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Record W2059072813 · doi:10.1260/1747-9541.7.1.89

Understanding Motivational Processes in University Rugby Players: A Preliminary Test of the Hierarchical Model of Intrinsic and Extrinsic Motivation at the Contextual Level

2012· article· en· W2059072813 on OpenAlexafffund
J. Paige Pope, Philip M. Wilson

Bibliographic record

VenueInternational Journal of Sports Science & Coaching · 2012
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsBrock UniversityWestern University
FundersSocial Sciences and Humanities Research Council of CanadaBrock University
KeywordsPsychologyCoachingAthletesSocial psychologyPerceptionTest (biology)AutonomyStructural equation modelingSelf-determination theoryStyle (visual arts)Applied psychologyMultilevel modelDevelopmental psychologyPhysical therapy

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the relationship between perceptions of autonomy support, structure and involvement provided by the head coach and motivational processes at mid- and late-season in competitive rugby players. Participants ( M age = 20.17 years, SD = 1.61 years, Range = 18 to 27 years) completed assessments of perceived coaching style and psychological need fulfillment at the mid-season point ( n mid-season = 102; 47.05% female) and motivation to continue playing rugby and perceived effort spent playing rugby at the late-season assessment ( N late-season = 82; 53.64% female). Structural equation modeling analyses provided support for a conceptual model whereby global perceptions of coach support predicted greater need fulfillment which, in turn, was associated with autonomous sport motivation and greater perceived effort. Overall, the results of this study lend partial support for Vallerand's contentions regarding the importance of motivation processes in sport and imply structure and involvement may be important components of a coach's interactional style that impact athletes' motivation.

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)0.001
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 score0.046
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.112
GPT teacher head0.303
Teacher spread0.191 · 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

Citations60
Published2012
Admission routes2
Has abstractyes

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