Associations between school-level environment and individual-level factors of walking and cycling to school in Canadian youth
Bibliographic record
Abstract
Identifying individual-level and school-level correlates of walking and cycling to school remains a public health priority as only one in four Canadian youth actively travels to school. This study aimed to estimate the prevalence of Canadian youth in grades 6 to 10 who walk, cycle, or use motorised transport to go to school, and to examine if school neighbourhood walkability, neighbourhood-level and individual-level correlates are associated with mode of transportation to school. Data come from the 2017/2018 Health Behaviour in School-aged Children study. The walkability of the schools' neighbourhood was measured using the Canadian Active Living Environments (Can-ALE) index. We observed that only 22.4% and 4.2% of youth walked and cycled to school, respectively. Most (73.4%) used motorised transport to school, including 53.2% of youth who lived less than 5 minutes from school. Schools located in neighbourhoods with higher Can-ALE classes (i.e., higher walkability) were positively associated with walking to school. No statistically significant association between school walkability and cycling to school was observed. Individual-level socioeconomic status (SES) was associated with walking, but not cycling, to school. Conversely, neighbourhood-level SES was associated with cycling, but not with walking, to school. Correlates of walking to school differed from those for cycling to school, suggesting that different approaches to promoting active transportation are needed.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".