Abstract

Abstract How can historical perspective be brought to the quantitative social sciences? The question has proven immensely popular, but answers that deal squarely with historical context and narrative remain elusive. An important recent book by Gregory Wawro and Ira Katznelson—Time Counts—provides an important new direction and a kit of useable tools. Using Wawro and Katznelson's approach and methods puts social scientists in a better position to appreciate the historicity of their data and to avoid common errors in statistical execution and inference. Time Counts also raises questions every bit as vital as those it answers, especially when it comes to the boundaries between narrative and quantitative work. An important concern is that inference from a particular historical setting (or what I call a “regime”) cannot be reduced to a special case of inference from large-sample statistics. Historical judgment is at least partially incommensurable with the idea of probability, cases are often important precisely because they are not countable, and scientific rigor may demand avoiding quantification for part of the social scientist's approach.

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