Bibliographic record
Abstract
This study examines the relationship between safety, the built environment, and the mode of travel to and from school. The paper contributes to the literature by analyzing the actual route traveled through the use of objective traffic data within school neighborhoods. Parents and children completed a survey and mapping exercise to obtain travel routes to and from school, a methodological improvement over network shortest-path analysis. Manual traffic counts around the sampled schools (n = 17) were conducted. Logistic regression analysis confirmed a priori expectations about the effects of distance, gender, and the number of vehicles per licensed driver. New insights into safety were produced through inclusion of objective metrics designed to explore the safety of the pedestrian environment. A higher number of vehicles, a higher number of crossing streets, incomplete sidewalk networks, and the presence of parking facilities emerged as potentially important transport supply-, design-, and safety-related factors. If children perceived their neighborhood to be a safe area in which to walk alone, they were also more likely to walk. For parents, the perception that strangers were present and the presence of busy streets influenced the mode of travel. Different effects were produced across separately estimated home-to-school and school-to-home models.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".