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Record W2310221429 · doi:10.1080/1612197x.2015.1114504

Experiences of competitive masters swimmers: Desired coaching characteristics and perceived benefits

2016· article· en· W2310221429 on OpenAlexaff
Gillian Ferrari, Gordon A. Bloom, Wade Gilbert, Jeffrey G. Caron

Bibliographic record

VenueInternational Journal of Sport and Exercise Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsMcGill University
Fundersnot available
KeywordsCoachingPsychologyAthletesThematic analysisApplied psychologyCompetitive athletesCompetitive sportPerceptionMedical educationQualitative researchPhysical therapyMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the experiences of competitive masters swimmers by asking them to describe desired coaching characteristics and perceived benefits associated with masters swimming. The research questions guiding this study were: What are masters swimmers’ desired coaching characteristics? What are masters swimmers’ perceptions regarding the benefits of participating in masters athletics? Semi-structured interviews were conducted with six competitive male masters swimmers aged 49–64 and the qualitative data were analysed using a thematic analysis. According to the athletes, their coaches used effective communication skills to establish positive environments that led to social, health, and performance improvements. In addition, the athletes reported how their coach's kept them focused and motivated prior to competitions when their training became more challenging. Results from this study are of interest to masters swimming athletes and coaches, and could be used to inform the development and design of programs that could optimise the performance and enjoyment of competitive masters swimmers.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.323
Teacher spread0.295 · 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

Citations26
Published2016
Admission routes1
Has abstractyes

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