Bibliographic record
Abstract
Interest in school transportation has emerged in response to concern over the reduced levels of physical activity among children and youth. Recent Canadian policies emphasize population health intervention to encourage active travel among this younger population; urban planners and public health professionals have also highlighted the importance of the neighbourhood built environment. However, this “child-youth friendly” turn in policy and planning practice, particularly in Canada, has arguably occurred in advance of conclusive and generalizable knowledge about the relationship between the built environment and children’s travel. Within this context, this thesis is the first quantitative research that examines school transportation mode choice behaviour in the largest Canadian city, the City of Toronto. At first, a Behavioural Model of School Transportation was outlined. This exercise was followed by three empirical studies that explored school travel by children and youth, using travel data from Transportation Tomorrow Survey. The first of these three studies investigated the association between the built environment and the likelihood of walking or being driven, for journeys to and from school. The next study focused on a measurement issue; the potential influence of the modifiable areal unit problem on statistical modelling of the built environment - mode choice relationship was examined. Lastly, the potential influence of travel interactions among household members, the built environment, and unobservable spatial dependency (i.e., spatial auto-correlation), on school travel outcome of children and youth, were examined. The results indicated that caregiver availability may influence travel mode choice. The built environment near both home and school locations was associated with the likelihood of walking. In addition, the correlates of mode choice were different between children and youth, which perhaps, reflects a child’s cognitive development with age as an independent traveller. These findings suggest the need for neighbourhood-wide improvement in the built environment, and age-specific population health interventions at schools and in the communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.027 | 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 teacher head, 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".