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Record W2431139842 · doi:10.1515/pcssr-2016-0016

The Effect of Coaching Practices on Psychological Contract Fulfillment of Student-Athletes

2016· article· en· W2431139842 on OpenAlexaffabout
Davar Rezania, Robert Gurney

Bibliographic record

VenuePhysical Culture and Sport Studies and Research · 2016
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsMacEwan UniversityUniversity of Guelph
Fundersnot available
KeywordsCoachingPsychological contractAthletesPsychologyCompensation (psychology)Applied psychologyPosition (finance)Social psychologyBusinessFinancePhysical therapyPsychotherapistMedicine

Abstract

fetched live from OpenAlex

Abstract We examine the relationships between coaching practices, psychological contract fulfillment and the impact it has on satisfaction and in-role behavior of student-athletes. We surveyed a total of 183 student-athletes in Canada. Utilizing Partial Least Squares path modeling algorithm, the results confirm that the extent of psychological contract fulfillment is positively related to satisfaction and role-behavior. In addition, practices of compensation, information sharing, and security (i.e. ensuring continuation of position on the team) are related to fulfillment of psychological contracts. However, the data does not provide support for the idea that training is related to the fulfillment of psychological contracts. The results suggest that universities can manage students-athletes’ expectations by institutionalizing coaching practices that signal commitments for compensation, information sharing, and provide assurance of position on the team. Such practices have potential to improve the athlete’s performance.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.065
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.105
GPT teacher head0.518
Teacher spread0.412 · 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 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

Citations6
Published2016
Admission routes2
Has abstractyes

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