Perceived Physical Competence, Self-Esteem, and Leadership among Girls: A Program Evaluation of GOALS (Girls Organizing and Learning Sport)
Bibliographic record
Abstract
This study evaluated a leadership-based physical activity program, Girls Organizing and Learning Sport (GOALS), by assessing changes in health behaviours, physical competence, self-esteem, and leadership. Of the 466 participants who enrolled in the program, 102 (22%) completed a pre-and post-program survey containing questions concerning demographics, physical activity, physical competence, self-esteem, and leadership. The GOALS program was held twice (fall 2022/winter 2023) and consisted of two-hour weekly sessions over four weeks at nine different locations. Paired-sample t-tests, Chi-squares, and one-way ANOVA tests were utilized to analyze differences before and after the GOALS program. Results revealed that more participants were involved in school sports, community sports, and regular physical activity post-program (all p’s < 0.05). A significant difference was also observed between pre-and post-test scores for physical competence and self-esteem (p’s < 0.05). However, the program did not elicit changes in health behaviours or total leadership scores (all p’s > 0.05). Moreover, significant results were observed between physical competence difference scores and those who care for their health by exercising (p = 0.025), leadership difference scores and those who take care of their health by exercising (p = 0.044), self-esteem difference scores by program location (p = 0.001), and physical competence difference scores by ethnicity (p = 0.003). Overall, further research into the design, administration, and targeted outcomes is recommended for future sessions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".