Utilizing the determinants of healthy aging to guide the choice of social prescriptions for older adults
Bibliographic record
Abstract
Executive summary: The age of Canada's population is increasing, necessitating innovative methods and tools for assessing the needs of older adults and identifying effective health and social prescriptions. In Alberta, a community-based, senior-serving organization undertook the development and piloting of the Healthy Aging Asset Index, an assessment tool and social prescribing guide for use by a variety of professionals within the community. Tool development was rooted in medical complexity assessment and social work practice, and adhered to the determinants of healthy aging established by Alberta's Healthy Aging Framework, which is based on the determinants of healthy aging published by the World Health Organization. Results from the pilot showed improvement in the functionality of older adults within the determinants over time, as they were supported in addressing areas of personal vulnerability. Adopting tools such as the Healthy Aging Asset Index can bring cohesiveness to the support that older adults receive across the care continuum and has the potential to shift the balance of care away from the health system and towards the community, thus improving the capacity of health systems and government to meet the needs of Canada's older adults.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".