Multiple institutional rationalities in the regulation of health technologies: an ethnographic examination
Bibliographic record
Abstract
The regulation of risk associated with health technologies uses scientific evaluation to identify harms and protect citizens. However, in some cases scientific uncertainty has resulted in regulatory failures (e.g. Cox-2 inhibitors) and led regulators to explore new ways of working, such as bringing in the expertise of new actors (patient groups, community health workers, caregivers, etc.), to provide evidence and assessment in the regulation of risk. Implementing changes, however, can be an uncertain process in itself. Regulatory institutions are populated with actors representing a range of disciplinary perspectives, priorities, and values, which all influence their rationality towards accepting an introduced innovation. This paper provides an ethnographic exploration of disciplinary boundaries and multiple rationalities during a period of institutional transformation, within the Canadian Health Products and Food Branch. We interpret our findings through a multiple rationalities framework, illuminating the processes and practices of transformative risk regulation.
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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 | 0.019 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.014 | 0.030 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".