Becoming a medical assistance in dying (MAiD) provider: an exploration of the conditions that produce conscientious participation
Bibliographic record
Abstract
The availability of willing providers of medical assistance in dying (MAiD) in Canada has been an issue since a Canadian Supreme Court decision and the subsequent passing of federal legislation, Bill C14, decriminalised MAiD in 2016. Following this legislation, Hamilton Health Sciences (HHS) in Ontario, Canada, created a team to support access to MAiD for patients. This research used a qualitative, mixed methods approach to data collection, obtaining the narratives of providers and supporters of MAiD practice at HHS. This study occurred at the outset of MAiD practice in 2016, and 1 year later, once MAiD practice was established. Our study reveals that professional identity and values, personal identity and values, experience with death and dying, and organisation context are the most significant contributors to conscientious participation for MAiD providers and supporters. The stories of study participants were used to create a model that provides a framework for values clarification around MAiD practice, and can be used to explore beliefs and reasoning around participation in MAiD across the moral spectrum. This research addresses a significant gap in the literature by advancing our understanding of factors that influence participation in taboo clinical practices. It may be applied practically to help promote reflective practice regarding complex and controversial areas of medicine, to improve interprofessional engagement in MAiD practice and promote the conditions necessary to support moral diversity in our institutions.
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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 | 0.054 | 0.386 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.023 |
| 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; both teacher heads agree on what is shown here.
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".