Social inequalities in child pedestrian collisions: The role of the built environment
Bibliographic record
Abstract
Background Important inequities in child pedestrian-motor vehicle collisions (PMVC) have been observed. The mechanism through which social dimensions influence child PMVC is not well understood, nor is the role of the roadway-built environment. Methods The relationship between area-level social dimensions (material deprivation, proportion recent immigrants, proportion visible minority) and police-reported child PMVC between 2010 and 2018 in Toronto, Canada was examined using multivariable negative binomial regression models, controlling for built environment covariates. Results All social dimensions were significantly associated with child PMVC, including material deprivation (Incidence Rate Ratio (IRR–adjusted): 1.31, 95 % Confidence Interval (CI): 1.22–1.40), recent immigrant proportion (IRR adjusted: 1.58, 95 %CI: 1.30–1.92, per 10 % increase), and visible minority proportion (IRR adjusted: 1.09, 95 %CI: 1.05–1.12, per 10 % increase). Built environment features did not attenuate these associations. Conclusion This study provides evidence of social inequalities in child PMVC, suggesting a need to target traffic safety interventions towards the most socially marginalized areas.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".