Comment lire de façon critiqueles articles de recherche qualitativeen médecine
Bibliographic record
Abstract
Contexte : Bien que la recherche qualitative soit de plus en plus reconnue en médecine, la plupart des cliniciens enseignants ne savent pas comment lire de façon critique les articles s'y rapportant. But : Présenter et expliquer une nouvelle grille de lecture critique des articles de recherche qualitative appliquée à la médecine afin que les médecins enseignants soient mieux en mesure de lire de façon critique ce type d'articles. Méthode : Revue de la littérature, sélection et explicitation des critères de scientificité en recherche qualitative. Résultats : Grille comportant 12 énoncés ainsi que des explications et des lectures complémentaires pour chacun d'eux. Conclusion : La présentation et la discussion de cette nouvelle grille permettra aux lecteurs de mieux comprendre ce que sont la recherche qualitative et les critères de scientificité qui lui sont propres.
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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 | 0.103 | 0.277 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.010 |
| 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".