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Record W4400032533 · doi:10.1123/iscj.2023-0091

Examining the Relationship Between Perceived Coaching Approaches for Life Skills Development and Life Skills Outcomes for High School Athletes

2024· article· en· W4400032533 on OpenAlexaff
Scott Pierce, Liam O’Neil, Martin Camiré, Corliss Bean, Scott Rathwell

Bibliographic record

VenueInternational Sport Coaching Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of LethbridgeBrock UniversityUniversity of Ottawa
Fundersnot available
KeywordsCoachingAthletesPsychologyLife skillsApplied psychologyDevelopmental psychologyPhysical therapyMedicinePedagogyPsychotherapist

Abstract

fetched live from OpenAlex

Promoting life skills is a prominent focus of the mission of high school sports. The purpose of this study was to examine the relationship between perceived coaching approaches for life skills development and life skills outcomes for high school athletes. A total of 346 athletes participating in high school sports from the United States completed the athlete-reported version of the Coaching Life Skills in Sport Questionnaire (perceived implicit and explicit coaching approaches) and the Life Skills Scale for Sport. Findings from hierarchical and stepwise regression models revealed that perceived implicit and explicit levels of coaching were differentially associated with each of the eight life skills outcomes, with the most consistent and significant predictor of life skills outcomes being structuring and facilitating a positive climate. Findings are discussed in relation to the conceptual and practical utility of the implicit–explicit continuum of life skills development and transfer, the importance of coach and athlete awareness of coaching approaches for life skills development, and recognition of the strengths and limitations of a variety of ontological and epistemological approaches to studying life skills in sport.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.100
GPT teacher head0.335
Teacher spread0.235 · 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.

Study designObservational
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

Citations3
Published2024
Admission routes1
Has abstractyes

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