MétaCan
Menu
Back to cohort
Record W4402402159 · doi:10.1080/14927713.2024.2399602

Opening doors to coach education in masters sport for lifelong sport participation

2024· article· en· W4402402159 on OpenAlexafffundvenue
Bettina Callary, Kimberley Eagles, Scott Rathwell, Bradley W. Young

Bibliographic record

VenueLeisure/Loisir · 2024
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of LethbridgeUniversity of OttawaCape Breton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDoorsLifelong learningPedagogyMedical educationPsychologySociologyPolitical scienceVisual artsEngineeringArtMedicineMechanical engineering

Abstract

fetched live from OpenAlex

Coach education directors of sport organizations are responsible for developing coaches to support quality sport participation. While adults comprise an increasingly larger cohort in many sport organizations, their programming, including coaching and coach education, is marginalized. The purpose of this collective case study was to outline directors’ perceptions of challenges and interests regarding lifelong sport participation through their perspectives of adult-oriented professional development for coaches in their sport organizations. Five directors of coach education attended webinars on coaching Masters sport and then engaged in follow-up interviews. Data were reflexively thematically analyzed. The results indicated that directors acknowledge differences in coaching adults and youth but a coaching focus on youth and high performance. They discussed the benefits of supporting Masters sport through quality coaching for lifelong sport participation and valued adult-oriented coaching approaches. Lifelong sport pathways could advance with shifts toward supporting Masters sport with quality coach education.

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)0.005
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0130.004
Scholarly communication0.0040.003
Open science0.0010.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0150.001

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 head0.036
GPT teacher head0.398
Teacher spread0.361 · 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
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 routes3
Has abstractyes

Explore more

Same venueLeisure/LoisirSame topicSport Psychology and PerformanceFrench-language works237,207