La régionalisation du social. Une approche de l’étude de cas en sociologie
Bibliographic record
Abstract
La sociologie fait face au constat du caractère local des savoirs et des objets qui figurent en tant que médiation de ses travaux empiriques. Cet article propose d'utiliser les referents de la localisation sociale (langage, espace et temps de l'action sociale) afin d'orienter la démarche d'étude de cas. Concevant que les savoirs et les pratiques sociales, dans les sociétés contemporaines, sont localisés plutôt que strictement locaux, l'auteur définit, ï partir de la description du processus d'assimilation et d'accommodation (J. Piaget) dont font état la connaissance et les pratiques sociales, les règles d'une méthode permettant l'identification d'une régionalisation du social. À l'appui de cette démarche, un traitement de l'information en série, recourant à l'informatique qualitative des documents, est proposé pour reconstruire les formes sociales constitutives d'une économie régionalisée.
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How this classification was reachedexpand
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads 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".