Deploying the Precautionary Principle to Protect Vulnerable Populations in Canadian Post-Market Drug Surveillance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Drug regulatory bodies aim to ensure that patients have access to safe and effective drugs; however, no matter the quality of pre-licensure studies, uncertainty will remain regarding the safety and effectiveness of newly approved drugs until a large and diverse population uses those drugs. Recent analyses of Canada’s post-market drug surveillance (PMDS) system have found that Canada’s PMDS system requires strengthening and that efforts must be improved to monitor and address the safety and effectiveness of approved drugs among vulnerable populations. Given the uncertainty that exists when drugs enter the market, some have suggested that the precautionary principle is relevant to guiding decision-making in this context. This paper responds to recommendations that the Canadian PMDS system should be responsive to the health needs of vulnerable populations by assessing the utility of deploying the precautionary principle to guide a post-market strategy for vulnerable populations.
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.
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 | 0.020 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it