Politics in the shadow of the gun: revisiting the literature on ‘Rebel-to-Party Transformations’ through the case of Burundi
Bibliographic record
Abstract
This article provides a critical review of ‘rebel-to-party transformation’ scholarship. It shows how three flawed assumptions have underpinned much of the literature: (1) an ideal-typical differentiation between rebel group and political party as distinct by their use or rejection of violence; (2) the analysis of armed conflict as breakdown of ‘normal’ politics, and the study of ‘rebel-to-party conversions’ as a gradual, natural shift from violence back to politics; (3) a failure to integrate the study of rebel legacies into an examination of broader authoritarian legacies. These assumptions have clouded our understanding of politico-military organizations in conflict-torn societies, which combine social protest, armed rebellion, political violence, and party politics throughout their history. Drawing on the ‘no peace, no war’ and ‘armed politics’ paradigms, this article revisits these assumptions through the case of Burundi.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.035 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".