Analyses qualitatives et quantitatives : deux visions, une même science
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cet article suggère que, malgré bon nombre de plaidoiries qui affirment que les méthodes qualitatives et quantitatives sont antinomiques, ces deux types de méthode ont beaucoup en partage et ils sont tous les deux soumis aux mêmes exigences de scientificité. Non seulement jouent-ils des rôles complémentaires dans les sciences humaines, mais, en plus, 1) leurs analyses doivent toujours avoir quelque représentativité, 2) leurs résultats doivent pouvoir caractériser un ensemble étudié, 3) les caractérisations doivent être modulées par les variations individuelles, 4) leurs analyses doivent établir des liens entre les objets/sujets étudiés, et 5) ces analyses sont soumises à la tension qui s’impose entre l’obligation de regrouper les données et celle d’en respecter les particularités.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.011 |
| Science and technology studies | 0.007 | 0.039 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it