Bibliographic record
Abstract
Cet article porte sur les dynamiques propres aux politiques russes antiterroristes au Caucase du Nord et analyse leurs impacts sur le conflit. Pour ce faire, il s’appuie sur le concept de configuration tel que développé par N. Elias. Il se propose de déconstruire les interdépendances qui lient les acteurs de l’antiterrorisme et d’en examiner la nature et les logiques. Il montre qu’il existe non seulement un décalage entre les discours et les pratiques, mais également une divergence d’intérêts et de croyances, que la prédominance du clanisme, du localisme et du clientélisme, comme modes d’interactions et principes organisationnels, ne fait qu’enraciner. Il explique les échecs des politiques antiterroristes par les jeux de pouvoir, qui à Moscou et au Nord-Caucase, entravent leur bonne mise en oeuvre, par l’absence de coordination et la compétition inter-agences et par le détournement de la violence à des fins privées. Il montre ainsi que loin de contenir le conflit, ces pratiques imputables aux différents acteurs impliqués dans la lutte anti-terroriste participent à la montée des violences et entretiennent un conflit aux logiques multiples.
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.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".