Comparative and Critical Analysis of Key Eligibility Criteria for Voluntary Assisted Dying under Five Legal Frameworks
Bibliographic record
Abstract
Eligibility criteria determine a crucial question for all voluntary assisted dying frameworks: who can access assistance to die? This article undertakes a critical and comparative analysis of these criteria across five legal frameworks: existing laws in Victoria, Western Australia, Oregon and Canada, along with a model Bill for reform. Key aspects of these criteria analysed are capacity requirements; the nature of the medical condition that will qualify; and any required suffering. There are many similarities between the five models but there are also important differences which can have a significant impact on who can access voluntary assisted dying and when. Further, seemingly straightforward criteria can become complex in practice. The article concludes with the implications of this analysis for designing voluntary assisted dying regulation. Those implications include challenges of designing certain yet fair legislation and the need to evaluate voluntary assisted dying frameworks holistically to properly understand their operation.
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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 | 0.080 | 0.126 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.019 | 0.042 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.004 | 0.008 |
| 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".