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Record W2553233140 · doi:10.1177/1747954116676116

Describing and classifying coach development programmes: A synthesis of empirical research and applied practice

2016· article· en· W2553233140 on OpenAlexaff
Jordan S. Lefebvre, M. Blair Evans, Jennifer Turnnidge, Heather L. Gainforth, Jean Côté

Bibliographic record

VenueInternational Journal of Sports Science & Coaching · 2016
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of British ColumbiaQueen's University
Fundersnot available
KeywordsCoachingIntrapersonal communicationPsychologyContext (archaeology)Interpersonal communicationEmpirical researchApplied psychologySocial psychology

Abstract

fetched live from OpenAlex

Coach development, coach development programmes are conducted to change coach behavior in a specific domain. To facilitate understanding of this growing field, the current synthesis review of coaching literature was conducted to generate classifications of coach development programme types. To identify coach development programmes described within academic research, a supplemental search of an earlier systematic review was conducted. In addition, a broad Internet search was used to identify publically available descriptions of coach development programmes. After extracting information describing the resulting 285 coach development programmes, the research team distinguished 16 coach development programme domains of focus, classified within professional, interpersonal, or intrapersonal domains. Five organizational contexts were also identified in relation to “where” and “why” coach development programmes were conducted, and the coaching context and mode of delivery were also classified. As an effort to bridge applied and empirical realms, the continued use and development of these classifications will facilitate the further progress and synthesis of coach development literature.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.166
GPT teacher head0.462
Teacher spread0.296 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations88
Published2016
Admission routes1
Has abstractyes

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