Policy and Complex Systems
Introduction
The phenomenon of genocide is
complex , as is the task of deriving its definition . According to Verdeja ( 2010 ), it will be difficult to compare theories on genocide until researchers decide on the definition of genocide . While the above task of definition primarily falls upon the shoulders of social scientists and the entities with which they work , it is important in the context of this computational effort to have clear direction . Verdeja ( 2010 ) skillfully surveys a number of related works and specifies what he and others see as flaws in the United Nation ’ s definition of genocide — the primary issue being its reference only to ethnic , racial , national , and religious groups . He points to the lack of recognition of political , economic , and other groups as one of many weaknesses of the definition of genocide ; with the lack of a threshold being another weakness in the definition of genocide because there is no criteria to differentiate mass killings from genocide .
Computational modeling typically requires a simple foundation , and given the lack of consensus , we default to Straus ’ definition of genocide ( Straus , 2012b ). According to Straus ( 2012b ), genocide is any large-scale territory-specific organized form of destruction that targets specific social groups . The above is a general statement , but its simplicity is appropriate for the domain of computational research . Creating a robust and flexible model that produces interpretable results requires stripping away details and focusing only on the most basic building blocks necessary . Given this definition , the next task is to derive a satisfactory framework from which to build a simulation , and a system ( or macro ) level perspective is a logical starting point .
This research attempts to gain new insights and understanding into the fundamental drivers of genocide in order to inform preventative policy decisions . Complexity theory guides the analysis , which begins by exploring the problem at the macro level . This approach produces a broad picture of the large-scale dynamics of genocide . However , given complexity theory ’ s focus on local interactions when examining adaptive systems , the model implementation uses a simplified framework in an agent-based model ( ABM ) for initial exploration of the problem .
Method
System-Level View
A survey of the work of major scholars in the fields of genocide studies shows that the complexity of the problem framework increases with the depth of the research . The causal loop diagram from the field of System Dynamics ( SD ) provides a useful structure for visualizing genocide ’ s system-level framework .
Figure 1 is a simplified causal loop diagram created with Vensim PLE Software ( Version 6.3G ; Ventana Systems , Inc ., 2006 ). It shows a number of relationships and feedback mechanisms . Each variable has a descriptive name and is connected to others by arrows of specified direction and polarization . A positive sign (+) indicates a positive relationship . This means that an increase in the variable at the beginning of the arrow leads to a corresponding increase in the variable at the end of the arrow , and vice versa . A negative sign ( − ) denotes the opposite , with an increase at the beginning of the arrow corresponding to a decrease at the end of the arrow , and vice versa . A positive / negative sign (+/ − ) indicates uncertainty in the nature of the variables ’
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