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Record W2407629882 · doi:10.1111/bioe.12262

The use of Ethics Decision‐Making Frameworks by Canadian Ethics Consultants: A Qualitative Study

2016· article· en· W2407629882 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBioethics · 2016
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsQueen's UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsEthical decisionHealth careAccreditationEngineering ethicsTriageOrganizational ethicsInformation ethicsNursing ethicsClinical EthicsResearch ethicsApplied ethicsQualitative researchWork (physics)SociologyPsychologyMedicinePolitical scienceMedical educationSocial scienceEngineering

Abstract

fetched live from OpenAlex

In this study, Canadian healthcare ethics consultants describe their use of ethics decision-making frameworks. Our research finds that ethics consultants in Canada use multi-purpose ethics decision-making frameworks, as well as targeted frameworks that focus on reaching an ethical resolution to a particular healthcare issue, such as adverse event reporting, or difficult triage scenarios. Several interviewees mention the influence that the accreditation process in Canadian healthcare organizations has on the adoption and use of such frameworks. Some of the ethics consultants we interviewed also report on their reluctance to use these tools. Limited empirical work has been done previously on the use of ethics decision-making frameworks. This study begins to fill this gap in our understanding of the work of healthcare ethics consultants.

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.

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)0.082
metaresearch head score (Gemma)0.755
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0820.755
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0060.005
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0070.053
Insufficient payload (model declined to judge)0.0000.000

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 head0.504
GPT teacher head0.628
Teacher spread0.125 · 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