Saisir la violence de masse : le nettoyage ethnique en Bosnie et l'apport d'une perspective locale et d'une approche de réseau
Bibliographic record
Abstract
La compréhension de l’élimination d’une population est généralement envisagée comme résultant d’un plan intentionnel, «d’en haut», coordonné par une série d’institutions étatiques et constituant alors le crime et le paradigme de génocide. Cette perspective, héritage des études traitant l’Holocauste, est ici pondérée dans le contexte du nettoyage ethnique de Bosnie-Herzégovine entre 1992 et 1995 par une approche de réseau et une perspective de «terroir» qui tiennent à la fois compte d’un redéploiement du pouvoir de coercition sur une multitude de gens armés et des dynamiques locales animant les exécutants. Par isomorphisme, ces approches peuvent alimenter la réflexion sur le processus de justice de transition.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".