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Record W3022335197 · doi:10.1136/medethics-2019-105758

Becoming a medical assistance in dying (MAiD) provider: an exploration of the conditions that produce conscientious participation

2020· article· en· W3022335197 on OpenAlexaffabout
Allyson Oliphant, Andrea Frolic

Bibliographic record

VenueJournal of Medical Ethics · 2020
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsHamilton Health SciencesLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsLegislationSupreme courtNarrativeContext (archaeology)TabooIdentity (music)Diversity (politics)SociologyQualitative researchPublic relationsLawPsychologyNursingPolitical scienceMedicineSocial scienceAestheticsHistory

Abstract

fetched live from OpenAlex

The availability of willing providers of medical assistance in dying (MAiD) in Canada has been an issue since a Canadian Supreme Court decision and the subsequent passing of federal legislation, Bill C14, decriminalised MAiD in 2016. Following this legislation, Hamilton Health Sciences (HHS) in Ontario, Canada, created a team to support access to MAiD for patients. This research used a qualitative, mixed methods approach to data collection, obtaining the narratives of providers and supporters of MAiD practice at HHS. This study occurred at the outset of MAiD practice in 2016, and 1 year later, once MAiD practice was established. Our study reveals that professional identity and values, personal identity and values, experience with death and dying, and organisation context are the most significant contributors to conscientious participation for MAiD providers and supporters. The stories of study participants were used to create a model that provides a framework for values clarification around MAiD practice, and can be used to explore beliefs and reasoning around participation in MAiD across the moral spectrum. This research addresses a significant gap in the literature by advancing our understanding of factors that influence participation in taboo clinical practices. It may be applied practically to help promote reflective practice regarding complex and controversial areas of medicine, to improve interprofessional engagement in MAiD practice and promote the conditions necessary to support moral diversity in our institutions.

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 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)0.054
metaresearch head score (Gemma)0.386
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0540.386
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.023
Insufficient payload (model declined to judge)0.0010.000

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 head0.450
GPT teacher head0.577
Teacher spread0.126 · 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; both teacher heads agree on what is shown here.

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

Citations38
Published2020
Admission routes2
Has abstractyes

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