Disciplining Bioethics: Towards a Standard of Methodological Rigor in Bioethics Research
Bibliographic record
Abstract
Contemporary bioethics research is often described as multi- or interdisciplinary. Disciplines are characterized, in part, by their methods. Thus, when bioethics research draws on a variety of methods, it crosses disciplinary boundaries. Yet each discipline has its own standard of rigor--so when multiple disciplinary perspectives are considered, what constitutes rigor? This question has received inadequate attention, as there is considerable disagreement regarding the disciplinary status of bioethics. This disagreement has presented five challenges to bioethics research. Addressing them requires consideration of the main types of cross-disciplinary research, and consideration of proposals aiming to ensure rigor in bioethics research.
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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 | 0.724 | 0.696 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.015 | 0.146 |
| Scholarly communication | 0.057 | 0.061 |
| Open science | 0.014 | 0.037 |
| Research integrity | 0.028 | 0.041 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".