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Record W1871204928 · doi:10.3917/cdle.039.0137

Les recherches collaboratives : enjeux et perspectives

2015· article· fr· W1871204928 on OpenAlexaboutno aff
Isabelle Vinatier, Joëlle Morrissette

Bibliographic record

VenueCarrefours de l éducation · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La note de synthèse donne un aperçu des fondements des recherches collaboratives, de leurs développements actuels, de leurs disséminations et enfin de leurs enjeux. Les auteurs se reconnaissent tous dans l’horizon de sens ouvert par le pragmatisme de Dewey et reprennent à leur compte une conception du fonctionnement des groupes humains que Lewin, à qui l’on doit le concept de « recherche-action », fonde sur la tolérance et la démocratie. Encore marginales en France elles jouissent d’une popularité certaine au Québec. Leur accréditation par les organismes internationaux leur attribue un potentiel de développement des professionnalités individuelles et collectives et les considère comme un levier de développement des organisations apprenantes. Dans un premier temps, l’identification des problématiques et des enjeux qui caractérisent les recherches collaboratives permet la mise en relief des tensions qui les traversent. Dans un deuxième temps, en référence aux travaux de Lenoir (2012), sont évoqués les marqueurs et tendances qui permettent de situer la notion de recherche collaborative entre celle de recherche-action et celle de recherche partenariale. Enfin, dans une perspective épistémologique, sont discutés les rapports entre chercheurs et professionnels de même que se trouve questionné le type de savoirs qui peut être produit par ces recherches.

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)0.065
metaresearch head score (Gemma)0.063
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 score0.065
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0650.063
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.012
Science and technology studies0.0190.053
Scholarly communication0.0400.039
Open science0.0040.018
Research integrity0.0100.013
Insufficient payload (model declined to judge)0.0100.002

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 head0.821
GPT teacher head0.612
Teacher spread0.209 · 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".

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Citations117
Published2015
Admission routes1
Has abstractyes

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