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Record W7027173546

Canadian national sport organizations’ eating disorder-related policies and practice guidelines: A summative content analysis

2023· article· en· W7027173546 on OpenAlexaffabout

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsSummative assessmentContent analysisCredibilityCLARITYScope of practiceCoachingCorporate governanceGuidelineAthletes
DOInot available

Abstract

fetched live from OpenAlex

Athletes are at significant risk of developing eating disorders (EDs). Sport policies can address the prevention, management, and return to sport following EDs. Although Canadian national sport organizations (NSOs) must comply with a universal code of conduct, there may be a need for additional policies and guidelines to address EDs. The purpose of this study was to examine the scope and content of ED-related policies and practice guidelines within Canadian NSOs. We searched all publicly available policy and guideline documents from Canada’s 64 NSOs and screened them for terms related to disordered eating, body image, nutrition/diet, exercise, and weight bias/stigma yielding 98 policies and 39 guidelines. We conducted a summative content analysis to examine the contextual use of our search terms, and the social and cultural implications of such use. No NSO had specific policy or practice guidelines addressing EDs. In policies, ED-related concepts (e.g., body shaming; weight-control) were discussed using standard language from the universal code of conduct. In guidelines, ED-related topics were discussed in relation to mental health, coaching female athletes, athlete development, nutrition, positive body image, and weight management. Guidelines often used language that perpetuates weight stigma and the stereotype that EDs are a feminine issue. We also observed a lack of coherence wherein policies outline prohibited behavior, but guidelines do not provide adequate guidance for optimal behavior. This study provides insight into the lack of systemic action surrounding EDs in Canadian sport and can inform the development of governance mechanisms to better address EDs.

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)0.037
metaresearch head score (Gemma)0.117
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score0.612

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.117
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0140.016
Science and technology studies0.0090.004
Scholarly communication0.0030.002
Open science0.0020.005
Research integrity0.0010.002
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 head0.071
GPT teacher head0.317
Teacher spread0.246 · 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.

Study designQualitative
DomainMethods
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

Citations0
Published2023
Admission routes2
Has abstractyes

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