In a Familiar Voice: The Dominant Role of Women in Shaping Canadian Policy on Medical Assistance in Dying
Bibliographic record
Abstract
Among the many remarkable aspects of the June 2016 introduction of legislation to permit medical assistance in dying (MAiD) in Canada, is the central and even dominant role that women have played in moving this legislation forward, and their ongoing influence as the law continues to be reviewed and revised. The index medical cases on which the higher courts have deliberated concern women patients, and the legal decisions in the various courts have been presided over by women justices. Since the legislation has become law in Canada, women have been among the most vocal and enthusiastic proponents for expanding the criteria to ensure MAiD is more accessible to more Canadians. In this paper, I discuss how the voice of women in this debate is not the ‘different voice’ of second wave feminism first articulated by Carol Gilligan and then adapted and expanded in the ethics of care and relational ethics literature. Instead it is the very familiar voice of the ethics of personal autonomy, individual rights and justice which feminist critics have long decried as inadequate to the task of articulating a comprehensive social morality. I argue for the need to reassert the different voice of relational ethics and the ethics of care into our ongoing discussion of 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 | 0.016 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.058 | 0.049 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".