Uncover Children’s Perceptions and Use of Neighborhood Environments.”
Bibliographic record
Abstract
This pilot study tested a child-guided protocol integrating qualitative field techniques with spatial analysis tools to explore children's neighborhood perceptions and use. Sixteen children aged 7-9 in London, Canada led researchers and city planners on guided walks of their school neighborhood to document and discuss places of significance to them. Children were equipped with digital cameras and maps to record neighborhood features, while adult facilitators recorded the ongoing dialogue and tracked the routes taken with GPS units. Children's photographs from the walks supported a group photo-elicitation exercise that further probed and clarified the children's community perspectives. Location data from the GPS and narratives allowed for the analysis of children's comments and photographs within a geographic information system (GIS). Thematic and spatial analysis of narratives and photographs revealed significant but complex patterns of neighborhood perception and use, suggesting that this child-led protocol is an effective tool for engaging children in community assessment and for revealing their local lived experience.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".