Investigating social inequalities in children’s independent mobility, active transportation and outdoor free play in two Canadian cities
Bibliographic record
Abstract
Background: Active transportation (AT) and free play (FP) are the primary ways in which children engage in unstructured physical activity in cities, with independent mobility (IM) gaining increased attention as a potential precursor of AT and FP. However, current trends show that children are engaging in less FP and AT, and have less IM, than previous generations and it is not well understood how these practices, and their interrelatedness, differ by neighbourhood-level socio-economic stats (SES) and municipal contexts. Objectives: This study aims to address the gaps in knowledge by quantifying, comparing, and correlating IM, AT, and FP practices in high and low-SES neighbourhoods within and across the cities of Montreal and Kingston, Canada. Methods: 584 questionnaires were distributed among children in grades 1 to 5, living in low- and high-SES neighbourhoods of these two citiesResultsEngagement in the three practices was low in every study neighbourhood, though all three practices were higher in high-SES compared to low-SES neighbourhoods in both cities. Levels of FP were higher in Kingston compared to Montreal, while AT was higher in Montreal than in Kingston. Conclusion: This study revealed social inequalities in all three of these practices based on socioeconomic status and city. Since IM is likely a precursor to both independent FP and AT, more research is warranted into how our cities can become more conducive to IM in children, particularly in low SES neighbourhoods where children have less freedom of movement independently and otherwise.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".