Bibliographic record
Abstract
Despite its mandate on minimizing harms in clinical trials, the Common Rule provides little guidance as to how IRBs should evaluate risk. The Common Rule and derivative commentaries tend to conceptualize risk review as an expert-based endeavor aimed at an objective and universal evaluation of possible harm; they also have tended to locate risk in the research activity itself rather than in the context of research. These views of risk conflict with scholarship showing that risk evaluations are socially determined even among experts, that the context of harms can influence how persons evaluate risks, and that forums that approach risk assessment as a technical endeavor bracket from discussion the numerous values that ground risk judgments. Possible reforms are proposed for clinical trial risk review that would render it more inclusive of the different types of risk encountered and more attuned to the priorities of trial subjects.
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 | 0.624 | 0.746 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.013 | 0.115 |
| Scholarly communication | 0.043 | 0.027 |
| Open science | 0.007 | 0.019 |
| Research integrity | 0.047 | 0.049 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier 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".