Bibliographic record
Abstract
With the aging of the population, the healthcare system needs to shift from the actual hospital-centred system developed in the past century for dealing with acute diseases and a young population toward a home-centred system, more appropriate for serving older people with chronic diseases. Funding of home care should not only be significantly increased but also be managed differently. We propose the introduction of an autonomy support benefit (ASB) to cover costs related to disabilities, irrespective of living environment, and to set up a public universal autonomy insurance program that will cover the ASB. This insurance should be at least partly capitalized to provide for the aging of the population and to ensure intergenerational equity. Also, since the home is a much more complicated service-delivery environment than the hospital, these services must be coordinated and integrated. The Program of Research to Integrate the Services for the Maintenance of Autonomy (PRISMA) is a coordination-type model of integration that was implemented and evaluated in three areas (one urban and two rural) in and around Sherbrooke, Quebec. A four-year longitudinal quasi-experimental study with over 1,500 participants demonstrated its efficiency in improving system effectiveness at no extra cost.
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 | 0.026 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".