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Record W3163752169 · doi:10.7202/1076025ar

Typologie des problèmes éthiques nommés par des employés du réseau québécois de la santé et des services sociaux à l’occasion de séances de groupes de codéveloppement professionnel*

2021· article· fr· W3163752169 on OpenAlexaffvenueabout
Yanick Farmer, Mehlia Bissière, Maxime Paquet, Nathalie Lafranchise

Bibliographic record

VenueManagement international · 2021
Typearticle
Languagefr
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

En matière d’éthique, les organisations optent le plus souvent pour une approche formaliste faisant appel au code d’éthique. L’approche formaliste omet toutefois de prendre en considération le sens que les acteurs d’une organisation donnent à ces normes. Afin de jeter les bases d’une éthique organisationnelle empirique partant du point de vue des acteurs, cette recherche propose une typologie des problèmes éthiques vécus en organisation à partir d’une analyse qualitative des verbatim de rencontres de groupes de codéveloppement professionnel dans le réseau québécois de la santé.

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)0.015
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.676

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.007
Science and technology studies0.0110.013
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.190
GPT teacher head0.468
Teacher spread0.278 · 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 designQualitative
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
Published2021
Admission routes3
Has abstractyes

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