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Record W2527582177 · doi:10.1080/1612197x.2016.1218529

Psychological collectivism in youth athletes on individual sport teams

2016· article· en· W2527582177 on OpenAlexafffund
Janice L Donkers, Luc J. Martin, M. Blair Evans

Bibliographic record

VenueInternational Journal of Sport and Exercise Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsQueen's UniversityUniversity of Lethbridge
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyCollectivismModerationAthletesSocial psychologyStructural equation modelingDevelopmental psychology

Abstract

fetched live from OpenAlex

The purpose of the current study was to determine whether psychological collectivism could predict enjoyment and intentions to return in athletes on individual sport teams. In addition, structural interdependence and age were used as moderator variables for the proposed relationships. A total of 142 youth (Mage = 14.44 years; SD = 1.63; 62% female) completed questionnaires at two data-collection periods (T1 – psychological collectivism, structural interdependence, and age; T2 – enjoyment and intentions to return), and the results indicated that psychological collectivism positively predicted both enjoyment and intentions to return. Also, task interdependence significantly moderated the relationship between psychological collectivism and enjoyment (b = .14, t(137) = −1.90, p = .06) and intentions to return (b = −.17, t(137) = −2.07, p < .05). Specifically, in situations where athletes were required to work together during competition (e.g. relays), athletes’ collectivistic orientation had a stronger relationship with both enjoyment and intentions to return. Similarly, among older athletes, collectivism had a stronger positive relationship with intentions to return (b = .05, t(138) = 2.04, p < .05). These results are discussed in terms of their theoretical and practical implications.

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 score0.082
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.034
GPT teacher head0.339
Teacher spread0.305 · 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

Citations14
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Sport and Exercise PsychologySame topicMotivation and Self-Concept in SportsFrench-language works237,207