Long-term care for the elderly in Canada: progress towards an integrated system
Bibliographic record
Abstract
Introduction Hospital and physician services for Canadians of all ages are shared responsibilities of the federal government and the governments of ten provinces and three territories. However, long-term care is regulated, funded and delivered only under the auspices of provincial/territorial governments with no major role for the federal government. Therefore, one cannot accurately refer to the ‘Canadian healthcare system’ as a singular entity. Rather healthcare, and long-term care, is delivered by thirteen different systems with national legislation guiding some, but not all, aspects of service delivery, regulation and administration (Beland and Shapiro, 1994). In addition, healthcare in Canada is provided by a mixture of public and privately funded services, and the balance between those sources of payment varies by region. The complexity of the Canadian healthcare mosaic has increased further with the introduction of regional authorities responsible for ‘local’ management of health services in the last two decades. Rather than provide an encyclopedic summary of the regulatory structure of healthcare for the elderly in all regions of Canada, this chapter will focus on the experience of the province of Ontario to illustrate the experience of the country’s most populous province. It is also the province with the most fully integrated health information system across the continuum of care for older people, which is intended to improve clinical practice, quality, public accountability and funding of health services. That said, one must remain aware that this overview represents a single province’s experience that shares much, but not all, in common with other regions of the country. The chapter begins with a brief overview of the three levels of government (federal, provincial, regional) that have an influence over healthcare in Canada. The remainder deals specifically with the continuum of care for the elderly in Ontario.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".