L’analyse qualitative informatisée : logiquedes puces et quête de sens
Bibliographic record
Abstract
Le recours massif aux nouveaux outils d’analyse qualitative informatisée risque-t-il d’imposer un carcan fatal à la recherche qualitative? À partir d’une expérience de formation et de consultation avec une variété d’individus s’initiant à l’analyse qualitative informatisée et d’une réflexion sociologique sur le pouvoir coercitif des inscriptions dans les instruments et les machines complexes, nous proposons que l’influence des logiciels spécialisés ne peut être comprise qu’en relation avec le degré d’expertise antérieure de l’apprenti et les conditions socioéconomiques de réalisation de la recherche. L’acquisition d’une culture fondamentale solide en recherche qualitative et un recul critique vis à vis des exigences productivistes de la recherche subventionnée actuelle apparaissent comme des conditions essentielles à l’utilisation libératrice de ces puissants outils.
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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 | 0.047 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.007 | 0.038 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".