A Life Disrupted: Perspectives on Track 2 MAID from Persons Living with Chronic Illness
Bibliographic record
Abstract
Background: In 2021, Canada extended Medical Assistance in Dying (MAID) to persons whose natural death is not reasonably foreseeable, referred to as Track 2 MAID. The purpose of this study was to develop a better understanding of best practices for Track 2 MAID from the perspectives of those living with an illness, disease, or disability that could potentially make them eligible for MAID. Methods: This was a qualitative interview study using the principles of Interpretive Description. Seven participants were interviewed three times over a period of 3-6 weeks. Findings: Participants described prolonged and complex illness trajectories that resulted in suffering from loss, stigma, and iatrogenic harm. The expertise they had developed over years of living with their condition and the challenges they had experienced in healthcare informed their perspectives about MAID care. Participants highlighted essential expertise needed for Track 2 assessors to provide compassionate, trauma-informed care. Participants recognized the need for time to achieve a holistic understanding of each applicant’s experience, consequent suffering, attempts to relieve that suffering, and to develop a picture of decline over time. Participants were troubled by perceived tension between autonomy and the role of the social determinants of health in determinations of eligibility for MAID. Discussion: Overall, participants described the necessity of a partnered approach to Track 2 MAID assessment. Although participants considered the individual autonomy of others as more important than their personal views, they expressed grave concerns about the potential for inadequate health and social care systems to influence requests for MAID.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.032 | 0.021 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.005 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 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".