Canada’s 150-minute ‘standard’ in physical education: a consideration of research evidence related to physical education instructional time
Bibliographic record
Abstract
Though physical education instructional time varies across Canada, an idealised standard of 150 minutes per week has been identified, followed, and aspired to by many. For example, Canada’s ‘best performers’ with respect to physical education instructional time achieve 150 minutes of weekly instruction. Moreover, Canada’s national association for physical and health education supports this same benchmark, offering awards to schools that achieve it. However, while this standard exists in practice for some and as a goal for others, it exists without any notable or significant evidence underpinning the proposed standard. Consequently, the 150-minute standard seems to be a target number lacking substantiation. Given these observations, the purpose of the study was twofold. First, we aimed to conduct a scoping literature review so that it might be possible for one to more clearly rationalise this 150-minute position suggested by many. Second, within the sourced body of evidence, we sought to identify and describe what relationship, if any, exists between instructional time (particularly 150 minutes of instructional time) and familiar physical education-related variables (i.e. physical fitness, physical activity, movement competence, movement confidence, academic learning/readiness). Considering our findings from this literature review, we also offer insights and possibilities for future inquiry, practice, and advocacy.
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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 | 0.050 | 0.142 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.015 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| 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".