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Record W1995281927 · doi:10.1080/17457300903308308

Are we there yet? Canada's progress towards achieving road safety vision 2010 for children travelling in vehicles

2009· article· en· W1995281927 on OpenAlexaffabout
Anne Snowdon, Abdul Hussein, Rebecca Purc-Stevenson, Beth S. Bruce, Carol Kolga, Paul Boase, Andrew Howard

Bibliographic record

VenueInternational Journal of Injury Control and Safety Promotion · 2009
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsHospital for Sick ChildrenDalhousie UniversityTransport CanadaSt. Clair CollegeUniversity of AlbertaUniversity of Windsor
Fundersnot available
KeywordsLegislationOccupational safety and healthSeat beltPoison controlInjury preventionSuicide preventionHuman factors and ergonomicsPsychological interventionChild safetyEnvironmental healthBooster (rocketry)Transport engineeringSocioeconomicsGeographyBusinessMedicineEngineeringPolitical scienceNursingEconomicsLaw

Abstract

fetched live from OpenAlex

This study examines safety seat use among Canadian children and evaluates child safety seat use relative to the national policy for child occupant safety, Road Safety Vision 2010. Using a probability sample, roadside observations of car safety seat use were collected from May to October of 2006 for 13,500 children aged from birth to 9 years in 10,084 vehicles at 182 sites in nine Canadian provinces and one territory. Observations revealed that 89.9% of Canadian children were restrained in some type of restraint. However, only 60.5% of these children were restrained in the correct safety seat. When comparing rates of correct use across provinces, results were not significantly different in provinces with booster seat legislation and those without this legislation. This data may be useful for healthcare practitioners and policy makers to develop interventions aimed at increasing appropriate car safety seat use for children in Canada.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.286
Teacher spread0.274 · 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

Citations30
Published2009
Admission routes2
Has abstractyes

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