DETERMINANTS OF PARENT PERCEPTIONS OF DANGEROUS TRAFFIC RELATED TO SCHOOL TRAVEL
Bibliographic record
Abstract
Background Walking to/from school is an important source of physical activity for children. Parents' perceptions of dangerous traffic affect whether or not their child walks to/from school. The determinants of parent's perceptions of dangerous traffic are currently unknown. Aims/Objectives/Purpose To determine which objective measures of the built environment and traffic at elementary schools are related to parent's perceptions of traffic danger. Methods Trained observers conducted school site surveys, vehicle speed/volume measurements and counts of school transportation modes in Toronto, Canada during school drop-off time. Parent surveys were distributed to grades 4–6 classrooms in 20 schools. Parents rated traffic danger en route to school and at school during drop-off as ‘not dangerous’, or ‘dangerous’. Multivariate cluster analyses were conducted. Results 729 parent surveys were returned with approximately ¼ of parents reporting either their child's route to school and/or school drop off time were dangerous. Higher measured car speed was a significant determinant of both dangerous route and drop-off. Parent-reported measure of distance and numbers of roads crossed were significantly related to dangerous route. Both ratings of danger were inversely related to reported walking to/from school. Significance Car speed was the only objectively measured built environment feature of the school site related to parent's perceptions of traffic danger. The relationship between features of the larger neighbourhood environment surrounding schools and parent perception of traffic danger requires investigation in order to further determine what influences children walking to school.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".