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Record W2551082578 · doi:10.1123/tsp.2016-0052

Examining the Experiences of Peer Mentored Athletes Competing in Elite Sport

2016· article· en· W2551082578 on OpenAlexaff
Matt D. Hoffmann, Todd M. Loughead, Gordon A. Bloom

Bibliographic record

VenueThe Sport Psychologist · 2016
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsMcGill UniversityUniversity of Windsor
Fundersnot available
KeywordsAthletesMentorshipElitePsychologyElite athletesApplied psychologyMedical educationPhysical therapyMedicinePolitical science

Abstract

fetched live from OpenAlex

The general objective of the current study was to explore the experiences of elite level athletes who reported being peer mentored by other athletes during their sporting careers. The primary purpose was to identify the mentoring functions provided by athlete mentors, while the secondary purpose was to examine the outcomes related to peer mentored athletes’ (i.e., protégés) mentoring experiences. Individual interviews were conducted with 14 elite peer mentored athletes, and the data were analyzed using a hierarchical content analysis. The results indicated that athlete mentors provided a variety of specific functions that facilitated protégés’ progression through sport and development from a personal standpoint. The findings also showed that protégés benefitted in terms of enhanced performance and confidence, and also demonstrated a willingness to provide mentorship to their peers. In sum, the results of the current study may be used to enhance the effectiveness of peer mentoring relationships between athletes.

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)0.003
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 score0.072
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.057
GPT teacher head0.346
Teacher spread0.289 · 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

Citations31
Published2016
Admission routes1
Has abstractyes

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