Understanding Girls' Motivation to Participate in Sport: The Effects of Social Identity and Physical Self-Concept
Bibliographic record
Abstract
Introduction: Girls are often less motivated to participate in community sport compared to boys. Having a strong social identity with a sports team is positively associated with motivation to continue participation in sport, yet the mechanisms explaining this association are not well-known. In the current study, physical self-concept is tested as a mediator of the association between social identity and motivation. Method: Girl badminton athletes were recruited to examine how the team environment shapes physical self-concept, and whether this association relates to motivation to participate in sport. Ninety-two girls completed a self-report survey to measure social identity, physical self-perceptions, and motivation. Two mediation models were conducted to examine whether physical self-concept mediated the relationship between social identity and autonomous motivation and controlled motivation. Results: Physical self-concept partially mediated the relationship between social identity and autonomous motivation. The bootstrapped unstandardized indirect effect was, b = 0.05, 95% CI = 0.002 to.14. Physical self-concept fully mediated the relationship between social identity and controlled motivation. The bootstrapped unstandardized indirect effect was, b = −0.13, 95% CI = −0.30 to −0.01, p = 0.04. Discussion: These results highlight the importance of the group context in relation to individual physical self-concept and motivation. Overall, targeting aspects of the team environment in community-level sport may be an important strategy to improve girls' physical self-concept, and autonomous motivation to continue sport participation.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".