Bibliographic record
Abstract
This dissertation examines the factors that have the most significant impact on the pace of change in the primary care (PC) sector in Ontario. In Canada, there have been many attempts to improve the PC system through the introduction of a variety of primary care reform (PCR) models. Some say that there is insufficient movement in the PC sector and that it is in a policy gridlock. Others assert that substantial progress has been made and that transformational change is proceeding. \n\nThis dissertation demonstrates that PCR – the movement from PC to some form of primary health care (PHC) – is multi-dimensional and complex. It identifies the multiple dimensions of PHC and demonstrates that each dimension has implications for the structural relationships between the state and the medical association in the PC sector in Ontario. \n\nThe framework for this dissertation was derived from three bodies of literature: PC/PHC, neo-institutionalism and professional autonomy. The research design used involves qualitative and quantitative methods, including historical analysis, document analysis, key informant interviews and qualitative data. \n\nThe case study of PCR in Ontario demonstrates that while there have been some changes in the methods of physician payment and in the organization and delivery of PC, the majority of PCR models have not fundamentally altered the underlying institutional and structural relationships that characterize the sector. This includes the profession’s ability to control the political, economic and clinical aspects of care. Thus, the PCR models that propose the greatest amount of reform – those that alter structural relationships between the state and the medical association in a manner that results in a significant impact on the balance of power in the PC sector- are less likely to be adopted by physicians. This dissertation corroborates that the PCR models that have the greatest impact on professional autonomy are those that remain at the margins of the health care system, whereas the models that have little or no impact on autonomy have been more readily adopted.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.026 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".