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Record W2992999517 · doi:10.1136/medethics-2019-105855

Conscientious objection and moral distress: a relational ethics case study of MAiD in Canada

2019· article· en· W2992999517 on OpenAlexaffabout
Mary Kathleen Deutscher Heilman, Tracy J. Trothen

Bibliographic record

VenueJournal of Medical Ethics · 2019
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsQueen's UniversitySt. Paul's Hospital
Fundersnot available
KeywordsConscienceBioethicsConscientious objectorHealth careConstructiveDistressSociologyPsychologyLawSocial psychologyEngineering ethicsPolitical scienceComputer sciencePsychotherapist

Abstract

fetched live from OpenAlex

Conscientious objection has become a divisive topic in recent bioethics publications. Discussion has tended to frame the issue in terms of the rights of the healthcare professional versus the rights of the patient. However, a rights-based approach neglects the relational nature of conscience, and the impact that violating one's conscience has on the care one provides. Using medical assistance in dying as a case study, we suggest that what has been lacking in the discussion of conscientious objection thus far is a recognition and prioritising of the relational nature of ethical decision-making in healthcare and the negative consequences of moral distress that occur when healthcare professionals find themselves in situations in which they feel they cannot provide what they consider to be excellent care. We propose that policies that respect the relational conscience could benefit our healthcare institutions by minimising the negative impact of moral distress, improving communication among team members and fostering a culture of ethical awareness. Constructive responses to moral distress including relational cultivation of moral resilience are urged.

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)0.052
metaresearch head score (Gemma)0.138
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.730
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0520.138
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.045
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 head0.154
GPT teacher head0.511
Teacher spread0.357 · 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 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

Citations22
Published2019
Admission routes2
Has abstractyes

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