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A Model Discipline - Political Science and the Logic of Representations (Hardcover)
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A Model Discipline - Political Science and the Logic of Representations (Hardcover)
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Political 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.
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