November 6-7, 2008
At its May 2007 meeting, the National Advisory General Medical Sciences Council advised the institute to explore the science of modeling social behavior as a potential new program. Social dynamics influence many biological processes of interest to NIGMS, including the organization of genetic information, transmission of disease, development of pharmaceuticals, and expanding the diversity of the scientific workforce. NIGMS is particularly well situated to consider support for mathematical and computational modeling of social behavior.
On November 6-7, 2008, NIGMS held an informational conference to identify obstacles and opportunities in the emerging field of modeling social behavior. The organizing committee selected several specific topics as exemplars of modeling in the social sciences. The purpose of the meeting was explore these areas of research, not in the details of content, but as examples of how concepts emerge, what questions are central, the nature of evidence, how analytical methods and modeling are used, and how the field connects to other disciplines.
On the first day of the meeting, speakers were asked to address the following questions:
The second day consisted of more in-depth discussion of two topics, prejudice and resilience, with the goal of discovering how various modeling and experimental approaches can contribute to understanding these social phenomena.
The NIH Office of Behavioral and Social Science Research supported the videotaping of the meeting (http://videocast.nih.gov).
Speakers agreed that modeling is a powerful tool for studying social processes relevant to NIH's mission, in large part because modeling forces us to make our assumptions explicit. As Josh Epstein pointed out in his introduction, "Anyone who ventures a projection or imagines how a social dynamic would unfold is running some model." Often our models are implicit, based on unstated assumptions, unknown relationships to data, and unverified consequences. Good modeling grows from a close association with empirical data, in which each informs the other.
People often assume that the goal of modeling is prediction. While it may be the case that modeling contributes to forecasting, that is not the only—or even the most important—reason to build models. Models help us explain observations, understand system dynamics, illuminate uncertainties, offer options for interventions, set boundaries of parameters and outcomes, discipline our thinking, and identify new questions. These are valuable, tangible results of applying modeling to social behavior research.
The presentations and workshops raised many important themes and questions, many of which are amenable to modeling approaches. Some of the questions to which mathematical and computational modeling is being applied are highlighted below:
The central themes about the role of modeling in social behavior research emerged:
In particular, the workshops on prejudice and resilience exemplified how knowledge from many levels and many perspectives can be brought to bear on understanding complex social issues. For example, prejudice can be studied as a structural, cultural, social network, individual, or interpersonal phenomenon, all of which are relevant to understanding and addressing disparities in health and access to resources. Resilience deals with the ability of a system (e.g., individual, community, society) to recover from a crisis. The modeling framework for studying resilience comes from ecological modeling and is now being applied to physiological, social, and cultural systems. With the inclusion of many perspectives, our understanding of the underlying theory is also broadening.
John CacioppoThe University of Chicago
Ana Diez-RouzUniversity of Michigan
Joshua EpsteinThe Brookings Institute
Jessica FlackThe Santa Fe Institute
Steve FrankUniversity of California, Irvine
Robert GoldstoneIndiana University
Eric SmithThe Santa Fe Institute
Irene EckstrandNIGMS Staff Organizer
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