Language Matters: The Semantics and Politics of “Assisted Dying”
Bibliographic record
Abstract
This essay examines the impact of linguistic choices on the perception and regulation of assisted dying, particularly in Canada. It argues that euphemistic terms like "medical assistance in dying" and its acronym, "MAID," serve to normalize the practice, potentially obscuring its moral gravity. This contrasts with what is seen in Belgium and the Netherlands, where terms like "euthanasia" are used, as well as in France and the United Kingdom, where terminology remains divisive and contested. By tracing the evolution of these terms and what they reveal about different cultural and legal approaches, this essay sheds light on the politics of language in end-of-life discourses. It suggests that the shift toward euphemistic language reflects a broader discomfort with death that can shape public attitudes and legal frameworks. It calls for a more transparent, philosophically grounded approach to terminology and suggests that continued debate about semantics is necessary to capture the complexities and ethical significance of assisted dying.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.109 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 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".