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Record W3080595153 · doi:10.1177/0030222820948645

Perception of Medical Assistance in Dying Among Asian Buddhists Living in Montreal, Canada

2020· article· en· W3080595153 on OpenAlexaffabout
Nidup Dorji, Sylvie Lapierre, Dolores Angela Castelli Dransart

Bibliographic record

VenueOMEGA - Journal of Death and Dying · 2020
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité du Québec à Montréal
Fundersnot available
KeywordsKarmaLegalizationPerceptionDoctrinePsychologyQualitative researchGender studiesSociologyPolitical scienceLawPsychiatrySocial scienceTheologyPhilosophy

Abstract

fetched live from OpenAlex

In the Western world including Canada, grievous and irredeemable health conditions, which cause unbearable suffering, has given support to the legalization of medical aid in dying (MAiD). It is unknown how Asian Buddhists who are in contact with the Western culture perceive MAiD. In this qualitative study, 16 Asian Buddhists living in Montreal took part in a semi-structured interview. Contrary to general findings in the literature, religious affiliation do not always determine moral stances and practical decisions when it comes to MAiD. Some participants were willing to take some freedom with the doctrine and based their approval of MAiD on the right to self-determination. Those who disapproved the use of MAiD perceived it as causing unnatural death, creating bad karma, and interfering with a conscious death. End-of-life (EoL) care providers have to remain sensitive to each patient's spiritual principles and beliefs to understand their needs and choices for EoL care.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.003
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.056
GPT teacher head0.342
Teacher spread0.286 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations5
Published2020
Admission routes2
Has abstractyes

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Same venueOMEGA - Journal of Death and DyingSame topicPalliative Care and End-of-Life IssuesFrench-language works237,207