Physical education teachers’ experiences during the COVID-19 pandemic: conceptualizing outdoors as a job demand and resource for school wellbeing
Bibliographic record
Abstract
Education systems across the world were significantly impacted by the disruptions of the COVID-19 pandemic. To accommodate physical distancing requirements mandated by public health authorities, many school gymnasiums were co-opted to become classrooms, consequently displacing many physical and health educators to teach in outdoor contexts. Through semi-structured interview methods, this research unpacked the perspectives of 10 Canadian physical and health educators’ experiences teaching outdoors during the pandemic. Findings indicated that: (a) physical educators struggled to navigate COVID-19 school protocols; (b) outdoor learning environments mitigated the strain of these regulations; (c) outdoor contexts benefited the wellbeing of staff and students; and (d) there were challenges associated with teaching outdoors. Utilizing the job demands-resource theoretical framework, this study illuminated a novel concepetualization of how teaching in outdoor spaces served as both a challenging job demand, but also a valuable job resource to support school wellbeing.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".