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Record W2889913975 · doi:10.1136/medethics-2018-104896

Medical Assistance in Dying at a paediatric hospital

2018· article· en· W2889913975 on OpenAlexaffabout
Carey DeMichelis, Randi Zlotnik Shaul, Adam Rapoport

Bibliographic record

VenueJournal of Medical Ethics · 2018
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsHospital for Sick ChildrenDe VeberUniversity of Toronto
Fundersnot available
KeywordsConfusionStigma (botany)InstitutionPopulationPublic relationsSociologyBest interestsMedical humanitiesMedicineNursingPsychologyMedical educationPolitical scienceLawSocial sciencePsychiatryPsychoanalysis

Abstract

fetched live from OpenAlex

This article explores the ethical challenges of providing Medical Assistance in Dying (MAID) in a paediatric setting. More specifically, we focus on the theoretical questions that came to light when we were asked to develop a policy for responding to MAID requests at our tertiary paediatric institution. We illuminate a central point of conceptual confusion about the nature of MAID that emerges at the level of practice, and explore the various entailments for clinicians and patients that would flow from different understandings. Finally, we consider the ethical challenges of building policy on what is still an extremely controversial social practice. While MAID is currently available to capable patients in Canada who are 18 years or older-a small but important subsection of the population our hospital serves-we write our policy with an eye to the near future when capable young people may gain access to MAID. We propose that an opportunity exists for MAID-providing institutions to reduce social stigma surrounding this practice, but not without potentially serious consequences for practitioners and institutions themselves. Thus, this paper is intended as a road map through the still-emerging legal and ethical landscape of paediatric MAID. We offer a view of the roads taken and considered along the way, and our justifications for travelling the paths we chose. By providing a record of our in-progress thinking, we hope to stimulate wider discussion about the issues and questions encountered in this work.

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)0.007
metaresearch head score (Gemma)0.046
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
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 head0.132
GPT teacher head0.470
Teacher spread0.338 · 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 designObservational
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

Citations16
Published2018
Admission routes2
Has abstractyes

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