The Effect of the Social and Physical Environment on Children’s Independent Mobility to Neighborhood Destinations
Bibliographic record
Abstract
BACKGROUND: Relationships between context-specific measures of the physical and social environment and children's independent mobility to neighborhood destination types were examined. METHODS: Parents in RESIDE's fourth survey reported whether their child (8-15 years; n = 181) was allowed to travel without an adult to school, friend's house, park and local shop. Objective physical environment measures were matched to each of these destinations. Social environment measures included neighborhood perceptions and items specific to local independent mobility. RESULTS: Independent mobility to local destinations ranged from 30% to 48%. Independent mobility to a local park was less likely as the distance to the closest park (small and large size) increased and less likely with additional school grounds (P < .05). Independent mobility to school was less likely as the distance to the closest large park increased and if the neighborhood was perceived as unsafe (P < .05). Independent mobility to a park or shops decreased if parenting social norms were unsupportive of children's local independent movement (P < .05). CONCLUSIONS: Independent mobility appears dependent upon the specific destination being visited and the impact of neighborhood features varies according to the destination examined. Findings highlight the importance of access to different types and sizes of urban green space for children's independent mobility to parks.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".