The Influence of the Physical Environment and Sociodemographic Characteristics on Children's Mode of Travel to and From School
Bibliographic record
Abstract
OBJECTIVES: We examined whether certain characteristics of the social and physical environment influence a child's mode of travel between home and school. METHODS: Students aged 11 to 13 years from 21 schools throughout London, Ontario, answered questions from a travel behavior survey. A geographic information system linked survey responses for 614 students who lived within 1 mile of school to data on social and physical characteristics of environments around the home and school. Logistic regression analysis was used to test the influence of environmental factors on mode of travel (motorized vs "active") to and from school. RESULTS: Over 62% of students walked or biked to school, and 72% from school to home. The likelihood of walking or biking to school was positively associated with shorter trips, male gender, higher land use mix, and presence of street trees. Active travel from school to home was also associated with lower residential densities and lower neighborhood incomes. CONCLUSIONS: Our findings demonstrate that active travel is associated with environmental characteristics and suggest that school planners should consider these factors when siting schools in order to promote increased physical activity among students.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".