Can We Die? The Seriously Ill Need Clarity
Bibliographic record
Abstract
More than 2,000 people have died with the help of a doctor since Canada’s new medical assistance in dying law, Bill C-14, received royal assent on June 17, 2016.\nThis legislation has, however, come under sustained criticism for its ambiguity. When it was first introduced, concerns were immediately expressed about the eligibility criterion that “natural death has become reasonably foreseeable.”\nThis phrase “reasonably foreseeable” was deemed by many to be unfamiliar and unclear for physicians and their regulators. It has led to confusion and a variety of interpretations among providers and assessors of medical assistance in dying (MAiD).\nNow the Nova Scotia College of Physicians and Surgeons has developed a statement that clarifies this criterion. This will remove a barrier to access to MAiD for some seriously ill patients in the province — such as, for example, a dialysis-dependent patient who decides to stop dialysis.
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 | 0.025 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.032 |
| Scholarly communication | 0.011 | 0.023 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.027 | 0.052 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".