Ethics education for clinician–researchers in genetics: The combined approach
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
Advancements in genomic technology and genetic research have uncovered new and unforeseen ethical and legal issues that must now be faced by clinician-researchers. However, lack of adequate ethical training places clinician-researchers in a position where they might be unable to effectively assess and resolve the issues presented to them. The literature demonstrates that ethics education is relevant and engaging where it is targeted to the level and context of the learners, and it includes real-world based cases approached in innovative ways. In order to test the feasibility of a combined approach to ethics education, a conference was held in 2012 to raise awareness and familiarize participants with the ethical and legal issues surrounding medical technology in genetics and then to have them apply this to reality-based case studies. The conference included participants from a variety of backgrounds and was divided into three sections: (i) informative presentations by experts in the field; (ii) mock REB deliberations; and (iii) a second mock-REB, conducted by a panel of experts. Feedback from participants was positive and indicated that they felt the learning objectives had been met and that the material was presented in a clear and organized fashion. Although only an example of the combined approach in a particular setting, the success of this conference suggests that combining small group learning, practical cases, role-play and interdisciplinary learning provides a positive experience and is an effective approach to ethics education.
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 | 0.026 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.016 |
| 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