(Re)defining legitimacy in Canadian drug assessment policy? Comparing ideas over time
Bibliographic record
Abstract
How do experts judge the legitimacy of technical policy processes, and do their ideas change as these processes are opened to other stakeholders and the public? This research examines the adoption of public and patient involvement in pharmaceutical assessment in Canada. It finds tensions between scientific legitimacy that prioritizes rigor and objectivity, and democratic legitimacy that values inclusion and a broader range of evidence. In response to policy change, experts incorporate new ideas about democratic inputs and processes, while maintaining scientific policy goals. The research responds to calls for more precise measurement of ideas and ideational change and more evaluation of public and patient involvement in health policy. It helps us understand the significance of, and limits to, ideational change among experts in health policy domains that are highly technical and publicly salient. Understanding the way democratic and scientific legitimacy are negotiated in policy decisions has a wide applicability in health, but is particularly relevant during a global pandemic when evidence is being generated rapidly, decisions must be made quickly, and these decisions have a significant, immediate effect on the lives of all citizens.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".