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Record W2504775407 · doi:10.15173/m.v1i29.1117

Physician-Assisted Dying: A New Option In Canadian End of Life Care

2016· article· en· W2504775407 on OpenAlexaffvenueabout
David Bobrowski, Faizan Bhatia

Bibliographic record

VenueThe Meducator · 2016
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEnd-of-life careMedicineFamily medicinePeer reviewNursingGerontologyPalliative carePolitical science

Abstract

fetched live from OpenAlex

Healthcare in Canada is undergoing a major transformation as patients obtain the right to request for and be granted physician-assisted dying (PAD).1 This legal reform represents a paradigm shift in Canada’s approach to end of life care. In February 2015, the Supreme Court of Canada (SCC) struck down laws that made it illegal for individuals to assist others in ending their own lives. The ruling on PAD has been held in suspension for 16 months to allow for amendments to health policy.2 The SCC’s ruling only applies to competent adults with persistent, intolerable suffering, who consent to ending their lives.1 In this article, we aim to coalesce several opinions on the implementation of PAD, highlight the challenges, and critically evaluate recommendations of several policy-influencing bodies.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.210
Threshold uncertainty score0.916

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0400.027
Scholarly communication0.0150.007
Open science0.0050.007
Research integrity0.0150.019
Insufficient payload (model declined to judge)0.0070.000

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 head0.096
GPT teacher head0.384
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2016
Admission routes3
Has abstractyes

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