Fragmentation of Care for Frail Older People— an International Problem. Experience from Three Countries: Israel, Canada, and the United States
Bibliographic record
Abstract
Cross-national comparisons of healthcare systems can help us to better understand them and to offer possible solutions for problems identified within these jurisdictions. Because multiple discontinuities present in most healthcare systems interfere with the appropriate clinical care of frail older people, we were interested in comparing the situation in three countries with markedly different healthcare systems. At one end of the spectrum we find Canada, with an almost fully socialized system. At the other stands the United States, where market forces are allowed the freest rein in any developed nation. Israel offers an intermediate model with elements held in common with both the U.S. and Canadian systems. Although the problems outlined in this paper can be addressed at the "micro" level, it is through an improvement in the structuring and organization of national systems of care that the appropriate conditions for the care of frail older people can be truly bettered. This international comparison offers insights for policy makers in these three states in particular and other countries in general.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".