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Record W4298006300 · doi:10.1136/jme-2022-108431

Externalist argument against medical assistance in dying for psychiatric illness

2022· article· en· W4298006300 on OpenAlexaboutno aff
Hane Htut Maung

Bibliographic record

VenueJournal of Medical Ethics · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicMental Health and Psychiatry
Canadian institutionsnot available
FundersLeverhulme Trust
KeywordsExternalismMental illnessPsychiatryArgument (complex analysis)JudgementPsychological interventionPsychologyMedicineMental healthLawPolitical science

Abstract

fetched live from OpenAlex

Medical assistance in dying, which includes voluntary euthanasia and assisted suicide, is legally permissible in a number of jurisdictions, including the Netherlands, Belgium, Switzerland and Canada. Although medical assistance in dying is most commonly provided for suffering associated with terminal somatic illness, some jurisdictions have also offered it for severe and irremediable psychiatric illness. Meanwhile, recent work in the philosophy of psychiatry has led to a renewed understanding of psychiatric illness that emphasises the role of the relation between the person and the external environment in the constitution of mental disorder. In this paper, I argue that this externalist approach to mental disorder highlights an ethical challenge to the practice of medical assistance in dying for psychiatric illness. At the level of the clinical assessment, externalism draws attention to potential social and environmental interventions that might have otherwise been overlooked by the standard approach to mental disorder, which may confound the judgement that there is no further reasonable alternative that could alleviate the person's suffering. At the level of the wider society, externalism underscores how social prejudices and structural barriers that contribute to psychiatric illness constrain the affordances available to people and result in them seeking medical assistance in dying when they otherwise might not have had under better social conditions.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0070.000

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 head0.069
GPT teacher head0.371
Teacher spread0.302 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations10
Published2022
Admission routes1
Has abstractyes

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