Bibliographic record
Abstract
Medical assistance in dying (MAiD) became legal in Canada in June 2016. Since that time, many health-care practitioners and health-care institutions have undertaken to provide it, and thousands of Canadians have taken advantage of it. At the same time, a significant number of both practitioners and institutions have refused provision of MAiD for various reasons, including conscience-based objections to it. In this article, I argue that refusal by practitioners could, and should, be tolerated but only where it could be accommodated in practice groups without unduly burdening willing providers or adversely affecting patient access. My conclusion about refusal by institutions is less compromising. In this case, the cost to vulnerable patients of MAiD being delayed or denied is much greater and the burdens of conscience (if we may call them that) to institutions are insignificant. Since it cannot be accommodated without seriously impairing both patient access and patient well-being, refusal by publicly funded health-care institutions to offer MAiD must be completely disallowed.
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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.020 | 0.029 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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".