Sociocultural Data to Accomplish Department of Defense Missions Toward a Unified Social Framework: Workshop Summary (2011) / Chapter Skim
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7 Modeling Sociocultural Behavior
7 Modeling Sociocultural Behavior
Pages 73-82
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From page 73... ...
. During the panel discussion, each paper author -- Laura McNamara, Mark Bevir, Robert Sargent, and Jessica Glicken Turnley -- gave a short overview of his or her paper; Albro, who had prepared a response paper in advance, then commented on the papers, summarizing and synthesizing their main points; and, finally, the workshop participants were given the opportunity to ask questions and to make comments.
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From page 74... ...
Robert Sargent of Syracuse University noted that there are two major types of models: causal models and empirical models. Causal models require sufficient knowledge about the system being modeled, including how the system works, the relationships among the various components of the system, theories about the functioning of different components, and so on.
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From page 75... ...
One of the clear themes that emerged from this panel was the difficulty -- or impossibility -- of separating a model of sociocultural knowledge and behavior from the people and organizations that have developed it. For example, Jessica Glicken Turnley of the Galisteo Consulting Group, Inc., and the Joint Special Operations University noted, in discussing her paper, "The Dangers of Rushing to Data: Constraints on Data Types and Targets in Computational Social Modeling and Simulation," that a model is not a representation of the entire world.
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From page 76... ...
In fact, models are given a primary role in moving ‘from data to decision.' A danger here is that computational models acquire too large a role in decision making, rather than being understood as merely one feature among many of complex interpretive environments." A better way to think about models of sociocultural knowledge and behavior, he said, is as part of a larger process in which models, modelers, and users interact. In particular, one should recognize that the key stakeholders in modeling are "meaning makers." Models should not be thought of as "approximations of poorly understood sociocultural realities but as theory-driven, partial and selective representations" that can help decision makers "generate new scenarios and new stories, to become parts of the encompassing and dialogically interpretive scene of decision making.
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From page 77... ...
But if the data are the more rich sociocultural data discussed by McNamara and Bevir, inserting them into a model may strip them of some or much of their meaningful content. Turnley specifically addressed this issue in her paper, writing: "Computational models require quantitative data, or (to put it another way)
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From page 78... ...
Albro illustrated this question by comparing the divergent perspectives of Bevir and Sargent concerning what constitutes a meaningful unit of analysis. Bevir's point of view is that any concept or proposition -- as a datum -- does not have "intrinsic properties and objective boundaries" and that explanations of sociocultural phenomena arise from tracing out and understanding the conceptual connections in "webs of belief." This, Albro commented, makes the conceptual boundary between data and meaning hard to locate, which in turn "poses a challenge to any effort to organize information into comparable units or sets, as available for standardized measure, or as subject to some kind of operation or manipulation." Turnley, whose concept of sociocultural knowledge has a great deal of overlap with Bevir's, spoke of analogies as ways in which people interpret the world and thus create meaning, rather than as bits of preexisting knowledge waiting to be discovered.
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From page 79... ...
Relatively ‘thin' and more easily extractable data sources are given priority, such as journalism, national opinion surveys, or polling data." When data are seen in this way, the job of models becomes to generate "significant information about a patchwork world of data points as checked-off cultural boxes representing quantifiable variables of cultural difference." But the results generated from such an approach to modeling the world could well be meaningless, Albro suggested. "There are, in short, epistemological consequences in assuming that cultures can be divided up into vehicles of extractable meaning." It is important that people using models of sociocultural knowledge and behavior grapple with these issues concerning the data used in the models, Albro said, and in particular to think about "the relative compatibility of such different epistemological departure points for data." Judging from some of the earlier presentations at the workshop, Albro said, it seems as though in practice the data used in sociocultural models end up being those data that are easier and most convenient to collect and to put into the models.
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From page 80... ...
If the District Narrative Assessments are to be of use to the modelers, they will have to be created in a standard format with interchangeable categories. But fitting everything into standard formats and defined categories makes it unlikely that "information outside of established expectations would find its way into the data sets of such models," Albro said.
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From page 81... ...
"We're trying to spread narratives when most people's day-today experience of the American presence is going to challenge the narratives we want to spread. And the narratives are not going to spread unless they're plausible to the people we want them to spread among, which means they have to map onto their day-to-day experience of the American presence." It is a phenomenally difficult problem, he said, but models are one tool that may help to figure out how to solve it.
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