Quelle place pour les méthodes mixtes dans la recherche francophone en management ?
Bibliographic record
Abstract
Cette note de recherche analyse l’utilisation des méthodes mixtes dans la recherche francophone en management. Une étude bibliographique de trois supports (AIMS, M@n@gement, Management International) a été réalisée. L’analyse des 2341 articles permet de conclure que le recours aux méthodes mixtes demeure limité. La contribution majeure de cet article est de montrer que les méthodes mixtes permettent d’enrichir le design de recherche soit en amont (enrichissement du questionnement) soit en aval (enrichissement des résultats) soit aux deux niveaux (amont et aval). Cette note de recherche permettra également aux chercheurs de comprendre l’intérêt et les possibles opérationnalisations des méthodes mixtes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.342 | 0.395 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.031 | 0.031 |
| Open science | 0.006 | 0.015 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".