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National survey data demonstrate that support of the federal government decreased substantially between 1964 and 1970. Policy preference, a lack of perceived difference between the parties, and policy dissatisfaction were hypothesized as correlates of trust and alternative explanations of this decrease. Analysis revealed that the increased distrust in government, or cynicism, was associated with reactions to the issues of racial integration and U.S. involvement in the Vietnam war. A curvilinear relationship was found between policy preference on these and other contemporary social issues and political cynicism. The minority favoring centrist policies was more likely to trust the government than the large proportion who preferred noncentrist policy alternatives. This complex relationship between trust and policy preference is explained by dissatisfaction with the policies of both political parties. The dissatisfied noncentrists formed highly polarized and distinct types: "cynics of the left," who preferred policies providing social change, and "cynics of the right," who favored policies of social control.

Political scientists use randomized treatment assignments to aid causal inference in field experiments, psychological laboratories, and survey research. Political research can do considerably better than completely randomized designs, but few political science experiments combine random treatment assignment with blocking on a rich set of background covariates. We describe high-dimensional multivariate blocking, including on continuous covariates, detail its statistical and political advantages over complete randomization, introduce a particular algorithm, and propose a procedure to mitigate unit interference in experiments. We demonstrate the performance of our algorithm in simulations and three field experiments from campaign politics and education.

Describes the Political Science department's assessment activities for academic year 2015-2016. ; The department reports on its loop closing measures in response to past years' assessments and analyses, focused on the updating and revision of the existing undergraduate and graduate curricula to align with new departmental strengths and interests, as well as revisions to the program SLOs in response to internal analyses of past assessments (including barriers to effective assessment). A discussion of the proposed PSLOs, including one specifically addressed to diversity, is included. Plans for AY 201617 include a finalizing of the proposed PSLO revisions and indirect assessments of student success rates to gauge the opportunity gap among Political Science majors.

ABSTRACT
ChatGPT has captured the attention of the academic world with its remarkable ability to write, summarize, and even pass rigorous exams. This article summarizes the primary concerns that political science faculty have about ChatGPT and similar AI software with regard to academia. We discuss results of a national survey of political scientists that we conducted in March 2023 to assess faculty attitudes toward ChatGPT and their strategies for effectively engaging with it in the classroom. We present several assignment ideas that limit the potential for cheating with ChatGPT—a primary concern of faculty—and describe ways to incorporate ChatGPT into faculty teaching. Several suggestions for syllabi that address political science students' use of ChatGPT also are provided.