The Future of Political Science: 100 Perspectives
Gary King, Kay Schlozman, Norman Nie. 2009.
"The Future of Political Science: 100 Perspectives".
Routledge Press, New York.

Abstract
This book contains some of the newest, most exciting ideas now percolating among political scientists, from hallway conversations to conference room discussions. To spur future research, enrich classroom teaching, and direct non-specialist attention to cutting-edge ideas, a distinguished group of authors from various parts of this sprawling and pluralistic discipline has each contributed a brief essay about a single novel or insufficiently appreciated idea on some aspect of political science. The one hundred essays are concise, no more than a few pages apiece, and informal. While the contributions are highly diverse, readers can find unexpected connections across the volume, tracing echoes as well as diametrically opposed points of view. This book offers compelling points of departure for everyone who is concerned about political science—whether as a scholar, teacher, student, or interested reader.
See Also
- [Paper] The 'Math Prefresher' and The Collective Future of Political Science Graduate Training (2020)
- [Paper] The Science of Political Science Graduate Admissions (1993)
- [Presentation] Empowering Social Science Research With Industry Partnerships (Dean's Symposium on Social Science Innovations, Harvard) (2021)
- [Presentation] Empowering Social Science to Understand and Ameliorate Major Challenges of Human Society (Federal Interagency Conference on Social Science and Big Data) (2020)
- [Presentation] The Next Big [Social Science] Thing. Some Suggestions for Science Magazine (2015)
- [Paper] From Preserving the Past to Preserving the Future: The Data-PASS Project and the Challenges of Preserving Digital Social Science Data (2009)
- [Paper] Archive of the Controversy Involving Wendy K. Tam Cho, Brian J. Gaines, and the American Political Science Review (2002)
- [Paper] Analyzing Incomplete Political Science Data: An Alternative Algorithm for Multiple Imputation (2001)