Conscientious objection to medical assistance in dying in rural/remote nursing
Bibliographic record
Abstract
In 2016, the Supreme Court of Canada legalized medical assistance in dying in Canada. Similar to jurisdictions where this has been a more long-standing option for end-of-life care, the Supreme Court’s decision in Canada included a caveat that no healthcare provider could be compelled to participate in medical assistance in dying. The Canadian Nurses Association, in alignment with numerous ethical guidelines for healthcare providers around the globe, maintains that nurses may opt out of participation in medical assistance in dying if they conscientiously object to this procedure. The realities of implementing medical assistance in dying are still unfolding. One area that has received little attention in the literature thus far is the ability of nurses who aid with, rather than administer, medical assistance in dying to conscientiously object. This is particularly significant in rural and remote areas of Canada where geographic dispersion and limited numbers of nursing staff create conditions that limit the ability to transfer care or call on a designated team. Exercising conscientious objection to medical assistance in dying in rural and remote areas, by way of policies developed with an urban focus, is one example of how the needs of rural nurses and patients may not be met, leading to issues of patient access to medical assistance in dying and retention of nursing staff. To illustrate the complexities of nurses’ conscientious objection to medical assistance in dying in a rural setting, we apply an ethical decision-making framework to a hypothetical case scenario and discuss the potential consequences and implications for future policy. Realizing that conscientious objection may not be a viable option in a rural or remote context has implications for not only medical assistance in dying, but other ethically sensitive healthcare services as well. These considerations have implications for policy in other jurisdictions allowing or considering medically assisted deaths, as well as other rural and remote areas where nurses may face ethical dilemmas.
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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 | 0.019 | 0.127 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.020 |
| 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 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".