Development and application of a geospatial index of urban playability for young children
Bibliographic record
Abstract
Playing outdoors supports young children's physical, cognitive and social-emotional health and development. However, urban environments may limit children's outdoor play. We developed an evidence-based index to evaluate neighbourhood supportiveness for young children's outdoor free play, and applied it across 35 Canadian cities. From an evidence-based, theoretical framework for neighbourhood playability among children, 2–6 years, we identified five major domains influencing outdoor free play: spaces for play , social , traffic/pedestrian and natural environments , and child-relevant destinations . We selected indicators for each domain from open-source geospatial, satellite and census data, and weighted indicators based on findings from a survey of experts. We applied the index at the postal code level, and examined associations between playability, population density and material advantage/disadvantage. We found wide variation (52–77 %) in neighbourhood playability within the same city. However, average playability differences between cities was relatively small (≤ 20 %). Higher density areas had higher traffic/pedestrian and child-relevant destination scores, but lower social and natural environment scores, while space for play showed no relationship with density (persons/km 2 ). Within study cities, 39 % of young children lived in neighbourhoods where at least one domain averaged at or below the 10th percentile score. For a majority of cities (20/35), materially disadvantaged neighbourhoods had lower playability scores. Across Canadian cities, children's access to playable neighbourhoods varies widely. The playability index enables small area-level assessment of supportiveness, barriers and facilitators to young children's outdoor play. The theoretical framework and methodological approach may be adapted to develop indices of playability across diverse urban contexts. • A novel playability index was developed to assess urban/suburban environments for young children's outdoor play. • Playability index domains include: spaces for play, social environments, traffic/pedestrian environments, natural environments and child-relevant destinations. • Children experience wide disparities residential neighbourhood playability within the same city. • Playability scores were generally higher in materially advantaged and lower density neighbourhoods. • The index provides a high-level tool to evaluate young children's equitable access to playable neighbourhoods in cities.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".