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Record W4401687656 · doi:10.7202/1112281ar

Les comités d’éthique de la recherche en milieu collégial : mandat, gouvernance et ressources

2024· article· fr· W4401687656 on OpenAlexaffvenue
Marie-Alexia Masella, Charles Dupras, Emmanuelle Marceau

Bibliographic record

VenueCanadian Journal of Bioethics · 2024
Typearticle
Languagefr
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsCégep du Vieux MontréalUniversité de Montréal
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Le développement de l’éthique de la recherche dans le milieu collégial soulève des préoccupations spécifiques, compte tenu des particularités de ce milieu. Cette étude s’intéresse à trois enjeux prioritaires de la communauté d’éthique de la recherche du collégial : 1) la question des ressources pour l’évaluation éthique par les comités d’éthique de la recherche du réseau collégial; 2) l’évaluation de projets de recherche relevant de plusieurs autorités; et 3) l’évaluation des activités de recherche conduite dans le cadre de cours par des étudiantes et étudiants. Afin de sonder cette communauté sur ses réalités concrètes face à ces enjeux, nous avons réalisé une étude mixte de type Delphi en temps réel grâce à la plateforme Surveylet, au cours de laquelle nous avons mis en dialogue 31 panélistes durant une période totale de cinq semaines. Cet article présente les résultats de notre analyse statistique et thématique des réponses obtenues, les principaux consensus et dissensus identifiés au sujet des trois enjeux, ainsi que des pistes de solutions pour surmonter ces enjeux inspirés par les propositions des panélistes.

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)0.105
metaresearch head score (Gemma)0.097
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.981
Threshold uncertainty score0.556

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1050.097
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0140.017
Scholarly communication0.0170.008
Open science0.0020.013
Research integrity0.0030.005
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 head0.400
GPT teacher head0.555
Teacher spread0.155 · 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.

Study designNot applicable
DomainMethods
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 routes2
Has abstractyes

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