Redesigning physical education in Canada
Bibliographic record
Abstract
Proposals for redesign of Canadian physical education (PE) are timely. While Canada has promising initiatives that reflect ongoing redesign, there are several instances where “institutional auto-pilot” has led to negative outcomes for many children, particularly for those who have been historically marginalized in mainstream PE pedagogies and practices. In the chapter we embrace a spirit of reconciliation with and affirmation of Indigenous ways, while also responding to related calls for action. We focus on three key areas for which redesign efforts currently are underway or where opportunities remain. First, regarding identity and equity, we suggest specific redesigns of school funding, PE and PE teacher education (PETE) curricula, and the recruitment and retention of PETE students and faculty in order to destabilize whiteness. Second, we identify how the concept of physical literacy has functioned to build bridges across sectors in Canada, whereas health literacy has not, leading to a critical opportunity to merge agendas. Third, we consider how the nexus of policy, ethics, and culture may impact the implementation of these redesign initiatives. We conclude by identifying a reprioritization of research agendas towards policy and practice as a pressing task because our ability to conduct evidence-based advocacy depends on it.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".