Bibliographic record
Abstract
This book began with a series of questions about the difficulties in reforming health care in Canada.The underlying assumption about the meagre extent of reform was confirmed in each of the four policy domains we studied.To shed light on why this was so, we undertook several kinds of comparisons: by factor (or influence), by issue, by phase, by direction (consensus or counter-consensus reform), by province, and by technical complexity.As expected, the paucity of reform was due mainly to the resistance of those actors in each of the four domains who benefited most from the status quo.These actors had the political clout to hang on to the turf they occupied or, where they could not, they generally were able to steer the direction of the reform process to a destination that was acceptable to the interests they represented and at a pace that minimized the disruption to those interests.The comparative analysis suggested several patterns in the decision process.One was in the factors associated with the different policy reform domains.Elites dominated the governance arrangements and financial arrangements domains.Indeed, on some issues in that grouping, the public and media were scarcely aware that there were important reform matters to be decided.When it came to the delivery arrangements and policy content domains, however, public opinion and civil society groups purporting to speak for large sectors of the public played a significant role.There was also a pattern in the factors associated with the different phases of reform.The media, civil society groups, and the public were key actors in causing issues in the delivery arrangements and policy content domains to reach the governmental agenda.They had less influence on policy choice in this grouping and on issues that had substantial technical content.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".