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Record W2110577712 · doi:10.1260/174795409789623928

Developmental Profiles of Successful High School Coaches

2009· article· en· W2110577712 on OpenAlexaff
Wade Gilbert, Luke Lichtenwaldt, Jenelle N. Gilbert, Lynnette Zelezny, Jean Côté

Bibliographic record

VenueInternational Journal of Sports Science & Coaching · 2009
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsQueen's University
Fundersnot available
KeywordsCoachingBasketballAthletesPsychologyApplied psychologyExploratory researchMedical educationRelation (database)Physical educationPedagogyPhysical therapyMedicine

Abstract

fetched live from OpenAlex

The purpose of this exploratory study was to compare the developmental profiles of successful high-school sport coaches, and to determine if elements of a coach's developmental profile were associated with coaching success. Sixteen high-school coaches in the United States – nine who coach basketball and seven cross-country running – participated in structured retrospective quantitative interviews. All coaches had accumulated extensive experience as an athlete ( M = 19.6 seasons; 2,428.8 hours) and were better than average athletes in relation to their peers. Positive significant relationships were found between time (seasons and hours) spent as an athlete in the sport that the participants now coach and five measures of coaching success. The results are discussed in relation to the ongoing dialogue about coach development, coaching effectiveness, and 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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.020
GPT teacher head0.333
Teacher spread0.313 · 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 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

Citations66
Published2009
Admission routes1
Has abstractyes

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