Bibliographic record
Abstract
BACKGROUND: Ethics training is required for all radiology residents in Canada, but this may be difficult to provide as radiology departments may not have radiologists with formal ethics training, and may not have access to educational resources focussed on teaching ethics to radiologists. We describe the implementation of a case-based approach to teaching and learning ethics, designed for Canadian radiologists. This approach can be adapted for use in other specialties through development of specialty-specific ethics case scenarios. METHODS: Ethics case study rounds specific to Canadian radiologic practice were presented at two different institutions, and using two different methods within one institution. In one method, we requested that the residents read the case study and questions ahead of time; in the other, the rounds were presented without any expectation of residents doing prior preparation. RESULTS: The participants, as a group, agreed with all seven survey statements describing the value of the experience. The opportunity to read the case ahead of time seemed helpful for some residents, but was not found to be overall more useful than discussing the case without prior review. Indeed, more than half of the resident participants in this group indicated that they did not make use of the advance materials at all. CONCLUSION: Resident feedback indicates that ethics case study rounds are a useful and valuable experience, especially when the case is specifically tailored to their medical practice. Prior preparation was not necessary for residents to benefit from these rounds.
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How this classification was reachedexpand
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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".