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mini-course: Modeling Emergence: Computer Simulation as a Theory-Building Tool,

Description: Much quantitative social science and behavioral research has focused on identifying statistical relationships in cross-sectional data. While rigorous and tractable, this research typically assumes the objects of study are independent of one another, and thus assumes away the complex social processes that we hope to understand. Qualitative (ethnographic and comparative-historical) lenses have allowed us to view the social world as a web of interdependent and contingent processes, with macro-level cultures, communities and organizations emerging from and constraining the micro-level interactions of individuals, relationships and families. An explosion of recent work has used computer simulation to think systematically and rigorously about these complex social dynamics. Simulation research can offer rich, nuanced process models similar to qualitative work, but employs a rigorous, transparent and replicable framework that can be extended to other research contexts, similar to statistical approaches. Theorists use computer models to elucidate, extend, integrate and validate social theory. Policy analysts use computer models to predict outcomes of policy scenarios in complex and interactive domains. Managers use computer models to design efficient and robust organizational operations and implement effective interventions. This proliferation of simulation work has generated great interest in computer modeling methods, but few disciplinary departments presently offer general training in this area. This introductory workshop will allow attendees to understand some of the overall goals and methods of social simulation, give them hands-on experience in experimenting on models, and point them to resources to begin using these tools in their own work.

https://www.umass.edu/issr/events/issr-summer-methodology-workshops-mode…

Location: 
University of Massachusetts, Amherst
Event Dates: 
Tue, 08/29/2017 to Wed, 08/30/2017
Submission Deadline: 
Fri, 08/25/2017
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