Bibliographic record
Abstract
Medically assisted dying is increasingly garnering global support, now permitted in thirteen countries and being considered in several more. This growing legalization has occurred largely in Western and European countries, a reflection of its impetus in societal factors such as an increasing emphasis on individual autonomy, secularism, consumerism and patient empowerment in these more individualistic or less collectivist cultures. Although the drive for assisted dying has not primarily come from medicine, physicians have been invoked as the gatekeepers. This has created personal distress for some clinicians and professional challenges for some disciplines such as palliative care. Yet, the majority of those who pursue assisted dying do receive palliative care services and there has been little global evidence of assisted dying being disproportionately provided to unwilling or vulnerable populations. The fact is that despite the availability of adequate palliative care, a small minority of patients will still want medically assisted dying. Assisted deaths have also been associated with better family bereavement outcomes than deaths due to other causes. Medically assisted dying accounts for less than 5% of deaths as compared to the suicide rate of only 0.03% in palliative care, suggesting that the desire for assisted death is distinct from suicide. Contrary to popular belief, unbearable pain or physical suffering is not the main reason patients request medically assisted dying at the end of life. Psychological factors are the most common reasons, including the loss of autonomy and the desire for control. It is often unclear if a psychosocial intervention would be clinically indicated or effective in altering a capable patient’s wishes. The paramount clinical responsibility in ensuring that MAiD is delivered safely and ethically is differentiating the desire for death as an indicator of pathology from a rational choice undertaken by a capable patient. This presentation will use case examples to illustrate that this is indeed possible to do, and in some cases, a medically assisted death may be the only and most patient-centered way to relieve end of life suffering. In this new clinical practice of medically assisted dying, medicine must now rise to the obligation to balance the concurrent duties of beneficence through respecting the autonomy of capable patients and nonmaleficence by protecting vulnerable patients.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.097 | 0.025 |
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".