A cross-national study, 49 samples in 38 nations (n = 4,344), investigates whether national peace and conflict reflect ambivalent warmth and competence stereotypes: High-conflict societies (Pakistan) may need clearcut, unambivalent group images distinguishing friends from foes. Highly peaceful countries (Denmark) also may need less ambivalence because most groups occupy the shared national identity, with only a few outcasts. Finally, nations with intermediate conflict (United States) may need ambivalence to justify more complex intergroup-system stability. Using the Global Peace Index to measure conflict, a curvilinear (quadratic) relationship between ambivalence and conflict highlights how both extremely peaceful and extremely conflictual countries display lower stereotype ambivalence, whereas countries intermediate on peace-conflict present higher ambivalence. These data also replicated a linear inequality-ambivalence relationship.stereotypes | peace | conflict | inequality | ambivalence

By means of evidence-driven and declaratively implemented social simulation, we grow qawm — solidarity networks in Afghanistan. The study of qawm lends insight into the structural and processual dynamics of Afghan society. In particular, we concentrate on the evolution of power structures. An agent-based computational model is presented whose ontology borrows from neopatrimonialism, a notion of power prevalent in contemporary conflicts. In this model, agents' structural arrangement, behavior and cognition are informed by qualitative data derived from case studies on Afghanistan. The simulation results suggest that the emergence of qawm and, hence, the fragmentation of Afghan society are systemic and lead to a constant drain of resources. Cross-validation between the simulated network and a target system network reveals that qawm exhibit small world characteristics.

We present a simulation model of current conflict-torn Afghanistan in which a system-dynamics model is coupled with an agent-based model. Agent-based modeling techniques are applied to model individual cognition and behavior as well as group formation processes. System-dynamics modeling is used for representing macro conflict processes, such as duration of violence and combat success ratio. The cognitive and behavioral processes are couched in a socio-cultural context and feed into the system dynamics processes. This affords us exploring the relationship between local socio-culturally-driven cognition and behavior and (dynamic) macro properties of armed conflict. We demonstrate the importance of analyzing conflict-torn Afghanistan from an interplay of adapting ''traditional'' socio-cultural mechanisms, political culture and power structures, and politico-economic macro-processes. We find that variations in the conflict's superstructure can be explained through variations in socio-culturally dependent structures. The model indicates limitations with regard to classical prediction, but is promising with regard to explanatory-driven pattern forecasting.In Afghanistan, ''traditional'' modes of warfare merge with contemporaneous modes of guerrilla warfare (Roy 1994) 1 . This does not only apply to warfare in a narrow, tactical sense, but also in a wider dimension encompassing the conflicttorn Afghan society. We argue that the socio-cultural dimension is important in creating an understanding of conflict in general and, more specifically, current Afghanistan. The aim of the research at hand is to investigate the role of sociocultural factors in the production of conflict. For this reason we investigate the following two general questions: What are the inter-relations between socio-cultural and -political patterns and macro-properties and -outcomes of armed conflict? Can we infer from knowledge about cultural traits to patterns of future conflict outcomes?International Studies Review (2010) 12, 8-30 For the purpose of this article, culture is understood as a set of shared attitudes, values, goals, and practices that characterizes an institution, organization or group. We understand as political culture a repertoire of cognitive, behavioral, and normative patterns in the production of power as well as in the organization of groups for the pursuit of cooperation and conflict. Whereas the sphere of the cultural has for long been of interest to both, anthropologists and political scientists that are interested in conflict (for example, Ferguson 1990;Snyder 2002), formal models of conflict taking into account the socio-cultural sphere are to the best of our knowledge non-existent.However, explanations for who interacts with whom, how, when, and why can be (partially) explained in terms of (political) culture through the idea of individual action selection. Issues of (political) culture also stand at the core of group and alliance formation as well as group interaction processes (for example, Hannan and Freeman 1977;Morril...

In many computational social simulation models only cursory reference to the foundations of the agent cognition used is made and computational expenses let many modellers chose simplistic agent cognition architectures. Both choices run counter to expectations framed by scholars active in the domain of rich cognitive modelling that see agent reasoning as socially inherently contextualized. The Manchester school of social simulation proposed a particular kind of a socially contextualized reasoning mechanism, so called endorsements, to implement the cognitive processes underlying agent action selection that eventually causes agent interaction. Its usefulness lies in its lightweight architecture and in taking into account folk psychological conceptions of how reasoning works. These and other advantages make endorsements an amenable tool in everyday social simulation modelling. A yet outstanding comprehensive introduction to the concept of endorsements is provided and its theoretical basis is extended and extant research is critically reviewed. Improvements to endorsements regarding memory and perception are suggested and tested against a case-study.

Knowing how to send and interpret signals is an essential part of both diplomacy and war. Political scientists have recognized that costly signalsgestures and actions that involve significant cost or risk-are central to politics and diplomacy since modeling doyen James Fearon built his Ph. D. thesis around the concept in the 1990s. Because these signaling systems are pervasive in nature (many of these strategies arise independently and repeatedly to solve common problems suggesting evolutionary pressure to select strategies offering the most success at the least cost), their underlying strategic logic has important implications to foreign policy challenges we face today. By capitalizing on solutions derived by evolution over 3. 5 billion years of life on Earth, we may identify ideas that otherwise might not have been explored in a policy context potentially offering quick, novel, and effective options to increase strategic and combat effectiveness. Here we present 8 lessons from evolution for political science.