Attitudes of Experienced Health and Physical Education Teachers Toward the Inclusion of Females with Physical Disabilities in General Health and Physical Education Classes
Bibliographic record
Abstract
The purpose of this qualitative research study is to explore experienced health and physical education teacher attitudes toward the inclusion of students with physical disabilities, particularly females. Experienced was defined as having five or more years of experience teaching the subject. Data was collected for this study through seven semi-structured interviews and a single focus group interview. Seven participants in total, four female and three male experienced health and physical education teachers, were drawn from the Greater Essex county District School Board (GECDSB). In addition, a subtle gender bias within these classes was also evident. Key factors that may impede upon experienced teacher attitudes included dysfunctional facilities for those with physical disabilities, a lack of resources, preparedness and inadequate training. Based on these findings, it is crucial that both educators and administrators question the current general health and physical education curriculum. In particular, it is recommended that teacher education programs must include appropriate training for health and physical educators with regard to how to appropriately instruct those with physical disabilities. Furthermore, educators can also broaden the variety of activity choices they teach in order to strive toward gender equity.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".