Exploring the Factors that Influence Female Students’ Decision to (Not) Enrol in Elective Physical Education: A Private School Case Study
Bibliographic record
Abstract
This article presents the results from a qualitative case study that examined the influencers upon a somewhat unique group of female students who opted out of elective physical education (PE). More specifically, this study focused upon female students attending an affluent private school, investigating why—when they transitioned from middle school to senior high school and PE became optional—they opted out of the class. Employing a research design that relied principally upon in-depth interviews, seven themes emerged from the students’ stories: perspectives on policy and PE programming, co-ed problems; friends’ influence, parental support for opting out, A+ academic achievement, free time and electives, and adequate physical activity accumulation outside of school. By considering these themes, particularly as they align with an Ecological Systems Theory, or EST (Bronfenbrenner, 1977) social-ecological framework, it is possible to more fully comprehend contributing influencers to these students’ decisions. Moreover, with this comprehension, we offer suggestions for future practice and inquiry.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".