Competitive Intervention, Protracted Conflict, and the Global Prevalence of Civil War
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This article develops a theory of competitive intervention in civil war to explain variation in the global prevalence of intrastate conflict. I describe the distortionary effects competitive interventions have on domestic bargaining processes and explain the unique strategic dilemmas they entail for third-party interveners. The theory uncovers the conditional nature of intervention under the shadow of inadvertent escalation and moves beyond popular anecdotes about “proxy wars” by deriving theoretically grounded propositions about the strategic logics motivating intervener behaviors. I then link temporal variation in patterns of competitive intervention to recent decreases in the prevalence and average duration of internal conflicts. The theory is tested with a quantitative analysis of all civil wars fought between 1975 and 2009 and a qualitative case study of the Angolan civil war (1975–1991). My results underscore the importance of a generalizable account of competitive intervention that not only explains past conflicts, but also informs contemporary policy.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it