JusticePsychologyQualitative researchSocial justiceApplied psychologySociologyCriminologyPolitical scienceSocial scienceLaw

Abstract

fetched live from OpenAlex

Sport can at once promote social justice and reinforce systemic inequities. Considering the influence coaches have on athlete development, research related to coaches’ perspectives on social justice issues is warranted. The purpose of the study was to explore Canadian high school sport coaches’ attitudes towards social justice. An online survey saw 392 coaches respond to six open-ended questions on perceived challenges (three questions; n = 989 responses) and recommendations (three questions; n = 724 responses) related to social justice within their teams, schools, and school boards. A content analysis led to coaches’ responses being classified into three groups: (a) high school sport faces social justice issues (57.38%), (b) no social justice challenges and/or recommendations to share (39.34%), and (c) urgency regarding social justice issues is overblown (3.28%). A reflexive thematic analysis, guided by the critical positive youth development framework, was used to develop several overarching themes, highlighting persistent inequities, a lack of involvement from school boards, missed/ignored social justice issues, and a small group of antisocial justice coaches within the Canadian high school sport system. Considerations for coach education programmes and future research are discussed.

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)0.003
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 score0.275
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.101
GPT teacher head0.408
Teacher spread0.307 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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