THE DISCIPLINE OF INFERENCE: Inference, Research Design, and Case Study Methods — Exposition and Critique - Tapa blanda

Sinopsis

What separates a researcher who applies a method from one who understands it?

This book teaches both. Most methodology textbooks hand you a set of rules. The Discipline of Inference does something rarer: it teaches you the rules clearly enough for a beginner to follow them, and then shows you the live controversies underneath each one—so that, before a committee, a referee, or your own conscience, you can defend not just what you chose but why you chose it where the methods disagree.

Built on two interlocking layers, every one of its forty-five chapters opens with a clear, pedagogical exposition and then descends into the debates, limits, and unresolved disputes that the exposition leaves out. You learn process tracing, causal-process observations, case selection, equifinality, falsifiability, and the integration of qualitative and quantitative methods—and then you learn why each of these tools rests on contestable assumptions that no manual can settle for you.

Among the questions the book confronts head-on: Do qualitative and quantitative research truly share a single logic of inference—or does that very thesis smuggle in the statistical template as a universal norm? How can a single, well-chosen case refute a theory that a thousand observations could not? When statistics finds an association but process tracing finds no mechanism, which evidence wins? Why is knowing when not to conclude the highest discipline of inference, not its failure?

Accessible enough for a graduate student approaching research design for the first time, and demanding enough for the experienced scholar who wants the field's deepest fractures laid bare, this is a methodology book that refuses the false comfort of a finished system. It offers instead something more durable: not a set of rules, but a map of problems.

For students and scholars of political science, sociology, public policy, law, and the social sciences who want to do rigorous research—and to know exactly what they are doing while they do it.

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