Canadian Medical Assistance in Dying: Provider Concentration, Policy Capture, and Need for Reform
Bibliographic record
Abstract
Canada's rapid rise in deaths from euthanasia and physician assisted suicide, termed Medical Assistance in Dying (MAID) in the country, now ranks it second only to the Netherlands in terms of MAiD deaths as percentage of overall deaths, with one province already hosting the highest rate of all jurisdictions in the world. Analyzing Health Canada's annual MAID reports, which show that up to 336 out of 1837 providers are likely responsible for the majority of MAID deaths in a given year, we discuss how the rapid increase likely reflects not a broad Canadian consensus but the capture of a policy-making and implementation process by a small group of activists and clinicians colonizing medicine to become an ideologically driven vehicle for expanding MAID access and delivery. As a remedy and to reprioritize patient safety and protection against premature death, a more transparent, relevant, and safeguarded compliance regime based on evidence-based, multi-perspective policy-making is needed.
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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 | 0.051 | 0.103 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.033 | 0.017 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 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".