What the clinician taught the ethicist: clinical contributions to ethical concerns.
Bibliographic record
Abstract
BACKGROUND: Clinical ethics is often assumed to be a one-way relationship in which ethicists consider the appropriate guidelines for clinical practice and research. This unfortunately ignores the important ways clinical practice informs bioethical thinking. MATERIAL/METHODS: This paper considers the relation between clinical and ethical practice through a consideration of whether there are conditions in which Physician Assisted Suicide, or other forms of euthanasia, serve as an ethically accepted response to chronic illness. At one scale it reviews publicly available data on deaths attributed to euthanasia practitioner Jack Kevorkian to consider the medical rationale of those deaths. At another scale, the 'mercy killing' by Canadian farmer Robert Latimer of his daughter is employed as a case study of surrogate decision making. RESULTS: A clinical review of the more than seventy cases attributed to Jack Kevorkian from 1990-98 reveals a client base that did not fit publicly or clinically accepted parameters within which euthanasia is generally understood. Few if any of the patients were near the end stage of a chronic progressive disease. Most were able to travel independently. Palliative care was in some cases problematic. The case of Latimer emphasizes the importance of social as well as medical care in cases of chronic illness, and the importance of palliative care as an alternative to CONCLUSIONS: Clinical ethics is of necessity a two-way street, one in which ethical paradigms influence practitioners and researchers whose expertise, in turn, necessarily educates the non-clinical ethicist.
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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 | 0.020 | 0.094 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.025 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".