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Record W4310565652 · doi:10.1007/s10912-022-09764-z

Medical Assistance in Dying: A Review of Related Canadian News Media Texts

2022· review· en· W4310565652 on OpenAlex
Julia Brassolotto, Alessandro Manduca-Barone, Paige Zurbrigg

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

Bibliographic record

VenueJournal of Medical Humanities · 2022
Typereview
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of Lethbridge
FundersSocial Sciences and Humanities Research Council of CanadaAlberta Innovates
KeywordsDignityLegislationAutonomyScholarshipNews mediaDeath with dignityAppealPolitical sciencePublic relationsSociologyLaw

Abstract

fetched live from OpenAlex

Medical assistance in dying (MAiD) was legalized in Canada in 2016. Canadians' opinions on the service are nuanced, particularly as the legislation changes over time. In this paper, we outline findings from our review of representations of MAiD in Canadian news media texts since its legalization. These stories reflect the concerns, priorities, and experiences of key stakeholders and function pedagogically, shaping public opinion about MAiD. We discuss this review of Canadian news media on MAiD, provide examples of four key themes we identified (vulnerability, autonomy, dignity, and human rights), and discuss their implications for health policy and equity. Though key stakeholders share the values of autonomy, dignity, and human rights, they appeal to them in diverse ways, sometimes with conflicting policy demands. These representations offer a useful gauge of how views about MAiD continue to shift alongside changes in federal legislation. These stories can influence related policies, respond to the powerful voices that shape MAiD legislation, and have the potential to change national conversations. Our analysis adds to the existing body of scholarship on MAiD by examining post-Bill C-7 news media, identifying related health equity issues and tensions, and discussing potential impacts of MAiD's representations in news media.

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)0.065
metaresearch head score (Gemma)0.251
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0650.251
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0030.044
Insufficient payload (model declined to judge)0.1350.000

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 head0.322
GPT teacher head0.546
Teacher spread0.224 · 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