“A Different Set of Eyes”: Breaking the Silence with Mature Minors about Medical Assistance in Dying Policy in Canada
Bibliographic record
Abstract
Background: Medical Assistance in Dying (MAID) was decriminalized in Canada in June 2016. In the approved legislation, mature minors (legally capable individuals under 18 years of age) were not permitted to access MAID. By contrast, assisted dying for minors is permitted in Belgium and the Netherlands under varying conditions. Mature minors were never engaged in the Canadian legislative process and there is very little research on mature minors’ views on MAID and their preferred role in public policy discussions about MAID. This dissertation responds to these public policy and research gaps.Methods: First, I engaged in conceptual scholarship to describe what clinical and sociological literatures contribute toward understanding the nature of death and dying related to children. Second, I conducted a comparative policy analysis using discourse coalition theory to examine policy discourse on MAID for mature minors in Canada, the Netherlands, and Belgium. Third, I conducted a qualitative study involving interviews with mature minors with critical, complex illnesses, and some parents, to explore their views on MAID. Findings: The findings from this dissertation offer many important takeaways. Study 1 revealed an “unspeakable nature” of childhood death and dying in health care (clinically and conceptually), where recognition of childhood death was rejected in pursuit and protection of ‘hope’ for recovery. Study 2 identified differences in legislative processes—Canada followed a judicial and parliamentary approach and the Netherlands/Belgium’s were parliamentary—and in dominant values and narratives underpinning policy journeys—all focused on alleviation of suffering, but Canada had a greater emphasis on rights. Study 3 highlighted that participants’ prioritize the consideration of patient suffering when contemplating MAID for mature minors, that their views and narratives were nuanced and evolving, and their advocacy for the inclusion of mature minors in related policy discussions. Conclusion: This work centralizes the voices of young people, revealing the significance of suffering in discussions related to MAID for mature minors, paediatric health care, and policy engagement. It establishes important insights for conceptualizing a ‘good death’ in childhood. Finally, the dissertation provides suggestions when considering the engagement of mature minors in clinical and policy spaces related to 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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.057 | 0.034 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.004 | 0.011 |
| 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".