The Reflections of Gender in Physical Education: Insights from Teachers and Metaphorical Representations
Bibliographic record
Abstract
This study aimed to determine physical education teachers’ views on physical education lessons from a gender perspective. The study also sought to exemplify teachers’ attitudes and behaviors towards students in classes, including their view on sports and school athletes, and behaviors within the framework of gender by assessing their metaphorical perceptions about female and male students. A total of 16 physical education teachers (eight female and eight male) aged between 32 and 51 employed in state and private secondary schools participated in the study. The study used the illustrative case study method, a qualitative research design. It also performed semi-structured individual interviews for data collection and used content analysis for data evaluation. Data collection was carried out between February and April of the 2022–2023 academic year. The study findings indicated that many participant teachers acted with gender-based stereotypes in their communication style, sports branch orientation, and definitions of successful athletes. While teachers typically described female students using the metaphors of “kind, delicate, and fragile,” they metaphorically defined male students as “strong, competitive, and enduring.” Additionally, many teachers classified sports into gender-specific branches; accordingly, they considered volleyball and tennis for girls, whereas football and wrestling were for boys. However, a few teachers observably displayed egalitarian and high-awareness approaches. As a result, this study shed light on how gender schemas shaped the pedagogical attitudes of teachers and revealed the need for awareness-raising to establish more inclusive physical education settings.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| 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".