Predictors of Driving Among Families Living Within 2 km from School
Bibliographic record
Abstract
This paper aims to present and evaluate demographic characteristics, parent/family level factors, attitudinal factors, psychosocial mediators, route features, resources and environmental factors which appear to influence the decision to drive children who live close enough to walk to and from school within the Greater Toronto and Hamilton Area (GTHA), Canada. Telephone interviews were conducted in 2009 with 1,001 parents of children attending elementary school in the GTHA. Analyses were performed for parents living less than 2 km away from school (n=529). Two groups were created: parents who typically drive their children to/from school (n=191) and parents who typically allow their children to walk to/from school (n=338). Descriptive statistics were used to examine household demographics, parent/family factors, attitudinal factors, psychosocial mediators, route features, resources and environmental factors. Independent-samples t-tests and chi-square analyses were used to test for group differences in these. Variables which were significantly different between groups were incorporated into logistic regression analyses to identify predictors of driving behavior. Children were more likely to be driven to school if they had less independent mobility, had fewer traveling companions and engaged in less discussion with their parents on how to walk or cycle to school safely; drivers were less concerned about the trip to school as an important source of physical activity, were more interested in alternative travel modes, had greater distances to travel and faced a greater proportion of local roads and major and minor intersections in their neighborhoods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".