Is the 15-minute city within reach? Evaluating walking and cycling accessibility to grocery stores in Vancouver
Bibliographic record
Abstract
Leaders around the world have embraced the idea of a "15-minute city". This urban planning concept proposes a city where residents can meet their essential needs within a short walking or cycling trip from their home. Local access to grocery stores is a necessary component for cities to achieve the 15-minute city. This study aims to evaluate local accessibility to grocery stores by walking and cycling in the City of Vancouver. We used a cu-mulative opportunity measure to count the number of grocery stores available within a 15-minute walk and cycle from people's homes. To evaluate accessibility from the perspective of younger and older travellers, we considered different travel speeds. Our results show there is good accessibility to grocery stores when cycling, with less than 1% of the city's population not having a grocery store within a 15-minute cycle. When assuming a walking speed of an older pedestrian, around one-fifth of the population did not have access to a grocery store in their local area. The neighbourhoods that did not have a store within a 15-minute walk had higher proportions of children, older adults, and visible minorities, and lower rates of employment and post-secondary education attainment. In seeking to improve accessibility via walking and cycling, cities should prioritize grocery store locations and investments in pedestrian and cycling infrastructure to underserved neighbourhoods and populations.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".