Bibliographic record
Abstract
Clinical trials present an ethical dilemma for pharmaceutical companies. While companies may want to undertake and report these trials in an ethical manner, negative results can significantly affect product sales. There is accumulating evidence that company-financed trials are biased in favor of the product that the company makes. Ethical conduct in this article is defined as whether the trials are conducted in the best interests of the participants and/or reported in the best interests of patients. Nine examples of how clinical trials are violating multiple articles in the Declaration of Helsinki are discussed using concrete case reports from the literature. The recognition of ethical problems in company run trials is not something new, but to date no meaningful action has been taken to resolve this issue. What is necessary is to separate the financing of clinical trials from their conduct.
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 | 0.280 | 0.488 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.115 |
| Scholarly communication | 0.022 | 0.033 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.036 | 0.050 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".