Bibliographic record
Abstract
This paper describes an innovative curriculum in cross-cultural clinical ethics developed by faculty in the Health Ethics and Law program at one Canadian university. The pedagogical approach explicitly uses the notion of relativism in bioethics to encourage (rather than compromise) the use of a standard western bioethics framework for ethical decision-making. It offers an argument, at the intersection of medical anthropology and bioethics, for a pedagogy in ethics that encourages clinicians to challenge Euro-American constructs such as “autonomy” while simultaneously working within a principles-based framework for ethical decision-making. This approach is based on the premise that training in cross-cultural clinical ethics requires a “critical consciousness” approach to cross-cultural health care. Such an approach is enhanced by the use of cases that illustrate how the ideas and practices of medicine itself are culturally embedded and socially, economically, and politically constituted. A pedagogical approach to clinical ethics that works from within a critical consciousness framework encourages a critique of Euro-American based normative assumptions of bioethics while working within a principles-based framework for ethical decision-making. The curriculum features six key learning points taught through case-based discussion. The learning points emphasize culture in its relation to power and underscore the importance of viewing both biomedicine and bioethics as culturally constructed.
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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 | 0.058 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.013 | 0.010 |
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".