A Comparative Study of the Law of Palliative Care and End-of-Life Treatment
Bibliographic record
Abstract
Since the Supreme Court of New Jersey decided the Quinlan case a quarter of a century ago, three American Supreme Court decisions and a host of state appellate decisions have addressed end-of-life issues. These decisions, as well as legislation addressing the same issues, have prompted a torrent of law journal articles analyzing every aspect of end-of-life law. In recent years, moreover, a number of law review articles, many published in this journal, have also specifically addressed legal issues raised by palliative care. Much less is known in the United States, however, as to how other countries address these issues. Reflection on the experience and analysis of other nations may give Americans a better understanding of their own experience, as well as suggest improvements to their present way of dealing with the difficult problems in this area. This article offers a conceptual and comparative analysis of major legal issues relating to end-of-life treatment and to the treatment of pain in a number of countries. In particular, it focuses on the law of Australia, Canada, the United Kingdom, Poland, France, the Netherlands, Germany, and Japan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".