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Record W2781658522

Understanding Parent and Child Perceptions of Barriers and Enablers Influencing Active School Travel

2017· article· en· W2781658522 on OpenAlexfundno aff
Katherine Wilson

Bibliographic record

VenueScholarship@Western (Western University) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
FundersChildren's Health FoundationChildren's Health Research Institute
KeywordsPerceptionPsychology
DOInot available

Abstract

fetched live from OpenAlex

Physical activity plays a fundamental role in developing and sustaining the health and well-being of children. Walking is the most common form of physical activity for people of all ages and the daily journey to and from school is a convenient opportunity for children to be physically active through the use of active school travel. This thesis uses a mixed methods approach, using: (a) parent and child surveys to examine how perceptions of barriers influence children’s active school travel; and (b) participatory mapping exercises and qualitative GIS to understand environmental influences on children’s journeys to and from school. Results suggest that parent and child perceptions of barriers vary greatly and are highly influenced by one’s individual environment. The overall aim of this research was to better understand features influencing children’s use of active school travel in order to improve interventions targeting increased physical activity. Findings from this thesis have implications for future research, urban planners, public health professionals, policy makers, educators, and parents.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.159
GPT teacher head0.346
Teacher spread0.186 · 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 designQualitative
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
Published2017
Admission routes1
Has abstractyes

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