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Record W2896013147 · doi:10.1111/bioe.12528

Institutional non‐participation in assisted dying: Changing the conversation

2018· article· en· W2896013147 on OpenAlexaff
Philip Shadd, Joshua Shadd

Bibliographic record

VenueBioethics · 2018
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsMcMaster UniversityRedeemer University
Fundersnot available
KeywordsConscienceCognitive reframingConversationFraming (construction)Philosophy of medicinePalliative careSociologyCorporate governancePolitical sciencePublic relationsLawSocial psychologyMedicinePsychologyNursingBusiness

Abstract

fetched live from OpenAlex

Whether institutions and not just individual doctors have a right to not participate in medical assistance in dying (MAID) is controversial, but there is a tendency to frame the issue of institutional non-participation in a particular way. Conscience is central to this framing. Non-participating health centres are assumed to be religious and full participation is expected unless a centre objects on conscience grounds. In this paper we seek to reframe the issue. Institutional non-participation is plausibly not primarily, let alone exclusively, about conscience. We seek to reframe the issue by making two main points. First, institutional non-participation is primarily a matter of institutional self-governance. We suggest that institutions have a natural right of self-governance which, in the case of health centres such as hospitals or hospices, includes the right to choose whether or not to offer MAID. Second, there are various legitimate reasons unrelated to conscience for which a health centre might not offer MAID. These range from considerations such as institutional capacity and expertise to a potential contradiction with palliative care and a concern to not conflate palliative care and MAID in public consciousness. It is a mistake to frame the conversation simply in terms of conscience-based opposition to MAID or full participation. Our goal is to open up new space in the conversation, for reasons unrelated to conscience as well as for non-religious health centres who might nonetheless have legitimate grounds for not participating in MAID.

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)0.095
metaresearch head score (Gemma)0.089
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.095
Threshold uncertainty score0.502

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0950.089
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0310.115
Scholarly communication0.0280.051
Open science0.0050.024
Research integrity0.0380.055
Insufficient payload (model declined to judge)0.0050.001

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 head0.354
GPT teacher head0.496
Teacher spread0.142 · 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

Citations46
Published2018
Admission routes1
Has abstractyes

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