Entre qualitatif et quantitatif; complexité, interprétation et découverte
Bibliographic record
Abstract
Malgré les différences paradigmatiques significatives entre méthodes qualitative et quantitative, les deux approches demeurent confrontées à la réduction et à la restauration de la complexité et partagent un fond commun d’opérations de recherche : identification des unités, description, exploration et analyse. Les sciences sociales ayant une vocation herméneutique, il importe de ne pas opposer interprétation et explication. Loin de s’opposer, ces deux processus interagissent dans l’élaboration d’une compréhension de l’objet. L’interprétation ne peut être réduite au sens donné aux résultats ou à la compréhension globale au terme de la recherche. Il existe divers actes herméneutiques adoptant des formes différentes et se logeant aux différentes étapes du processus de recherche aussi bien dans le qualitatif que dans le quantitatif. Une démarche mixte qui combine les attributs du quantitatif et du qualitatif est susceptible de dépasser l’opposition entre le raisonnement inductif et le raisonnement déductif en adoptant la forme abductive favorisant ainsi la découverte.
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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 | 0.048 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.003 | 0.040 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".