Hegemonic shocks and patterns of secession
Bibliographic record
Abstract
Studies of secession typically focus on domestic factors that produce independence movements, such as the role of ethnic divides or the concentration of material resources. But motivations for secession are also linked to broader changes in the international system. This article examines the links between great power shocks and global patterns of secession. We argue that abrupt great power shocks, marked by the rise and fall of powerful states, trigger waves of secessionism by temporarily weakening metropoles and facilitating the diffusion of independence movements. These movements, however, often stumble when the global shock passes and local conditions like institutional capacity or the strength of the metropole regain importance. Using a comprehensive dataset of secessionist movements between 1900 and 2011, we find that great power shocks are closely linked with bursts of secessionist activity. Consistent with expectations, we also find that secessionist attempts in the wake of great power transitions are not more likely to succeed. Overall, the results suggest that sudden great power shocks play an important and under-examined role in the timing and success of secessionist movements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".