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Appendix B: Abstracts of Background Papers
Pages 105-108

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From page 105...
... Third, correlations, models, and frameworks are just more data, not explanations, and -- to explain such data -- one has to tell stories. An interpretive social science suggests lessons for policy makers.
From page 106...
... This challenge of evaluation is not just one of usability and usefulness for technologies but extends to the assessment of how new modeling and simulation technologies shape human and organizational judgment. The robust and systematic evaluation of organizational decision-making processes, and the role of computational modeling and simulation technologies therein, are a critical problem for the organizations that promote, fund, develop, and seek to use computational social science tools, methods, and techniques in high-consequence decision making.
From page 107...
... Finally, the use of domain experts in problem solving is discussed, including why it is an important approach for solving social system problems. THE DANGERS OF RUSHING TO DATA: CONSTRAINTS ON DATA TYPES AND TARGETS IN COMPUTATIONAL SOCIAL MODELING AND SIMULATION Jessica Glicken Turnley By the time most modeling projects address data, the project team has made significant decisions in the course of the project that determine the type of data they need and constrain which part of a comprehensive picture they will provide.


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