Primary Health Care in Canada: Systems in Motion
Bibliographic record
Abstract
CONTEXT: During the 1980s and 1990s, innovations in the organization, funding, and delivery of primary health care in Canada were at the periphery of the system rather than at its core. In the early 2000s, a new policy environment emerged. METHODS: This policy analysis examines primary health care reform efforts in Canada during the last decade, drawing on descriptive information from published and gray literature and from a series of semistructured interviews with informed observers of primary health care in Canada. FINDINGS: Primary health care in Canada has entered a period of potentially transformative change. Key initiatives include support for interprofessional primary health care teams, group practices and networks, patient enrollment with a primary care provider, financial incentives and blended-payment schemes, development of primary health care governance mechanisms, expansion of the primary health care provider pool, implementation of electronic medical records, and quality improvement training and support. CONCLUSIONS: Canada's experience suggests that primary health care transformation can be achieved voluntarily in a pluralistic system of private health care delivery, given strong government and professional leadership working in concert.
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.009 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".