Paving the Way for Outdoor Play: Examining Socio-Environmental Barriers to Community-Based Outdoor Play
Bibliographic record
Abstract
Outdoor play and independent, neighborhood activity, both linked with healthy childhood development, have declined dramatically among Western children in recent decades. This study examines how social, cultural and environmental factors may be hindering children's outdoor and community-based play. A comprehensive survey was completed by 826 children (aged 10-13 years) and their parents from 12 schools (four each urban, suburban and rural) from a large county in Ontario, Canada. Five multilevel regression models, controlling for any school clustering effect, examined associations between outdoor play time per week and variable sets representing five prevalent factors cited in the literature as influencing children's outdoor play (OP). Models predicted that younger children and boys were more likely to spend time playing outdoors; involvement in organized physical activities, other children nearby to play with, higher perception of benefits of outdoor play, and higher parental perceptions of neighborhood social cohesion also predicted more time in outdoor play. Time outdoors was less likely among children not allowed to play beyond home without supervision, felt they were 'too busy' with screen-based activities, and who reported higher fears related to playing outdoors. Study findings have important implications for targeting environmental, cultural and policy changes to foster child-friendly communities which effectively support healthy outdoor 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 | 0.000 | 0.001 |
| 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".