A Model Discipline: Political Science and the Logic of RepresentationsPolitical science is an intensely quantitative discipline, and models are central. Political scientists use models—formal and informal, statistical and qualitative—to investigate and illuminate causal mechanisms, generate comparative data, and understand the conditions under which certain outcomes are expected to occur. But even though the use of models has grown dramatically in the discipline, there is very little understanding among political scientists of the role or function that models play in the scientific enterprise more generally. Moreover, theoretical models and empirical models have traditionally been treated as separate (hence the division between theorists and empiricists). Today, however, the emphasis is on using models to generate testable predictions that serve as hypotheses for subsequent data analysis. But how do we justify and rationalize the method? Why test predictions from a deductive, and thus truth-preserving, system? David Primo and Kevin Clarke tackle these central questions in this novel work of methodology. They argue that the lack of a suitable justification for model testing is not the only reason to revisit the role of models in political science. Most importantly, they contend that models should be seen as 'objects' and thus neither true nor false. Rather, they should be evaluated in the same fashion as models are evaluated in the physical sciences—good models are useful for particular purposes. Nothing more, nothing less. Divided into two parts, the book first establishes that no social scientific endeavor is philosophy-free. The second part focuses on different types of models, and closes with a framework for integrating theoretical and statistical models. |
Contents
1 A Model Discipline | 1 |
2 The Science in Political Science | 20 |
3 What Is a Model? | 52 |
4 Theoretical Models | 78 |
5 Empirical Models | 104 |
6 Explanation | 134 |
7 Conclusion | 168 |
Notes | 182 |
Bibliography | 190 |
Name Index | 206 |
212 | |
Other editions - View all
A Model Discipline: Political Science and the Logic of Representations Kevin A. Clarke,David M. Primo No preview available - 2012 |
Common terms and phrases
analysis answer approach argue argument assumptions authors bargaining Boston causal chapter choice claim compared Conception concerns conclusion confirmation connection Consider construct deductive demonstrate depends derived describe discipline discussion distributive Economic empirical models evaluation event evidence example exist explanation fact false figure formal given goal Green hypothesis idea implications important interested issue legislative logical means measurement mechanism method nature noted null objects observation particular philosophy political science political scientists positive possible practice precisely prediction Press probability problem proposal question rational Rational Choice Theory reasons refers regarding relationship represent Review role rules scholars scientific sense similar simple social specific statement statistical statistical model structure testing theoretical models theory testing true understanding University variables voters voting write