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Record W2892270673 · doi:10.1123/jsep.2018-0008

Providing Social Support to Female Olympic Athletes

2018· article· en· W2892270673 on OpenAlexaff
Zoë A. Poucher, Katherine A. Tamminen, Gretchen Kerr

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2018
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAthletesSocial supportPsychologyInterpersonal communicationApplied psychologyElite athletesSocial psychologyMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Support providers may experience positive and negative outcomes associated with supporting others. However, there is a lack of research on support provision to elite athletes and the views of athletes' support providers. This study addressed this gap by exploring the experiences of providing and receiving support between female Olympians and their main support providers. Five female Olympians and their main support providers participated in separate semistructured interviews. It appeared that support provision was personally and professionally rewarding, as well as challenging, for support providers, and athletes were generally satisfied with the support they received. Athletes appeared highly dependent on their support providers, but both athletes and support providers felt that high levels of support were necessary for athletic success. Further research is needed to understand how support providers are able to foster their own personally supportive relationships and whether high levels of interpersonal dependence are required to achieve athletic success.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0050.001

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 head0.034
GPT teacher head0.360
Teacher spread0.326 · 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.

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

Citations18
Published2018
Admission routes1
Has abstractyes

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