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Record W4412086763 · doi:10.1080/10413200.2025.2528735

Exploring and contextualizing the science to practice of psychological skills and characteristics during Chinese first level athletes’ meta-transitions

2025· article· en· W4412086763 on OpenAlexaff
Yufeng Li, Robert J. Schinke, Liwei Zhang, Yang Ge, Xiao Yang, Jinting Liu, Georges Kpazaï

Bibliographic record

VenueJournal of Applied Sport Psychology · 2025
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsLaurentian University
Fundersnot available
KeywordsAthletesPsychologyPsychological scienceMeta-analysisApplied psychologySports scienceSport psychologySocial psychologyPhysical therapy

Abstract

fetched live from OpenAlex

Career transition scholars have examined athletes’ experiences during various major transitions, including, but not limited to the junior-to-senior transition and retirement. Within these inquiries, psychological skills and characteristics (PSCs) are often conceptualized as a sub-theme associated with transition demands, barriers, and coping strategies. We aim to advance the understanding of how PSCs facilitate athletes’ meta-transitions by providing contextualized examples via a polyphonic tale. The intention is to equip athletes, coaches and sport psychology practitioners (SPPs) with effective strategies to support athletes’ transitions and long-term development. A culturally sensitive methodology was employed, situated within the Eastern philosophy of Confucian relationism. A group reflective practice interview was the chosen data collection method whilst also being a learning opportunity for athletes to increase their self-awareness. We found that most PSCs do span the developmental and transitional processes including meta-transitions, but there are also distinct PSCs that serve as important resources associated with the demands and barriers within each meta-transition. PSCs should be systematically introduced to athletes within the Chinese Whole Nation System (CWNS) and beyond from an early stage of athletic development as they provide the essential foundation for elite athletes’ long term and holistic growth.

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)0.002
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 score0.603
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.094
GPT teacher head0.392
Teacher spread0.298 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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