Physical environments, policies and practices for physical activity and screen‐based sedentary behaviour among preschoolers within child care centres in <scp>M</scp>elbourne, <scp>A</scp>ustralia and <scp>K</scp>ingston, <scp>C</scp>anada
Bibliographic record
Abstract
BACKGROUND: Characteristics of preschool and child care centres have previously been shown to be associated with children's health behaviours such as physical activity and screen-based sedentary behaviour. This paper investigates differences in physical environments, policies and practices between child care centres in Melbourne, Australia and Kingston, Canada which may be associated with such behaviours. METHODS: Audits of child care centres were undertaken by trained research assistants for the Healthy Active Preschool and Primary Years (Melbourne, Australia; n = 136) study and the Healthy Living Habits in Pre-School Children (Kingston, Canada; n = 46) study. Twenty-one of the audit items (nine physical environment; 12 policies and practices) were assessed in both samples. Example items included outdoor play and shaded areas, availability of equipment, physical activity instruction for children and staff, opportunities to use electronic media and staff/child interaction during physical activity time. Analyses were completed using SAS version 9.2. RESULTS: Compared with Australian centres, a higher per cent of Canadian centres had a formal physical activity policy, reported children sat more frequently for 30 min or more and allowed children to watch television. A higher per cent of Australian centres provided an indoor area for physical activity, shade outdoors and physical activity education to staff. Children in Australian centres had access to more fixed play equipment and spent more time outdoors than in Canadian centres. CONCLUSIONS: These findings may help inform the development of best practice and policy guidelines to enhance opportunities for healthy levels of physical activity and screen-based sedentary behaviour within child care centres in both countries.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".