The realities of Medical Assistance in Dying in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In 2015, the Canadian Supreme Court declared that an absolute Criminal Code prohibition on assisted suicide and euthanasia was unconstitutional. In response, the Canadian parliament enacted Bill C-14 in 2016 permitting assisted suicide and euthanasia for the end-of-life context, which it termed “Medical Assistance in Dying” (MAiD). In 2021, Bill C-7 expanded eligibility for MAiD to those with disabilities not approaching their natural death. By 2021, MAiD accounted for 3.3% of all deaths in Canada with some areas of Canada presently reporting MAiD death rates upward of 7%. In 2021, Canada had 10,064 deaths by MAiD, surpassing all jurisdictions for yearly reported assisted deaths. Objectives To examine the impact of the Canadian MAiD program and analyze its safeguards. Methods A working group of physicians from diverse practice backgrounds and a legal expert, several with bioethics expertise, reviewed Canadian MAiD data and case reports. Grey literature was also considered, including fact-checked and reliable Canadian mainstream newspapers and parliamentary committee hearings considering the expansion of MAiD. Results Several scientific studies and reviews, provincial and correctional system authorities have identified issues with MAiD practice. As well, there is a growing accumulation of narrative accounts detailing people getting MAiD due to suffering associated with a lack of access to medical, disability, and social support. Significance of results The Canadian MAiD regime is lacking the safeguards, data collection, and oversight necessary to protect Canadians against premature death. The authors have identified these policy gaps and used MAiD cases to illustrate these findings.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it