Paediatric Physician–Researchers: Coping With Tensions in Dual Accountability
Bibliographic record
Abstract
Potential conflicts between the roles of physicians and researchers have been described at the theoretical level in the bioethics literature (Czoli, et al., 2011). Physicians and researchers are generally in mutually distinct roles, responsible for patients and participants respectively. With increasing emphasis on integration of research into clinical settings, however, the role divide is sometimes unclear. Consequently, physician–researchers must consider and negotiate salient ethical differences between clinical– and research–based obligations (Miller et al, 1998). This paper explores the subjective experiences and perspectives of 30 physician–researchers working in three Canadian paediatric settings. Drawing on qualitative interviews, it identifies ethical challenges and strategies used by physician–researchers in managing dual roles. It considers whether competing obligations could have both positive and adverse consequences for both physician–researchers and patients. Finally, we discuss how empirical work, which explores the perspectives of those engaged in research and clinical practice, can lead the way to understanding and promoting best practice.
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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 | 0.137 | 0.134 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.042 | 0.075 |
| Scholarly communication | 0.020 | 0.018 |
| Open science | 0.005 | 0.032 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".