COMMUNITY ENGAGED MODELS TO ENHANCE PHYSICAL AND SOCIAL DIMENSIONS OF HEALTH IN OLDER ADULTS
Bibliographic record
Abstract
In Canada, older adults will soon outnumber children, and there will be a greater increase in the proportion of adults over age 80 than any other age group. Maintaining one’s mobility is considered the best guarantee of older adults being able to cope and remain in their homes and communities. There is clear evidence that neighbourhoods, communities and social networks where older adults live, directly affect their mobility and health. In this panel presentation, we draw on our community based research across four interconnected programs of inquiry to 1: highlight the need to move beyond the ‘instrumental/functional’ understanding of mobility to explore what conveys meaning for older people, particularly in public urban environments; 2: describe the physical activity implications of a newly developed Greenway among older adults living in a highly walkable urban environment; 3: emphasize the importance of evaluating implementation of a physical activity intervention delivered at-scale across BC, and 4: describe the impact of a scaled-up physical activity intervention on dimensions of older adults’ physical and social health.This session will be of particular interest to those who work with an aging population and social and urban planners who work across the age spectrum to design inclusive communities for people of all abilities. To animate our discussion we will use a series of short (2–3 minute) video vignettes (produced by our team) to foreground the voices and experiences of older adults.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".