Institutional conflict of interest: attempting to crack the deferiprone mystery
Bibliographic record
Abstract
A recent study by Olivieri et al , published in PLOS ONE , reports that between 2009 and 2015 a third of patients with thalassaemia in Canada’s largest hospital were switched from first-line licensed drugs to regimens of deferiprone, an unlicensed drug of unproven safety and efficacy. Based on retrospective data from patient records, the PLOS Study reports that patients treated with deferiprone, either as monotherapy or in combination with first-line drugs, suffered serious (and often irreversible) adverse effects. The data reported by Olivieri et al give rise to a number of ethical issues. These ethical issues are identified, placed in historical context and analysed. For purposes of this analysis, reliance is placed on two core principles of research ethics, harm minimisation and informed consent, and also on the hospital’s mission statement. Then a mystery is explored: How and why did it happen that Toronto’s University Health Network treated large numbers of patients with an unlicensed drug over a period of many years? ‘Institutional conflict of interest’ is considered as a possible explanatory hypothesis.
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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.014 |
| 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; both teacher heads agree on what is shown here.
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".