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Record W2942420449 · doi:10.1097/jsm.0000000000000665

Canadian Centre for Mental Health and Sport (CCMHS) Position Statement: Principles of Mental Health in Competitive and High-Performance Sport

2019· article· en· W2942420449 on OpenAlexaffabout
Krista J. Van Slingerland, Natalie Durand‐Bush, Lindsay Bradley, Gary S. Goldfield, Roger Archambault, D. E. Smith, Carla Edwards, Samantha Delenardo, Shaunna Taylor, Penny Werthner, Göran Kenttä

Bibliographic record

VenueClinical Journal of Sport Medicine · 2019
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsOkanagan CollegeUniversity of British ColumbiaMcMaster UniversityCanadian Psychological AssociationCarleton UniversityUniversity of CalgaryMental Health Research CanadaChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsMental healthPosition statementAthletesCompetitive athletesMultidisciplinary approachPublic relationsMission statementParticipatory action researchCitizen journalismApplied psychologyPsychologyMedicinePolitical sciencePsychiatrySociologyFamily medicinePhysical therapySocial science

Abstract

fetched live from OpenAlex

The brave decision made by many Canadian athletes to share their experience with mental illness has fed a growing dialogue surrounding mental health in competitive and high-performance sport. To affect real change for individuals, sport culture must change to meet demands for psychologically safe, supportive, and accepting sport environments. This position statement addresses mental health in competitive and high-performance sport in Canada, presenting solutions to current challenges and laying a foundation for a unified address of mental health by the Canadian sport community. The paper emerged from the first phase of a multidisciplinary Participatory Action Research (PAR) project, in which a sport-focused mental health care model housed within the Canadian Centre for Mental Health and Sport (CCMHS) is currently being designed, implemented, and evaluated by a team of 20 stakeholders, in collaboration with several community partners and advisors.

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)0.020
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.952
Threshold uncertainty score0.484

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0140.013
Scholarly communication0.0080.003
Open science0.0060.007
Research integrity0.0110.018
Insufficient payload (model declined to judge)0.0090.002

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 head0.035
GPT teacher head0.395
Teacher spread0.360 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations96
Published2019
Admission routes2
Has abstractyes

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