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Record W2102229280 · doi:10.1123/tsp.26.1.135

Female Athletes’ Perceptions of Teammate Conflict in Sport: Implications for Sport Psychology Consultants

2012· article· en· W2102229280 on OpenAlexaff
Nicholas L. Holt, Camilla J. Knight, Peter Zukiwski

Bibliographic record

VenueThe Sport Psychologist · 2012
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAthletesSport psychologyPsychologyConflict resolutionPerceptionApplied psychologySocial psychologySociologySocial sciencePhysical therapyMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to examine female varsity athletes’ perceptions of teammate conflict. Semistructured interviews were conducted with 19 female varsity athletes (M age = 21.17 years) from four sport teams. Analysis revealed that conflict was a prevalent feature of playing on their teams. Conflict relating to performance and relationships was identified. Strategies athletes thought may help create conditions for managing conflict were to (a) engage in team building early in the season, (b) address conflict early, (c) engage mediators in the resolution of conflict, and (d) hold structured (rather than unstructured) team meetings. It also seemed that athletes required personal conflict resolution skills. These findings are compared with previous research and offered as implications for professional practice.

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)0.005
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 score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.073
GPT teacher head0.417
Teacher spread0.344 · 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

Citations57
Published2012
Admission routes1
Has abstractyes

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