Canadian policy perspectives on promoting physical activity across age-friendly communities: lessons for advocacy and action
Bibliographic record
Abstract
ABSTRACT Population ageing combined with physical inactivity has critical implications for the public health of communities in the twenty-first century. In the last decade, the World Health Organization launched the age-friendly cities agenda, aiming to address population ageing through whole-systems, rights-based, health equity-focused approaches. An important intervention for age-friendly communities is modifying built environments to support population-level physical activity. Physical activity can help mitigate impacts of chronic diseases and social isolation on older adults. Need for advocacy and action in this area raises questions of how to develop supportive environments for physical activity across age-friendly community types. In Canada, a substantial proportion of older adults live outside large urban municipalities, for which scant research exists on fostering age-friendly built environments. To this end, we conducted qualitative research involving semi-structured interviews with 21 municipal policy influencers in Alberta, Canada to gather perspectives on development and early implementation of an age-friendly policy framework in the small urban and rural context. Our findings are organised by three main themes providing key lessons for advocacy and action, namelypursuing comprehensive planning,promoting public engagementandprioritising the needs of older adults. This research informs advocacy and action priorities in promoting built environment modification for routine physical activity as part of an age-friendliness agenda for small urban and rural regions of Canada and other countries.
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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 | 0.020 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.033 | 0.021 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 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".