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Record W4312787179 · doi:10.22374/cjgim.v17i2.586

The Expansion of Medical Assistance in Dying in the COVID-19 Pandemic Era and Beyond

2022· article· en· W4312787179 on OpenAlex
Sera Whitelaw, Trudo Lemmens, Harriette G.C. Van Spall

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.
fundA Canadian funder is recorded on the work.
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 General Internal Medicine · 2022
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsMcMaster UniversityPopulation Health Research InstituteSt. Joseph’s Healthcare HamiltonPublic Health OntarioUniversity of TorontoImpactMcGill UniversityMcGill University Health Centre
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsTribunalParliamentCoronavirus disease 2019 (COVID-19)LawPolitical scienceEconomic JusticePandemicGovernment (linguistics)Equity (law)HumanitiesMedicinePoliticsPhilosophy

Abstract

fetched live from OpenAlex

In 2015, the Canadian parliament passed a law permitting adults to request Medical Assistance in Dying (MAiD) when they have a grievous, irremediable medical condition that causes unbearable suffering and their natural death is reasonably foreseeable. Following a constitutional challenge, a Quebec lower court, ruled in the Truchon vs. Canada AG case that the restriction to a reasonably foreseeable death is an unjustifiable impingement on the right to life, liberty, and security of the person and the right to equality. In response, the government expanded the MAiD law in March 2021 through Bill C-7 to include those who are not approaching their natural death. Bill C-7 is a potentially harmful approach to justice for vulnerable groups such as the elderly, disabled, or those with chronic illnesses. The COVID-19 pandemic has highlighted serious problems with how we care for the vulnerable members of our society. In this article, we explore what has gone wrong and what has raised serious concerns, while proposing potential options to consider when developing new laws, systems, and processes to improve societal equity.

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)0.013
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.009
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 science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.107
GPT teacher head0.451
Teacher spread0.343 · 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