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Record W3166533003 · doi:10.47206/ijsc.v1i1.55

Reflective Practice: Helping Coaches Improve their Coaching

2021· article· en· W3166533003 on OpenAlexaff
Xavier Roy, Simona E. Gavrila, Pierre Sercia

Bibliographic record

VenueInternational Journal of Strength and Conditioning · 2021
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversité de MontréalUniversité du Québec à MontréalBishop's University
Fundersnot available
KeywordsCoachingReflective practiceReflexivityPsychologyProcess (computing)Reflection (computer programming)Applied psychologyMedical educationPedagogyComputer scienceSociologyPsychotherapistMedicine

Abstract

fetched live from OpenAlex

ABSTRACT Reflective practice has recently been advocated as approach for sports and strength and conditioning coaches to question, learn from, and understand their own experiences to adapt and/or change their subsequent behaviors and decision-making processes. This article discusses the importance of reflexive practice for coaches and provides examples of how reflective practice can be implemented at each step of the coaching process.

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)0.042
metaresearch head score (Gemma)0.132
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: none
Teacher disagreement score0.042
Threshold uncertainty score0.223

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.132
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0050.004
Scholarly communication0.0100.008
Open science0.0030.008
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0050.004

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 head0.022
GPT teacher head0.359
Teacher spread0.337 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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Same venueInternational Journal of Strength and ConditioningSame topicSport Psychology and PerformanceFrench-language works237,207