Bibliographic record
Abstract
There are approximately 4.4 million Canadians (14%) with a physical disability, yet less than 1% of these individuals participate in organized sport programs (Sport Canada, 2006; Statistics Canada, 2007). Using Self-Determination Theory (SDT) as a framework, the purpose of the current study was to examine the relationship between Paralympic athletes’ perceptions of coach behaviour, psychological needs satisfaction, and motivation. The participants in this study were 113 Canadian Paralympic athletes. Participants completed an online survey comprised of the Sport Climate Questionnaire (Deci & Ryan, 2006), measures of perceived autonomy (Hollembeak & Amorose, 2005), competence (Hollembeak & Amorose, 2005), relatedness (Richer & Vallerand, 1998) and the Sport Motivation Scale (Pelletier et al., 1995). Confirmatory factor analysis was used to test the measurement model. Path modeling was used to test the relationships among perceptions of coach behaviour, the basic psychological needs of competence, autonomy, and relatedness, and motivation. Findings from the path model partially supported the tenets of SDT. There was a significant relationship between perceptions of coach behaviour and perceived autonomy and relatedness. Autonomy and competence were significant correlates of motivation. Results revealed the presence of a relationship between perceptions of autonomy supportive coaching strategies, the three psychological needs, and athletes’ intrinsic motivation towards sport. These findings hold theoretical and practical significance as they underscore the importance of using autonomy supportive coaching strategies to promote motivation in Paralympic athletes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".