The Evolving Complexities of MAID Care in Canada From a Nursing Perspective
Bibliographic record
Abstract
Medical Assistance in Dying (MAID) legislation has evolved rapidly in Canada with significant impacts on nursing practice. The purpose of this paper is to describe evolving complexities in legislative context and practice standards that influence the experiences nurse practitioners and registered nurses have with MAID. Qualitative interviews were conducted with 25 registered nurses and 10 nurse practitioners from diverse contexts across Canada. Participants described their practices and considerations when discussing MAID as part of advance care planning; their use of, and challenges with, waivers of consent; their practice considerations in negotiating the complexities of clients for whom death is not reasonably foreseeable; and their moral wrestling with the inclusion of MAID for persons whose sole underlying medical condition is mental illness. Findings illustrate the moral complexities inherent in the evolving legislation and the importance of robust health and social care systems to the legal and ethical implementation of MAID in Canada.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".