Recognizing Patterns of Anomie that Set the Conditions for Insurgency

Abstract

New challenges to analysis, modeling and simulation have arisen in recent years as decision-makers and policy makers seek a better understanding of human social culture behavior. The Office of Naval Research has tasked a team of researchers to investigate the specific question of the relationship between the well-established theory of anomie and the emergence of insurgency. This project proposes to identify patterns of anomie that set the conditions for insurgency, categorize the events that trigger the start of an insurgency, and simulate the path of a nation state from peace into political violence using wargaming and modeling. Anomie — the loss of compelling norms that enable populations to meaningfully interpret social change — threatens nation states with instabilityinduced conflict. Nation-states that experience anomie-induced conflict are similar in that they share common factors that make them susceptible to insurgency. We will utilize pattern classification algorithms to identify associations of conditions to outbreaks of insurgency. The presence of anomie alone does not lead to insurgency, but helps establish conditions upon which pivotal events trigger the political violence. Micro-level analysis will complement macrostructural concept and data analysis. The research will develop case studies for nation-states that have suffered insurgency to understand the types of triggers that were involved. Understanding the roots of anomie that set the conditions for insurgency and the triggers that initiate the violence will enable creation of wargames and models to examine the onset of an insurgency and develop mitigation strategies. These allow vicarious learning for decision makers to experience the onset of an insurgency before the first shot is fired, providing time and understanding to potentially prevent or mitigate the outbreak of the violence in real-world regions of interest. The project’s multi-level approach offers a needed methodological step forward, and its outputs include new empirical grist for fellow scholars and field practitioners. This paper provides an overview of the project and proposed methodology, as well as progress to date and planned go-forward efforts. Moreover, the paper will serve as a representative example of exploration into social theories, real-world data collection, and various modeling approaches to stimulate SISO community consideration of the need for model and data standards in the area of human social culture behavior (HSCB) modeling.