Creating walkable places: neighbourhood and municipal level perspectives on the socio‐political process in Ottawa, Canada
Bibliographic record
Abstract
As society faces concerns over rising obesity rates, traffic congestion and global warming, attention is turning to the importance of creating more walkable environments. The objective of this study was to investigate how community stakeholders, at both neighbourhood and municipal levels, describe the socio‐political process of creating walkable neighbourhoods. Thirty‐one key informants were interviewed about walking issues identified by older people in four different neighbourhoods in Ottawa, Canada. Five dimensions of the process were identified through qualitative analysis that elucidated insights on political context, access channels, resources, actors and opportunities. Creating walkable neighbourhoods is ultimately a political process that involves the convergence of resources facilitated by actors who are able to bridge sectors, organizations and levels of the system. Mobilization of resources at the neighbourhood level affected citizens' abilities to utilize access channels and act on opportunity raising considerations around equity. Future efforts to improve walkability will require that conventional bureaucracies develop approaches that are sensitive to place‐based needs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.045 | 0.011 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".