Replication Data for Rebel Victory and Constitutional Change
Bibliographic record
Abstract
This dataset provides a comprehensive cross-national analysis of constitutional provisions regarding property rights in rebel and non-rebel regimes from 1946 to 2021. It focuses on rebel victories, defined as the extra-legal acquisition of central authority by non-state armed forces or factions within the state military apparatus following civil wars. Rebel victory cases were identified using the Uppsala Conflict Data Program (UCDP) Conflict Termination Dataset and the Correlates of War (COW) dataset, supplemented with additional criteria to exclude cases of foreign intervention or incomplete rebel control. The dataset includes 44 states with 1,175 rebel regime-years. Constitutional data were sourced from the Comparative Constitutions Project (CCP), which documents formal constitutional texts since 1789. The dataset captures constitutional changes (amendments, interim constitutions, or new constitutions) initiated by rebel regimes and examines four key property rights provisions: (1) private property rights, (2) expropriation for public purposes, (3) payment timelines for expropriated property, and (4) expropriation through legal process or court decision. These variables are analyzed to assess how rebel regimes use constitutional changes to consolidate power and control property rights.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.059 | 0.044 |
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".