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Record W2173175847 · doi:10.1177/2158244015588960

Masters Swimmers’ Experiences With Coaches

2015· article· en· W2173175847 on OpenAlexaff
Bettina Callary, Scott Rathwell, Bradley W. Young

Bibliographic record

VenueSAGE Open · 2015
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of OttawaCape Breton University
Fundersnot available
KeywordsCoachingPsychologyAthletesApplied psychologyInterpretative phenomenological analysisMedical educationPedagogySocial psychologyQualitative researchPsychotherapistSociology

Abstract

fetched live from OpenAlex

Much work addresses coaches’ contributions to younger athletes; however, the psycho-social coaching needs of adult Masters athletes remain unexamined. This study explored the lived experiences of 10 Masters swimmers (5 male, 5 female; age range = 45-65 years) through interviews. Interpretative phenomenological analysis delved into benefits that swimmers wanted to derive from coaches, how they wished to be coached, and what they liked about coaches. Themes related to (a) swimming and non-swimming benefits; (b) coaches’ experience and professional development, personal attributes, and behaviors holding athletes accountable to training; (c) preferences for coaching instruction; (d) preferences for coaches’ planning/structuring of the practice and program; and (e) preferences for how coaches prepare and interact with them at competitions. We discuss how benefits relate to models of athlete development and identify how preferences link to adult learning literature and models of coaching practice. Finally, we note incongruent findings and limitations to be addressed in future.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.003
Scholarly communication0.0030.001
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.135
GPT teacher head0.382
Teacher spread0.247 · 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

Citations29
Published2015
Admission routes1
Has abstractyes

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