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Record W2919151056 · doi:10.1177/0739456x19828444

Examining the Social and Built Environment Factors Influencing Children’s Independent Use of Their Neighborhoods and the Experience of Local Settings as Child-Friendly

2019· article· en· W2919151056 on OpenAlexafffundabout
Janet Loebach, Jason Gilliland

Bibliographic record

VenueJournal of Planning Education and Research · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsWestern University
FundersChildren’s Health FoundationCanadian Institutes of Health ResearchSocial Sciences and Humanities Research Council of CanadaChildren's Health Research InstituteHeart and Stroke Foundation of Canada
KeywordsAffordanceDestinationsPsychologyPerceptionGeographyTourism

Abstract

fetched live from OpenAlex

Neighborhoods have traditionally served as important settings for children’s independent activities, but use has declined dramatically. Global positioning system (GPS) monitors, activity diaries, annotated maps, and Google Earth–enabled interviews captured the neighborhood perceptions, usage, and independent activity ranges of twenty-three children (nine to twelve years) from London, Canada. While few participants used neighborhood settings on a habitual basis, local parks and homes of nearby friends were important independent destinations. Usage was strongly influenced by positive and negative social conditions, but local environments did not generally cater well to the shifting interests of resident children. Embedding child-friendly affordances through neighborhood planning may improve children’s experience and independent use of local settings.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.328
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.076
GPT teacher head0.393
Teacher spread0.317 · 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

Citations36
Published2019
Admission routes3
Has abstractyes

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