Fighting over nation or state: States, communal demography, and the type of ethnic civil war
Bibliographic record
Abstract
Abstract We recognise nationalist and centre‐seeking ethnic civil wars as distinct types of conflict and draw on key ideas from political sociology to make hypotheses about the causes of each. First, we argue that the character of states shapes antistate actors in ways that channel ethnic conflict in different ways, with pluralist states promoting nationalist warfare but integrative states contributing to centre‐seeking civil war. Second, we propose that the relative power of communities affects the type of ethnic civil war, arguing that centre‐seeking civil war is most common in situations of communal multipolarity whereas nationalist civil war is concentrated in regions with asymmetric power relations. And because historical statehood promotes elements of pluralist states and asymmetric communal power relations, we hypothesise that the risk of nationalist civil war is high in places with large and longstanding states. To test these hypotheses, we use ethnic fractionalisation to measure configurations of communal power and the state antiquity index to measure level of historical statehood, create a variable measuring the extent to which colonial states were pluralist, and run panel analyses of the odds of civil war onset. With one possible exception, the findings support our hypotheses.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".