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Record W4388152987 · doi:10.1016/j.pmedr.2023.102489

Associations between school-level environment and individual-level factors of walking and cycling to school in Canadian youth

2023· article· en· W4388152987 on OpenAlexafffundabout
Valérie Lavergne, Gregory Butler, Stéphanie A. Prince, Gisèle Contreras

Bibliographic record

VenuePreventive Medicine Reports · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of OttawaPublic Health Agency of Canada
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsWalkabilityNeighbourhood (mathematics)CyclingSocioeconomic statusLevel designPsychologyPhysical activityGerontologyEnvironmental healthDemographyGeographyMedicineSociologyPhysical therapyPopulation

Abstract

fetched live from OpenAlex

Identifying individual-level and school-level correlates of walking and cycling to school remains a public health priority as only one in four Canadian youth actively travels to school. This study aimed to estimate the prevalence of Canadian youth in grades 6 to 10 who walk, cycle, or use motorised transport to go to school, and to examine if school neighbourhood walkability, neighbourhood-level and individual-level correlates are associated with mode of transportation to school. Data come from the 2017/2018 Health Behaviour in School-aged Children study. The walkability of the schools' neighbourhood was measured using the Canadian Active Living Environments (Can-ALE) index. We observed that only 22.4% and 4.2% of youth walked and cycled to school, respectively. Most (73.4%) used motorised transport to school, including 53.2% of youth who lived less than 5 minutes from school. Schools located in neighbourhoods with higher Can-ALE classes (i.e., higher walkability) were positively associated with walking to school. No statistically significant association between school walkability and cycling to school was observed. Individual-level socioeconomic status (SES) was associated with walking, but not cycling, to school. Conversely, neighbourhood-level SES was associated with cycling, but not with walking, to school. Correlates of walking to school differed from those for cycling to school, suggesting that different approaches to promoting active transportation are needed.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.078
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
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 head0.105
GPT teacher head0.332
Teacher spread0.228 · 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

Citations5
Published2023
Admission routes3
Has abstractyes

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