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Record W636224762

Is It Safe? How Does Safety Play a Role in a Child’s Mode of Travel Between Home and School?

2012· article· en· W636224762 on OpenAlexaboutno aff
Kristian Larsen, Ron Buliung, Guy Faulkner, Caroline Fusco

Bibliographic record

VenueTransportation Research Board 91st Annual MeetingTransportation Research Board · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisPopulationPsychologySafety behaviorsHuman factors and ergonomicsPoison controlApplied psychologySocial psychologyQualitative researchEnvironmental healthSociologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

This study examined how both personal and traffic safety influenced a child’s mode of travel to/from school and how these concerns varied by population, built and social environment. Semi-structured interviews were conducted (n=37) with parents and their children at four schools of contrasting built and social environments within the City of Toronto. Thematic analysis of the interview transcripts was conducted. Comparative analyses of the data were explored by the environment (built and social), population (parent and child) and mode of travel. Personal safety concerns such as ‘stranger danger,’ bullies and dogs, along with traffic safety at street crossings and around the school emerged as the primary concerns for parents and children. It is difficult to alleviate parental fears of strangers, although they do decrease as the child gets older. For children, traveling in groups and ensuring dogs are on leashes can reduce personal safety fears. Personal safety was more of a concern in low income neighborhoods, whereas traffic safety was much more prevalent of an issue in inner-suburban areas. Furthermore, traffic concerns were more of an issue for non-active travellers. The findings of this research give evidence that mode choice is associated with safety and these concerns vary by environment, population and mode of travel.

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)0.012
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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 score0.080
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.056
GPT teacher head0.396
Teacher spread0.340 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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