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Record W2290920886 · doi:10.1080/15389588.2015.1116041

Dangerous student car drop-off behaviors and child pedestrian–motor vehicle collisions: An observational study

2016· article· en· W2290920886 on OpenAlexafffundabout
Linda Rothman, Andrew Howard, Ron Buliung, Colin Macarthur, Alison Macpherson

Bibliographic record

VenueTraffic Injury Prevention · 2016
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsUniversity of TorontoYork UniversityHospital for Sick ChildrenSickKids FoundationInstitute for Clinical Evaluative Sciences
FundersCanadian Institutes of Health ResearchDelaware Department of Transportation
KeywordsPedestrianRate ratioPoisson regressionConfidence intervalDemographyPoison controlInjury preventionDisadvantagePsychologySuicide preventionHuman factors and ergonomicsSpeed limitMultivariate analysisMedicineEngineeringEnvironmental healthTransport engineeringPopulationSociologyComputer science

Abstract

fetched live from OpenAlex

OBJECTIVES: The objective of this study was to examine the association between dangerous student car drop-off behaviors and historical child pedestrian-motor vehicle collisions (PMVCs) near elementary schools in Toronto, Canada. METHODS: Police-reported child PMVCs during school travel times from 2000 to 2011 were mapped within 200 m of 118 elementary schools. Observers measured dangerous student morning car drop-off behaviors and number of children walking to school during one day in 2011. A composite score of school social disadvantage was obtained from the Toronto District School Board. Built environment and traffic features were mapped and included as covariates. A multivariate Poisson regression was used to model the rates of PMVC/number of children walking and dangerous student car drop-off behaviors, adjusting for the built environment and social disadvantage. RESULTS: There were 45 child PMVCs, with 29 (64%) sustaining minor injuries resulting in emergency department visits. The mean collision rate was 2.9/10,000 children walking/year (SD = 6.7). Dangerous drop-off behaviors were observed in 104 schools (88%). In the multivariate analysis, each additional dangerous drop-off behavior was associated with a 45% increase in collision rates (incident rate ratio [IRR] = 1.45, 95% confidence interval [CI], 1.02, 2.07). Higher speed roads (IRR = 1.27, 95% CI, 1.13, 1.44) and social disadvantage (IRR = 2.99, 95% CI, 1.03, 8.68) were associated with higher collision rates. CONCLUSIONS: Dangerous student car drop-off behaviors were associated with historical nonfatal child PMVC rates during school travel times near schools. Some caution must be taken in interpreting these results due small number of events and limitations in the data collection, because collision data were collected historically over a 12-year period, whereas driving behavior was only observed on a single day in 2011. Targeted multifaceted intervention approaches related to the built environment, enforcement, and education could address dangerous drop-off behaviors near schools to reduce child PMVCs and promote safe walking to school.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.036
GPT teacher head0.304
Teacher spread0.268 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations24
Published2016
Admission routes3
Has abstractyes

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