Ties Versus Institutions: Revisiting Foreign Interventions and Secessionist Movements
Bibliographic record
Abstract
Abstract. This article is a response to one published by Louis Bélanger, Érick Duchesne and Jonathan Paquin challenging existing accounts for the patterns of external support for secessionist movements. They assert that regime type—democracy—provides a better explanation than either vulnerability or ethnic ties. I take issue with their operationalization of my arguments along with other aspects of their work. Here, I replicate their study first using their data and importing my variable measuring not just ethnic affinity with the secessionists but the possibilities of a country having ties with either or both sides of an ethnic conflict. Then, using my data, I again replicate their analyses. I find that ethnic ties, properly measured, not only better accounts for the international relations of secession but of ethnic conflict in general. Résumé. Ce texte est une réplique à l'article de Louis Bélanger, Érick Duchesne et Jonathan Paquin, qui conteste les explications usuelles des variations dans l'appui international aux mouvements sécessionnistes. Selon eux, plus que la vulnérabilité ou les liens ethniques, c'est le type de régime – soit la démocratie – qui explique mieux le phénomène. Je remets en question leur façon d'opérationnaliser mes arguments, ainsi que plusieurs autres aspects de leur recherche. Afin de tester leurs résultats, je reproduis d'abord leur étude en utilisant leurs données et en y ajoutant ma variable qui mesure non seulement les affinités ethniques avec les sécessionnistes, mais également l'éventualité qu'un pays entretienne des relations avec l'un ou l'autre des protagonistes d'un conflit ethnique. Puis, je reprends leur analyse en utilisant mes propres données. Il en ressort que, lorsqu'elle est mesurée correctement, la variable des liens ethniques fournit une meilleure compréhension non seulement des relations internationales du phénomène de sécession, mais également des conflits ethniques en général.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".