Should Medical Assistance in Dying Extend to Include Mental Illness?
Bibliographic record
Abstract
In June 2016, the Parliament of Canada enacted federal legislation, known as Bill C-14, that outlined the eligibility criteria for Canadian adults to receive medical assistance in dying (MAID). The most important condition highlighted by the legislation was that a natural death must be a reasonably foreseeable future event (Truchon c. Procureur General du Canada, 2019). Two criteria, in particular, organized the broader intent of the legislation. First, a person's death must be reasonably foreseeable, and second, the medical condition must be grievous and irremediable. While the first criterion appears to exclude individuals whose sole underlying condition is a mental illness, the latter does not explicitly exclude those with mental illness (Freeland et al., 2021, p. 72). Due to the challenging wording of Bill C-14, it has been explicitly stated that people with mental illness could not legally access medical assistance in dying (MAID). Bill C-7 was put into force and effect years later, which amended the powers of Bill C-14. As of 2020, Bill C-7 established a separate set of procedural safeguards for individuals whose natural death is not reasonably foreseeable, however, this new legislation also excludes people with mental illness from accessing MAID (Nicol & Tiedemann, 2021). I will explore the thorny debate around whether MAID should extend to those with a mental illness, and ultimately show the legislative changes throughout the last few years and provide insight into potential future issues surrounding the extension of MAID to vulnerable people in Canada.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.013 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".