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Record W1965425492 · doi:10.3917/jib.233.0111

Chapitre 7. La formation éthique continue : de l'éthique clinique à l'éthique institutionnelle

2012· article· fr· W1965425492 on OpenAlexaffabout
Lucie Brazeau-Lamontagne

Bibliographic record

VenueJournal international de bioéthique et d éthique des sciences · 2012
Typearticle
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsHôpital FleurimontUniversité de Sherbrooke
Fundersnot available
KeywordsMandateClinical EthicsConvictionContext (archaeology)BioethicsPolitical scienceProfessional ethicsEngineering ethicsHumanitiesPhilosophyLawEngineering

Abstract

fetched live from OpenAlex

UNLABELLED: The mandate of the Ethics Committee of the Conseil de médecins, dentistes et pharmaciens (CMDP) at the Centre hospitalier universitaire de Sherbrooke (CHUS), Sherbrooke, Quebec is three-fold: to guide the clinical decision; to address the institutional ethical function; to create the program for continuing education in ethics (Formation éthique continue or FEC). Might FEC be the means of bridging from individual ethics to institutional ethics at a hospital? AIM: To take the FEC perspectives considered appropriate for doctors and consider them for validation or disproving in the context of those of other professionals. PROPOSED METHOD: Situate the proposed FEC mandate in a reference framework to evaluate (or triangulate) the clinical decision and the institutional ethic. CONVICTION: Sustainable professional development for doctors (DPD) includes ethics; it cannot be ignored. Without constant attention to upgrading one's abilities in professional ethics, these suffer the same fate as other professional aptitudes and competences (for example, techniques and scientific knowledge): decay.

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)0.005
metaresearch head score (Gemma)0.010
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: none
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.008
Scholarly communication0.0080.005
Open science0.0010.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0220.003

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 head0.114
GPT teacher head0.446
Teacher spread0.332 · 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

Citations3
Published2012
Admission routes2
Has abstractyes

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Same venueJournal international de bioéthique et d éthique des sciencesSame topicHealth, Medicine and SocietyFrench-language works237,207