How should palliative care respond to increasing legislation for assisted dying?
Bibliographic record
Abstract
How should palliative care respond to increasing legislation for assisted dying?Assisted dying is a contentious issue.Debates about it continue predominantly in the popular press, public discourse and within governments across the world.Assisted dying is the umbrella term that incorporates euthanasia and some forms of physician assisted dying.Euthanasia is where a doctor administers a lethal injection whereas in physician assisted dying the physician may be required to assess the patient as competent, terminally ill and provide a prescription for a lethal concoction that the patient self-administers.There is a changing picture in relation to legislation but broadly speaking euthanasia and physician assisted dying are legal in Belgium, the Netherlands, Luxemburg and most of Canada (except Quebec where they only legalised euthanasia).In various US states and Victoria in Australia some form of physician assisted death is legal.In Switzerland, legislation from the 1940's permits someone to assist in a death if they do not profit from it.When doctors assist, they are acting in this way almost as a civil act.Rates of euthanasia are increasing where it is legal, whereas rates of physician assisted dying tend to remain lower especially in countries where euthanasia is also legal (1,2).
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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 | 0.010 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.028 | 0.032 |
| Insufficient payload (model declined to judge) | 0.013 | 0.012 |
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".