Family physician views about primary care reform in Ontario: a postal questionnaire
Bibliographic record
Abstract
BACKGROUND: Primary care reform initiatives in Ontario are proceeding with little information about the views of practicing family physicians. METHODS: A postal questionnaire was sent to 1200 randomly selected family physicians in Ontario five months after the initial invitation to join the Ontario Family Health Network. It sought information about their practice characteristics, their intention to participate in the Network and their views about the organization and financing of primary care. RESULTS: The response rate was 50.3%. While many family physicians recognize the need for change in the delivery of primary care, the majority (72%) did not expect to join the Ontario Family Health Network by 2004, or by some later date (60%). Nor did they favour capitation or rostering, 2 key elements of the proposed reforms. Physicians who favour capitation were 5.5 times more likely to report that they expected to join the Network by 2004, although these practices comprise 5% of the sample. CONCLUSIONS: The results of this survey, conducted five months after the initial offering of primary care reform agreements to all Ontario physicians, suggest that an 80% enrollment target is unrealistic.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".