A Model Discipline: Political Science and the Logic of Representations

A Model Discipline: Political Science and the Logic of Representations

A Model Discipline: Political Science and the Logic of Representations

A Model Discipline: Political Science and the Logic of Representations

Synopsis

In A Model Discipline, Kevin A. Clarke and David M. Primo turn a critical eye to the methodological approach that dominates modern political science. Clarke and Primo contend that the field's emphasis on model testing has led to a distortion of both the modeling process and the art of data analysis and cannot be logically justified. The authors argue that models should be seen as "objects" and thus regarded as neither true nor false. Models should instead be evaluated for their usefulness for a particular purpose. Divided into two parts, the book first establishes that current practice is not philosophy-free and rests on a number of questionable assumptions. The second part focuses on the different ways that theoretical and statistical models can be useful, and closes with a defensible justification for integrating theoretical and statistical models. A novel work of methodology, A Model Discipline offers a new perspective on long-held assumptions about the way research in the social sciences should be conducted.

Excerpt

This book project began with a question raised by an undergraduate student: Why test deductive models? The question seemed simple, even obvious, but after thinking it through, we decided that it was not so simple. A few years earlier, the Empirical Implications of Theoretical Models (EITM) project had gotten under way, and finding new ways to test theoretical models was all the rage. We felt that a paper exploring the logic of testing theoretical models was in order. After writing that paper, we felt that we had more to say, not only about theoretical models but also about empirical models and the conditions under which the two should be combined. This book is the result.

Many people helped us revise, refine, and improve our argument from its initial incarnation. Sometimes we disagreed with the advice that we received, and sometimes the advice givers disagreed among themselves. Thus, all errors are ours, and ours alone.

Among our colleagues at the University of Rochester, we are particularly indebted to Jim Johnson, who supported this work from the beginning, patiently engaged in seemingly endless conversations about models in political science, and who was gracious enough to read a number of drafts. John Duggan, Mark Fey, Hein Goemans, Gretchen Helmke, Bethany Lacina, Michael Peress, Larry Rothenberg, Curt Signorino, and Randy Stone also provided helpful comments and advice. Our arguments have been sharpened by exchanging views with Rochester graduate students both in seminars and in hallways. Outside the department, we benefited from interactions with Chris Achen, Jim . . .

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