Fragilité régionale, capacité de l’État et guerre civile
Bibliographic record
Abstract
Il est fréquent de voir des guerres civiles éclater simultanément dans des pays voisins. Cela tient notamment à ce que ces pays présentent des caractéristiques communes, et aussi à ce qu’une guerre civile favorise l’apparition de conflits dans les pays voisins. La littérature empirique dissocie habituellement ces deux explications. Nous proposons un modèle de la contagion des guerres civiles qui illustre que certaines caractéristiques des pays sont affectées par le risque de contagion. En particulier, un gouvernement peut éviter la contagion en investissant dans la qualité de ses institutions. La complémentarité stratégique entre les institutions de pays voisins génère des regroupements de pays selon leur capacité étatique. Cela suggère que les effets de contagion ont pu jusque-là être sous-estimés par la littérature empirique.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".