Rising to the Top: Armed Group Consolidation in Civil Wars and Fragile States
Abstract
Proposal Title: Rising to the Top: Armed Group Consolidation in Civil Wars and Fragile States Problem: We propose to investigate consolidation processes among non-state armed groups in fragmented conflicts and fragile states. The proliferation of rebels and militias is a prevalent feature of modern civil wars, insurgencies, and weakly governed spaces. While recent scholarship has studied the causes and consequences of militant fragmentation, the reverse process, in which power that is dispersed among many non-state armed groups becomes concentrated among one or a handful of factions, has been neglected. Approach: Our effort will integrate theory development, data collection, qualitative and statistical analysis, network analysis, and computational modeling. We will study consolidation at both factional and conflict levels of analysis. At the factional level, we will investigate how the mode of consolidation Ð coercive, cooperative, or competitive Ð depends upon the nature of the conflict (e.g., insurgency, civil war, secessionist, resource, ethnic) and factors such as political institutions, ideology, and foreign state sponsorship. We will also address which consolidation mode is more stable, more likely to produce a hegemonic faction, or more successful at achieving political goals. Conflict-level questions include the factors that lead to particular stable distributions of power (e.g., hegemonic, bipolar, multipolar), the triggers of consolidation such as external military intervention, and endogenous patterns of consolidation. Empirically, we will (1) conduct eight in-depth studies of historical cases and ongoing cases of major concern to US national security and (2) assemble a cross-national dataset for large-n analysis. The case studies will be used to elucidate causal mechanisms, to generate high resolution data on armed groups, and for within-case comparison of consolidation behavior. The cross-national dataset will be used to establish a general empirical basis for our theorized behaviors. Methodologically, we will analyze the case study data qualitatively and using network analytic and other quantitative methods. The cross-national dataset will be analyzed using standard statistical methods and machine learning methods. We will also develop computational models of consolidation processes within a network dynamics and complex systems framework, which will aid theory development and be quantitatively applied to the data. Scientific Impact: By investigating an important and highly understudied aspect of civil conflict Ð consolidation among non-state armed groups Ð we will forge new fundamental theoretical and empirical ground in the study of civil wars and weakly-governed regions and set an agenda for future research. The unique data we generate will be made publicly available to advance future research. Our project will also further demonstrate the power of network analytic methods for investigating militant group dynamics. We expect that our network-based models will advance the formal modeling of alliance and conflict dynamics among a multiplicity of armed groups and also contribute to network science efforts at modeling cooperation and conflict. We anticipate that our approach of developing models that can be quantitatively implemented upon empirical data will spur new theory and improve the ability to anticipate conflict dynamics.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 10, 2019
- Source ID
- W911NF1910291
Entities
People
- Michael Gabbay
Organizations
- Army Contracting Command
- United States Army
- University of Washington