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Record W2132078911 · doi:10.7202/045358ar

Comparaison de deux méthodes de dissémination de résultats de recherche dans le domaine de la santé : les arts et le café scientifique

2011· article· fr· W2132078911 on OpenAlexaffvenue
Darquise Lafrenière, Susan Cox

Bibliographic record

VenueSociologie et sociétés · 2011
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Un nombre croissant de chercheurs du domaine de la santé se tournent vers des formes novatrices de recherche alliant les méthodologies des sciences sociales et des arts performatifs, littéraires et visuels. Cet article compare et analyse deux méthodes de dissémination de résultats de recherche dans le domaine de la santé : le café scientifique et la performance artistique (arts visuels, chant, poésie, théâtre). L’analyse de questionnaires remplis par 78 répondants et d’entrevues menées auprès de ces personnes indique que la performance artistique est plus efficace dans la communication de résultats de recherche selon trois des quatre critères d’évaluation utilisés : elle suscite davantage d’émotions chez les membres de l’auditoire, suscite plus de questions sur le sujet couvert et influence un plus grand nombre de personnes à modifier leur point de vue et leurs pratiques. Tant le café scientifique que la performance artistique aident les participants à comprendre la problématique exposée. Les arts permettent cependant une compréhension différente.

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)0.396
metaresearch head score (Gemma)0.615
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.745

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3960.615
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0150.013
Science and technology studies0.0040.006
Scholarly communication0.0130.009
Open science0.0030.010
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.002

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 head0.856
GPT teacher head0.663
Teacher spread0.193 · 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 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

Citations2
Published2011
Admission routes2
Has abstractyes

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