Medical Assistance in Dying: Challenges of Monitoring the Canadian Program
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
The Canadian medical assistance in dying (MAID) program, based on an ambitious piece of legislation and detailed regulations, has failed to provide Canadians with sufficient publicly accessible evidence to show that it is operating as mandated by the requirements of the law, regulations, and expectations of all stakeholders. The federal law that was adopted in 2016 defined the eligibility criteria and put in place a number of safeguards that had to be satisfied before providing assisted dying to a person in order not to transgress the Criminal Law. The responsibility of monitoring for the purpose of investigating compliance with the eligibility criteria and procedural safeguards was assigned by the Federal Ministry of Health (responsible for all monitoring) to the provincial and territorial governments. Some of the governments have released statistical data concerning the program, but none have yet issued a comprehensive report on adherence to the eligibility criteria and its safeguards as required by the law and regulations. This paper explains the process, explores the possible reasons for this shortfall, and offers some suggestions for actions that could rectify this aspect of the MAID program. Accountability and transparency are integral to the delivery of MAID and the publications of the mandated federal as well as provincial/territorial monitoring reports are one important approach to achieving confidence and trust in the program.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| 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