IRBs and the Protection-Inclusion Dilemma: Finding a Balance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Institutional review boards, tasked with facilitating ethical research, are often pulled in competing directions. In what we call the protection-inclusion dilemma, we acknowledge the tensions IRBs face in aiming to both protect potential research participants from harm and include under-represented populations in research. In this manuscript, we examine the history of protectionism that has dominated research ethics oversight in the United States, as well as two responses to such protectionism: inclusion initiatives and critiques of the term vulnerability. We look at what we know about IRB decision-making in relation to protecting and including "vulnerable" groups in research and examine the lack of regulatory guidance related to this dilemma, which encourages protection over inclusion within IRB practice. Finally, we offer recommendations related to how IRBs might strike a better balance between inclusion and protection in research ethics oversight.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.007 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it