Bibliographic record
Abstract
Canada's population is aging, and the authors of this issue's lead article, Neena Chappell and Marcus Hollander, present a policy prescription for how to design a healthcare system that better responds to needs of older Canadians.The timing of this issue of Healthcare Papers is important: the first of the baby boomers turned 65 in January 2011.There is a pressing need to develop policies and implement sustainable reforms that will allow older adults to stay healthier and maintain their independence longer in their place of choice, while also creating efficiencies and quality improvements in our overall healthcare system that will benefit Canadians of all ages.Central to Chappell and Hollander's prescription is a shift away from our currently splintered system, toward an integrated system of care delivery.It is a prescription that calls for a wide range of health and supportive services for older adults, including care management, home care, home support services, supportive housing and residential care and hospital-based geriatric assessment units -all situated within a broader health and social services system, not a stand-alone continuing care system.This prescription, and the rich range of perspectives in the commentaries that follow, allows us to make several observations about how to get there from here.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.040 | 0.025 |
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".