Exploring the role of the outdoor built environment for aging in place: A look into the False Creek South neighbourhood
Bibliographic record
Abstract
Population aging and urbanization calls for urban planners to take a closer look at age-friendly plans and policies to support aging in place.Research shows that most older adults prefer to "age in place", continuing to live in their own home or neighbourhood for as long as possible.This study explores the outdoor built environment of an urban neighbourhood in the City of Vancouver, identifying aspects perceived as barriers and facilitators for aging in place.Data were collected using semistructured interviews with 11 older adults and four key informants, supplemented by photographs and journal entries from the older adults.Data were analyzed using inductive and deductive thematic analysis.Findings show that older adults and key informants agree objective features such as smooth sidewalks, curb ramps, the proximity of green spaces, availability of benches, public washrooms, and street lighting facilitate aging in place.Key informants reported distance to amenities and poor transportation service as barriers.Older adults positively reported on the therapeutic and social aspects of the built environment such as forest walks and meeting places for social interaction as important facilitators for aging in place.To address the issues of population aging and urbanization, this thesis suggests that urban planners need to prioritize age-friendly policies that promote mobility and well-being in neighbourhood planning programs, and further develop age-friendly built environments for aging in place.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".