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State-of-the-art review: preventing child and youth pedestrian motor vehicle collisions: critical issues and future directions

2020· review· en· W3097476153 on OpenAlexafffund
Marie‐Soleil Cloutier, Émilie Beaulieu, Liraz Fridman, Alison Macpherson, Brent Hagel, Andrew Howard, Tony Churchill, Pamela Fuselli, Colin Macarthur, Linda Rothman

Bibliographic record

VenueInjury Prevention · 2020
Typereview
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsAlberta Children's HospitalUniversity of CalgaryInstitute for Clinical Evaluative SciencesToronto Metropolitan UniversitySickKids FoundationYork UniversityHospital for Sick ChildrenUniversité LavalParachuteCentre hospitalier universitaire de QuébecInstitut National de la Recherche Scientifique
FundersCanadian Institutes of Health Research
KeywordsPsycINFOPedestrianPoison controlInjury preventionHuman factors and ergonomicsOccupational safety and healthSuicide preventionScopusPsychological interventionMEDLINEEnvironmental healthForensic engineeringPsychologyMedicineTransport engineeringEngineeringPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

AIM: To undertake a comprehensive review of the best available evidence related to risk factors for child pedestrian motor vehicle collision (PMVC), as well as identification of established and emerging prevention strategies. METHODS: Articles on risk factors were identified through a search of English language publications listed in Medline, Embase, Transport, SafetyLit, Web of Science, CINHAL, Scopus and PsycINFO within the last 30 years (~1989 onwards). RESULTS: This state-of-the-art review uses the road safety Safe System approach as a new lens to examine three risk factor domains affecting child pedestrian safety (built environment, drivers and vehicles) and four cross-cutting critical issues (reliable collision and exposure data, evaluation of interventions, evidence-based policy and intersectoral collaboration). CONCLUSIONS: Research conducted over the past 30 years has reported extensively on child PMVC risk factors. The challenge facing us now is how to move these findings into action and intervene to reduce the child PMVC injury and fatality rates worldwide.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.016
GPT teacher head0.300
Teacher spread0.284 · 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 designOther design
Domainnot available
GenreReview

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

Citations62
Published2020
Admission routes2
Has abstractyes

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