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Record W2342304210 · doi:10.1136/medethics-2016-103560

Why medical professionals have no moral claim to conscientious objection accommodation in liberal democracies

2016· article· en· W2342304210 on OpenAlexaff
Udo Schüklenk, Ricardo Smalling

Bibliographic record

VenueJournal of Medical Ethics · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicTorture, Ethics, and Law
Canadian institutionsQueen's University
Fundersnot available
KeywordsConscientious objectorAccommodationLawScope (computer science)TortureDemocracyPolitical scienceReasonable accommodationLiberal democracySociologyMedicineHuman rightsPoliticsPsychologyComputer science

Abstract

fetched live from OpenAlex

We describe a number of conscientious objection cases in a liberal Western democracy. These cases strongly suggest that the typical conscientious objector does not object to unreasonable, controversial professional services-involving torture, for instance-but to the provision of professional services that are both uncontroversially legal and that patients are entitled to receive. We analyse the conflict between these patients' access rights and the conscientious objection accommodation demanded by monopoly providers of such healthcare services. It is implausible that professionals who voluntarily join a profession should be endowed with a legal claim not to provide services that are within the scope of the profession's practice and that society expects them to provide. We discuss common counterarguments to this view and reject all of them.

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)0.020
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.065
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0140.057
Scholarly communication0.0100.007
Open science0.0010.012
Research integrity0.0120.012
Insufficient payload (model declined to judge)0.0070.001

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 head0.073
GPT teacher head0.429
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; 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 designTheoretical or conceptual
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

Citations146
Published2016
Admission routes1
Has abstractyes

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