Bibliographic record
Abstract
A new report has urged Canada's federal government to do more to curb attempts by pharmaceutical companies to influence the conduct and publication of clinical studies carried out by researchers into their products. The report, commissioned by the Canadian Association of University Teachers, follows a four year dispute at the Toronto Hospital for Sick Children, centring on attempts by a drug company to prevent publication of results of a trial that were unfavourable in relation to one of its products. The dispute began after researcher Dr Nancy Olivieri decided to break a confidentiality agreement with Apotex, a Toronto based pharmaceutical company that was sponsoring her research. She published results critical of the drug deferiprone, which she was testing in young patients with thalassaemia, in the New England Journal of Medicine (1998;339:417-23). Dr Olivieri, former head of the hospital's haemoglobinopathy programme, was threatened with legal action by Apotex and also removed from her hospital post, though she …
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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 | 0.054 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.053 | 0.037 |
| Insufficient payload (model declined to judge) | 0.031 | 0.017 |
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".