The relationship between school ground design and intensity of physical activity
Bibliographic record
Abstract
In this study, we investigated the relationship between school ground design and children's physical activity levels. In particular, we were interested in understanding the contribution of ‘green’ school ground design to physical activity levels. Data for this study were collected at an elementary school in Australia and in Canada. At each school, scans of Target Areas were completed to record the students' location and intensity of physical activity, based on the System for Observing Play and Leisure Activity in Youth (SOPLAY) (Australia: 23 scans, 6 Target Areas; Canada: 18 scans, 7 Target Areas). At both schools, the highest percentage of children present was engaged in vigorous physical activity on the manufactured equipment (42% of children/scan). Similarly, at both schools, the green area encouraged the highest percentage of children present to be engaged in moderate physical activity (47% of Australian children/scan, 51% of Canadian children/scan). The patterns of sedentary behavior differed slightly between countries. At the Australian school, the paved sporting courts (57%) and the paved canteen courtyard (50.5%) promoted the highest degree of sedentary play. At the Canadian school, the treed grassy berm (42%) and the treed concrete steps (43%) encouraged the highest percentage of sedentary behavior, followed by the open asphalt (34%). These results are also discussed in light of gender distribution. We conclude with a discussion of the design and cultural factors that influence children's physical activity on school grounds. We argue that if school grounds are to realize their potential to promote physical activity, they should include a greater diversity of design features and ‘green’ elements that engage children of varying interests and abilities in active play.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".