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Record W4401687760 · doi:10.7202/1112300ar

Do Clinical Ethicists Improve with Experience? And, If So, How Would We Know?

2024· article· en· W4401687760 on OpenAlexaffvenueabout
Victoria Seavilleklein, Jennifer Flynn, Andrea Frolic, Frank Olaf Wagner, Katarina Lee-Ameduri

Bibliographic record

VenueCanadian Journal of Bioethics · 2024
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of ManitobaPublic Health OntarioHamilton Health SciencesOntario Shores Centre for Mental Health SciencesUniversity of TorontoSt. Boniface HospitalAlberta HealthUniversity of AlbertaMemorial University of NewfoundlandAlberta Glycomics CentreMcMaster UniversityAlberta Health Services
Fundersnot available
KeywordsMEDLINEComputer sciencePsychologyData sciencePolitical science

Abstract

fetched live from OpenAlex

During our workshop at the 2023 CBS-SCB Workshop and Community Forum, we explored and problematized the concept of “improvement” of clinical ethicists, situated within the larger context of discussions about the professionalization of clinical ethics. This summary provides key insights on this topic by clinical ethicists from across Canada and includes suggestions for steps that we might want to take in the field to enable and support the improvement of clinical ethicists going forward.

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)0.017
metaresearch head score (Gemma)0.025
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesScience and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.913
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0030.041
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 head0.226
GPT teacher head0.541
Teacher spread0.315 · 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 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

Citations1
Published2024
Admission routes3
Has abstractyes

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