Bioethics for clinicians: 18. Aboriginal cultures.
Bibliographic record
Abstract
Although philosophies and practices analogous to bioethics exist in Aboriginal cultures, the terms and categorical distinctions of "ethics" and "bioethics" do not generally exist. In this article we address ethical values appropriate to Aboriginal patients, rather than a preconceived "Aboriginal bioethic." Aboriginal beliefs are rooted in the context of oral history and culture. For Aboriginal people, decision-making is best understood as a process and not as the correct interpretation of a unified code. Aboriginal cultures differ from religious and cultural groups that draw on Scripture and textual foundations for their ethical beliefs and practices. Aboriginal ethical values generally emphasize holism, pluralism, autonomy, community- or family-based decision-making, and the maintenance of quality of life rather than the exclusive pursuit of a cure. Most Aboriginal belief systems also emphasize achieving balance and wellness within the domains of human life (mental, physical, emotional and spiritual). Although these bioethical tenets are important to understand and apply, examining specific applications in detail is not as useful as developing a more generalized understanding of how to approach ethical decision-making with Aboriginal people. Aboriginal ethical decisions are often situational and highly dependent on the values of the individual within the context of his or her family and community.
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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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.032 | 0.019 |
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".