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Record W4381192809 · doi:10.1136/ip-2023-044922

Is higher school neighbourhood Walk Score associated with greater child pedestrian safety near schools?

2023· article· en· W4381192809 on OpenAlexaffabout
Linda Rothman, Brent Hagel, Andrew Howard, Naomi Schwartz, Marie Soleil Cloutier, Alison Macpherson

Bibliographic record

VenueInjury Prevention · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversity of TorontoToronto Metropolitan UniversityYork UniversityHospital for Sick ChildrenPublic Health OntarioUniversity of CalgaryToronto Public Health
Fundersnot available
KeywordsWalkabilityPedestrianNeighbourhood (mathematics)Poison controlTransport engineeringInjury preventionLevel designEnvironmental healthOccupational safety and healthHuman factors and ergonomicsBuilt environmentSuicide preventionPsychologyGeographyMedicineEngineeringComputer scienceMathematicsCivil engineering

Abstract

fetched live from OpenAlex

Walk Score is a common index used to estimate how suitable the built environment is for walking. Although Walk Score has been extensively validated as a measure of walkability and walking, there are limited studies examining whether commonly used constructs of walkability are associated with traffic safety in children. This study examined the association between Walk Score and child pedestrian injury controlling for observed walking exposure in school zones in Calgary, Toronto and Montreal, Canada. Results indicate that a higher Walk Score was associated with more child pedestrian injuries in all three cities, even after controlling for walking exposure. School travel planning should consider established individual pedestrian collision risk and individual factors rather than assuming a highly walkable environment is also a safe pedestrian environment.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.030
GPT teacher head0.306
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2023
Admission routes2
Has abstractyes

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