The relationship between cluster-analysis derived walkability and local recreational and transportation walking among Canadian adults
Bibliographic record
Abstract
We investigated the association between objectively-assessed neighborhood walkability and local walking among adults. Two independent random cross-sectional samples of Calgary (Canada) residents were recruited. Neighborhood-based walking, attitude towards walking, neighborhood self-selection, and socio-demographic characteristics were captured. Built environmental attributes underwent a two-staged cluster analysis which identified three neighborhood types (HW: high walkable; MW: medium walkable; LW: low walkable). Adjusting for all other characteristics, MW (OR 1.40, p < 0.05) and HW (OR 1.34, approached p < 0.05) neighborhood residents were more likely than LW neighborhood residents to participate in neighborhood-based transportation walking. HW neighborhood residents spent 30-min/wk more on neighborhood-based transportation walking than both LW and MW neighborhood residents. MW neighborhood residents spent 14-min/wk more on neighborhood-based recreational walking than LW neighborhood residents. Neighborhoods with a highly connected pedestrian network, large mix of businesses, high population density, high access to sidewalks and pathways, and many bus stops support local walking.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".