Bibliographic record
Abstract
Proposed changes to the Common Rule are proffered to save almost 7,000 reviews annually and consequently vast amounts of investigator and IRB-member time. However, the proposed changes have been subject to criticism. While some have lauded the changes as being imperfect, but nevertheless as improvements, others have contended that ‘neither the scientific community nor the public can be confident that improved practices will emerge from the regulatory changes mandated by the NPRM.’ In the present article, I discuss an important aspect that has been overlooked: the question of whether benefits will emerge is demonstrably empirical, yet data upon which to draw conclusions are conspicuous by their absence. This is thrown into sharp relief when we consider the current environment in which health research is increasingly focused on providing evidence of need or benefit, where there is greater emphasis on evidence-based practice, and when we have the nascent field of implementation science.
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 | 0.621 | 0.831 |
| Meta-epidemiology (narrow) | 0.005 | 0.008 |
| Meta-epidemiology (broad) | 0.013 | 0.027 |
| Bibliometrics | 0.017 | 0.010 |
| Science and technology studies | 0.014 | 0.069 |
| Scholarly communication | 0.038 | 0.054 |
| Open science | 0.038 | 0.034 |
| Research integrity | 0.173 | 0.176 |
| Insufficient payload (model declined to judge) | 0.005 | 0.008 |
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".