The Moderating Role of Perception of Control in the Relationship between Competence Evaluation and Sports Motivation among Athletes
Bibliographic record
Abstract
Understanding the role of perception of control in the relationship between competence evaluation and athletes’ sports motivation is sacrosanct for optimal performance and participation. The present study examined the direct effect of competence evaluation by (a) investigating its relationship with athletes' sports motivation, (b) the direct effect of perception of control on athletes' sports motivation, and (c) testing the indirect effect of perception of control on the relationship between competence evaluation and athletes’ sports motivation. Student-athletes (N = 200, Mage = 20.61 years; SD = 3.73) completed self-report measures assessing competence evaluation, sports motivation and perception of control. Regression analysis showed that competence evaluation and perception of control were significantly associated with sports motivation; however, the perception of control moderated the interaction of competence evaluation and athletes' sports motivation. Thus, competence evaluation was significantly associated with sports motivation for athletes with moderate and high perceptions of control. The findings underscore the need for athletes, coaches, sports psychologists, and other sports stakeholders to understand how competence evaluation and perception of control interrelate to boost motivational levels among athletes in sports competitions.
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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 | 0.003 | 0.011 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".