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Record W7071296382

School travel planning: A Canadian pilot evaluation

2015· article· en· W7071296382 on OpenAlexaffabout

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsAction planIntervention (counseling)Plan (archaeology)Pilot programAction (physics)Program evaluationData collectionTravel time
DOInot available

Abstract

fetched live from OpenAlex

Background:Active school transport (AST) may be an important source of children's physical activity (PA). 'School Travel Plans' (STP) may increase AST by addressing school specific concerns such as road safety and traffic. Purpose:The purpose of this pilot study was to determine the potential impact of school travel planning (STP) for increasing AST in Canada.Methods: A pilot School Travel Planning (STP) intervention was conducted at twelve schools in four Canadian provinces. STP Facilitators worked with the schools to create and implement an action plan encouraging active transportation choices at each school. The intervention was evaluated using parental self-report (n=1520).Results: Thirteen per cent of families reported that they drove less to/from school because of the Travel Plan implementation. Thirty-seven percent of children walked to school and 43% from school to home. Distance and convenience were the primary reasons given for continued driving. Conclusions:While data provides tentative support for the STP process in Canada, it is critical that future STP initiatives explicitly address parental convenience and time constraints as barriers to greater AST.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.056
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0050.002
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.192
GPT teacher head0.388
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2015
Admission routes2
Has abstractyes

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