L’entretien individuel en recherche qualitative : usages et modes de présentation dans la Revue des sciences de l’éducation
Bibliographic record
Abstract
Cet article présente les résultats d’une étude visant à connaître l’usage de l’entretien individuel en recherche qualitative. Elle s’appuie sur l’analyse des précisions méthodologiques fournies dans 18 articles empiriques recourant à l’entretien individuel, publiés entre 2006 et 2009 dans la Revue des sciences de l’éducation . Les résultats révèlent : une utilisation marquée de l’entretien semi-dirigé ; des objectifs, contextes de recherche, participants et procédures d’analyse décrits de manière peu précise ; des résumés généralement conformes aux exigences de la Revue et l’absence de précisions quant aux précautions éthiques et à la scientificité des études. Des questions sont soulevées au regard de la validité des données et des résultats.
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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 | 0.315 | 0.321 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.010 | 0.029 |
| Scholarly communication | 0.018 | 0.018 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".