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Predictors of Parental Risk Perceptions: The Case of Child Pedestrian Injuries in School Context

2010· article· en· W1509020103 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRisk Analysis · 2010
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsUniversité de MontréalInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsBivariate analysisContext (archaeology)PedestrianPerceptionPoison controlRisk perceptionInjury preventionHuman factors and ergonomicsPsychologySuicide preventionOccupational safety and healthTransport engineeringEnvironmental healthApplied psychologySocial psychologyMedicineEngineeringGeographyMathematicsStatistics

Abstract

fetched live from OpenAlex

The objective of this article is to explore the factors that influence parental risk perceptions of child pedestrian injuries in the elementary school context. Parents (n=193) from six different schools responded to a questionnaire on road safety, including a measure of their risk perception. Results of bivariate analyses show that eight variables are significantly related to risk perception. Environmental variables, as we measure them, were not significant, contrary to our initial hypotheses. Only three variables, parent's gender, perceived primary source of danger, and sense of control remained significant in OLS regression analyses (adjusted R(2) of 0.16, F=9.27; p=0.00). Since parents' perceptions of road risks are an important factor in their road safety practices and in their choice of transportation mode used for their child's journey to school, our analysis elucidates factors underlying these choices. Our results can help decisionmakers to design traffic injury prevention measures and to promote physical activity through the use of active modes of transport.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.003
GPT teacher head0.210
Teacher spread0.206 · 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