The relationship between walk score® and perceived walkability in ultrahigh density areas
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Walk Score® is a free web-based tool that provides a walkability score for any given location. A limited number of North American studies have found associations between Walk Score® and perceived built environment attributes, yet it remains unknown whether similar associations exist in Asian countries. The study's objective is to examine the covariate-adjusted correlations between the Walk Score® metric and measures of the perceived built environment in ultrahigh density areas of Japan. Cross-sectional data were obtained from a randomly selected sample of adult residents living in two Japanese urban localities. There was a large correlation between Walk Score® and access to shops (0.58; p < 0.001). There were medium correlations between Walk Score® and population density (0.38; p < 0.001), access to public transport (0.34; p < 0.001), presence of sidewalks (0.41; p < 0.001), and access to recreational facilities (0.37; p < 0.001), and there was a small correlation between Walk Score® and presence of bike lanes (0.16; p < 0.001). There was a small negative correlation between Walk Score® and traffic safety (-0.13; p < 0.001). There was a medium correlation between Walk Score® and overall perceived walkability (0.48; p < 0.001). This study's findings highlight that Walk Score® was correlated with several perceived walkable environment attributes in the context of ultrahigh density areas in Asia.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it