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Record W3112368686 · doi:10.1093/jlb/lsaa087

The impact of the COVID-19 pandemic on medical assistance in dying in Canada and the relationship of public health laws to private understandings of the legal order

2020· article· en· W3112368686 on OpenAlex
Sabrina Tremblay-Huet, Thomas McMorrow, Ellen Wiebe, Michaela Kelly, Mirna Hennawy, Brian Sum

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Law and the Biosciences · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsUniversity of British ColumbiaOntario Tech UniversityUniversité de Sherbrooke
Fundersnot available
KeywordsExcusePandemicNormativePublic healthContext (archaeology)LawHealth careVariety (cybernetics)Order (exchange)Political scienceMeaning (existential)Public relationsSociologyCriminologyCoronavirus disease 2019 (COVID-19)PsychologyMedicineBusinessNursingDiseaseHistory

Abstract

fetched live from OpenAlex

Drawing on interviews we conducted with 15 medical assistance in dying (MAiD) providers from across Canada, we examine how physicians and nurse practitioners reconcile respect for the new, changing rules brought upon by the coronavirus disease 2019 (COVID-19) pandemic, along with their existing legal obligations and ethical commitments as health care professionals and MAiD providers. Our respondents reported situations where they did not follow or did not insist on others following the applicable public health rules. We identify a variety of techniques that they deployed either to minimize, rationalize, justify or excuse deviations from the relevant public health rules. They implicitly invoked the exceptionality and emotionality of the MAiD context, especially in the time of COVID, when offering their accounts and explanations. What respondents relate about their experiences providing MAiD during the COVID pandemic offers occasion to reflect on the role actors themselves play in giving meaning (if not coherence) to the potentially conflicting normative expectations to which they are subject.

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)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.233
GPT teacher head0.460
Teacher spread0.227 · 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