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Record W2891279429 · doi:10.1111/cag.12488

Children's perspectives on neighbourhood barriers and enablers to active school travel: A participatory mapping study

2018· article· en· W2891279429 on OpenAlexafffundvenue
Katherine Wilson, Stephanie E. Coen, Angela Piaskoski, Jason Gilliland

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsWestern University
FundersChildren's Health FoundationChildren's Health Research Institute
KeywordsPhotovoiceThematic analysisCitizen journalismFocus groupNeighbourhood (mathematics)Privilege (computing)Psychological interventionPsychologyParticipatory action researchPerceptionSociologyQualitative researchPedagogyPublic relationsMedical educationMedicinePolitical scienceSocial science

Abstract

fetched live from OpenAlex

Abstract Children today are spending more sedentary time indoors than time playing and being active outdoors. The daily journey to and from school represents a valuable opportunity for children to be physically active through active school travel. The majority of research on children's active school travel omits children from the research process even though children interpret their environments in fundamentally different ways than adults. Our research uses innovative participatory mapping and qualitative GIS methods to examine how children's perceptions of their environments influence their school journey experiences. Through our thematic analysis of 25 map‐based focus groups, we identified three main themes characterizing barriers and enablers to active school travel: safety‐related, material, and affective features. By positioning children as experts of their environments in our participatory methodology, our findings provide an important counterpoint to the adultist privilege characterizing the majority of research on children's active school travel. Environmental features that mattered for children's school journeys took on multiple meanings in their eyes, demonstrating that children's perspectives must be engaged to inform interventions to promote active school travel. We thus argue that identifying barriers and enablers to active school travel for children requires engaging children's views.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0030.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.247
Teacher spread0.232 · 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; both teacher heads agree on what is shown here.

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

Citations65
Published2018
Admission routes3
Has abstractyes

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