Understanding Sex Differences in Children’s Injury Risk as Pedestrians
Bibliographic record
Abstract
OBJECTIVE: Boys experience more injuries as pedestrians than girls. The aim of this study was to compare how boys and girls cross streets in order to identify factors that differentially influence their injury risk as pedestrians. METHODS: Using a fully immersive virtual reality (VR) system interfaced with a 3D movement measurement system, various measures of children's street-crossing behaviors were taken. RESULTS: At the start of the crossing, boys selected smaller (riskier) inter-vehicle gaps to cross into than girls. Subsequently, as they crossed, they showed greater attention to traffic, shorter start delay, and more evasive action than girls, which are strategies that could reduce risk as a pedestrian. Despite these efforts, however, boys experienced more hits and close calls than girls. CONCLUSION: To enhance their safety as pedestrians, girls adopt a proactive approach and select larger inter-vehicle gaps to cross into, whereas boys apply a reactive approach aimed at managing the risk created by having selected smaller (riskier) gaps. Girls' proactive approach yielded safer outcomes than boys' reactive strategy.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".