Bibliographic record
Abstract
In the arena of pharmaceutical drug regulation, transparency is the favoured focus of many current policy initiatives. Transparency is predominantly understood in terms of information disclosure. Requirements to register clinical trials, publish summary results, share clinical trial data, and disclose physician-industry relationships as well as rationales behind regulatory decision making are each predicated upon this idea that imparting information will both inform and deter unwanted behaviours. In this paper, I argue that understanding transparency qua disclosure has clear limitations and suggest transparency can and should serve an additional function - namely, of enabling standard setting through a more participatory, public model of drug regulation. I turn to the history of Canadian drug regulation to demonstrate that such an alternative conception of transparency - transparency qua standard construction - is in fact possible. I document the regulator's extensive use of publicity practices to develop standards for assessing drug adulteration through the early years of Canadian drug regulation, from 1887 to 1920 when hundreds of analytical bulletins were publicly disseminated. I also show how, from the 1920s onwards, this participatory, public transparency transmogrified into a form of closed, insider transparency as the regulator constituted a collaborative relationship with industry. Given this shift, I suggest that an alternative conception of transparency is not only possible but also increasingly needed, and then begin to sketch how tying transparency to a revitalized concept of fraud in drug research and development might activate that participatory, public regulatory work.
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 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 | 0.059 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.061 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".