Separatism as a Bargaining Posture: The Role of Leverage in Minority Radicalization
Bibliographic record
Abstract
Abstract Why do some minorities seek affirmative action while others pursue territorial autonomy or secession, given similar conditions at the substate level? This article attempts to unpack the puzzle of minority radicalization, focusing on group claim-making as an important dynamic that has been overlooked by much of the recent quantitative literature on ethnic conflict. To address this gap, the authors introduce a new `claims' variable, which codes the demands made by groups in the Minorities at Risk dataset for three five-year periods from 1985 to 2000. The authors examine the relationship between minority claim-making and rebellion and conclude that they are similar but distinct forms of group mobilization. Groups use claims as a means of bargaining with the center; relative power, therefore, has a critical influence on the extremity of demands that groups advance against the government. The authors test this model against alternative arguments using ordinal logit analysis and find that factors related to strategic power — including a history of autonomy, outside military support, and territorial concentration — are all positively correlated with a group's propensity to advance more extreme demands. This study shows that minorities with greater power vis-à-vis the center are more likely to both rebel and mobilize around separatist demands. However, minority rebellion — unlike separatist claims — may also be triggered by group deprivation, indicating that violent resistance may be driven by grievances as well as opportunities.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".