Bibliographic record
Abstract
Planners do not seem to recognize the significance o f their role in facilitating active living for older adults. Active living is a way o f life that values and integrates physical activity into daily life. Most Canadians, and particularly older adults, are not active enough to obtain health benefits. With the number and proportion of older adults set to increase significantly in Canada over the coming decades, there is an urgent need for planners to help eliminate barriers to active living. This project uses qualitative research methods to explore planning's links to active living for older adults. Through interviews and a literature review, four broad areas o f current planning action are identified. These areas are: 1) research, policies and plans, 2) housing and neighbourhoods, 3) walking and cycling and 4) streets and plazas. Planners should create more active living opportunities in these areas as well as through inclusive processes and building design. The problems associated with sedentary lifestyles may be addressed by such efforts and by strengthening partnerships within the active living community. Additional research and evaluation of planning endeavours are also necessary. Planners concerned about healthy and sustainable communities must embrace their role in increasing the activity levels of older Canadians.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".