Conflicting interests: Critiquing the place of “institutional reputation” in research ethics reviews
Bibliographic record
Abstract
Going through Research Ethics Boards (REB) and being held accountable to the highest ethical standards to conduct research with human subjects is commonplace. The goal of such a process helps ensure the selection and achievements not only of morally acceptable ends, but also of acceptable means to those ends when conducting research. Ultimately, REBs must pass judgment about the acceptability of harms and benefi ts to participants as they relate to research processes and outcomes. In this paper, we explore the implication of integrating “institutional reputation” as a category of analysis in the ethical review process. Informed by a recent Research Ethics Board (REB) review, we seek to engage with the readership in a constructive refl ection on the concept of institutional reputation as a source of confl icting interests in research ethics review process.
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 | 0.654 | 0.827 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.015 | 0.087 |
| Scholarly communication | 0.035 | 0.031 |
| Open science | 0.010 | 0.020 |
| Research integrity | 0.038 | 0.042 |
| 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".