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Record W4401687625 · doi:10.7202/1112287ar

Assisted Suicide and Euthanasia: Language Lost in MAiD

2024· article· en· W4401687625 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Bioethics · 2024
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsDalhousie UniversityHorizon Health NetworkUniversity of New Brunswick
Fundersnot available
KeywordsSuicide preventionHuman factors and ergonomicsOccupational safety and healthPoison controlAssisted suicideInjury preventionPsychologyMEDLINEPsychiatryMedical emergencyMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

For most of Canada’s approximately 40-year debate on medically assisted death, euthanasia and assisted suicide were considered distinct issues. Yet in 2016 their ethical, psychological, and practical differences were effectively disregarded when the two acts were grouped together in the legislation under the umbrella term “Medical Assistance in Dying” (MAiD). The lack of distinction under the law of the two terms ignores important ethical considerations from the MAiD practitioners’ perspective. Although the principle of respect for autonomy must remain central to the assessments of MAiD eligibility, it cannot be the only consideration. This paper examines the ethical considerations and principles that underlie decisions to provide MAiD through an analysis of the progress, and results, of the 40-year debate on assisted suicide and euthanasia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.125
GPT teacher head0.414
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it