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What do elite policymakers consider when making assessments about national security, particularly about issues of deterrence? Scholarship thus far on this question has been limited to qualitative analyses of smaller sets of documents and formal models that cannot trace dynamics within a state's policymaking apparatus. In this paper, we address this issues by applying computational text analysis to a newly compiled dataset of over 750,000 pages of declassified documents from the National Security Council (NSC) between the Truman and Ford administrations (1947-1977). This represents the largest and most comprehensive collection of NSC documents to date. Supervised learning techniques applied to these texts, in concert with a series of extant measures of diplomatic, military, and political activity, reveal the conditions under which elites in the NSC---the principal forum for issues of American foreign policy---grew most concerned about national security and the United States' ability to deter aggression. This paper and its associated dataset of NSC documents establishes a solid and unprecedented foundation for the study of foreign policy, information aggregation, and group decision-making.
Tyler C. Jost, Brown University
Joshua D. Kertzer, Harvard University
Eric Min, UCLA
Robert Schub, University of Nebraska, Lincoln