Civil War Tycoons: Explaining Rebel Group Entrepreneurism in the Myanmar Civil War
Bibliographic record
Abstract
Why do some rebel groups invest in large, capital-intensive businesses in the formal market whilst fighting the state during civil wars? What purpose do they serve in rebel groups’ strategy in engaging with the state during war? Drawing from a comparative analysis of rebel groups active in Myanmar, I argue that rebel groups establish capital-intensive formal businesses to send a costly signal to demonstrate their credible commitment to maintaining a cooperative relationship with the state when they are interested in establishing a relationship where there is neither war nor peace. Dubbed symbiotic armed orders, such relationships develop when rebel groups are interested in moderating the level of violence with the state but wish to continue using warfare and violence as a mode of political interaction and engagement with other political actors. In symbiotic armed orders, rebel groups continue to operate business as usual to enhance their bargaining power against the state. They continue to enhance and maintain their military and administrative capacity and fight the state on the battlefield despite political settlements to mitigate the violence between them. Capital-intensive formal businesses maintain symbiotic armed orders as a costly signalling mechanism. It displays the rebel group’s credible commitment to a cooperative relationship with the state despite continued violence by making both a large lump-sum concession and continued concessions over time to maintain the quality of the sender’s credible commitment. Such signals are rigorous enough to withstand repeated violations of agreed settlements caused by frequent fighting and refusal to demobilise for peace. I find support for this argument by comparing three rebel groups active in Myanmar – the Restoration Council of Shan State, the Karen National Union, and the KNPP – studied through 12 months of qualitative field research on the Thai-Myanmar border. The dissertation builds on semi-structured interviews with rebel elites and observation data from rebel-held strongholds.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".