La désintégration yougoslave : un cadre fertile pour la théorie des dominos ?
Bibliographic record
Abstract
Undoubtedly, one of the most critical crisis in the post-Cold War ex a, the Yugoslav conflict, due to its nationalist character, nurture the fear that a full scale Balkan War would result. In the very heart of Europe, it threated to spread, and then to slip away from the Occidental power's control. How to explain it, but specially how to prevent this diffusion ? The Domino Theory applied to the Yugoslav conflict proposes a model to answer these core questions. Based on a positive model of spatial diffusion, the analysis which follows investigates in depth the relationships between the « 1989 socialist break-up », the internal situation of Yugoslavia, and the spreading of the conflict. By so doing this analysis sheds light on the circomstantial causes and on the chaine of events which explain the origin of the conflict, as well as its expension. Starting with the postulate that the actions of state, within a given spatial and time framework, have a definite chance of influencing the actions of its neighboring states, we attribute an important mesure of responsibility to the collapse of USSR in the Yugoslav Conflict's release.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.024 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".