An Evidence-Based Policy Prescription for an Aging Population
Bibliographic record
Abstract
In this paper, the authors provide a policy prescription for Canada's aging population. They question the appropriateness of predictions about the lack of sustainability of our healthcare system. The authors note that aging per se will only have a modest impact on future healthcare costs, and that other factors such as increased medical interventions, changes in technology and increases in overall service use will be the main cost drivers. They argue that, to increase value for money, government should validate, as a priority, integrated systems of care delivery for older adults and recognize such systems as a major component of Canada's healthcare system, along with hospitals, primary care and public/population health. They also note a range of mechanisms to enhance such systems going forward. The authors present data and policy commentary on the following topics: ageism, healthy communities, prevention, unpaid caregivers and integrated systems of care delivery.
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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 | 0.100 | 0.286 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.018 | 0.014 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.063 | 0.051 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".