Report of the IOM Committee on Assessing the System for Protecting Human Research Participants
Bibliographic record
Abstract
In response to society's concerns about the use of human subjects in research, the Department of Health and Human Services commissioned the Institute of Medicine to perform a comprehensive assessment of current systems of research participant protection in the U.S., including recommendations for reform (Committee 2002). Although the committee declared its frustration over the lack of data, it found ample evidence to indicate that there are pivotal weaknesses in the current system. First, it discovered dissatisfaction with the current system from virtually every quarter and at virtually every level. Second, it found evidence that IRBs are under severe strain and performing inadequately. Third, it found that the existing regulatory framework—the IRB system and the Common Rule—has not and probably now cannot react adequately to the constantly evolving research environment. Some of these problems might be handled through federal agencies, but the committee holds that the problems are more extensive and will require additional institutional support and professional attention.
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 | 0.573 | 0.465 |
| Meta-epidemiology (narrow) | 0.003 | 0.005 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.024 | 0.010 |
| Open science | 0.022 | 0.016 |
| Research integrity | 0.055 | 0.041 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".