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Blocking the Future: New Solutions for Old Problems in Historical Social Science

Published online by Cambridge University Press:  04 January 2016

Peter Bearman ,
Robert Faris  and
James Moody
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Extract

The only true voyage would be not to travel through a hundred different lands with the same pair of eyes, but to see the same land with a hundred different pairs of eyes.

Marcel Proust

Although it may turn out to be otherwise, this is an early article in what is hoped to be a larger series of studies in the application of network methods to historical problems. This article explores some new solutions to old problems in historical social science and history more generally and provides some templates for thinking about an old problem in a new light. The old problem is the problem that arises when one considers how we know what historical events mean and how we can have confidence in our interpretations. For many social science historians, the problem of meaning is secondary to the problem of making causal arguments. And often the practical reality of much historical work is that more mundane problems of data and evidence often consume an unusual amount of time and energy, drawing attention away from the luxurious concerns discussed in this article — concerns with what things actually mean. Despite the recognition that the problem of meaning may not lurk around every corner for all social science historians, the goal of this article is to propose some new strategies for determining what things mean in historical context.

Type
Special Issue: What Is Social Science History?
Information
Social Science History , Volume 23 , Issue 4 , Winter 1999 , pp. 501 - 533
Copyright
Copyright © Social Science History Association 1999 

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Footnotes

We have benefited from the comments of Craig Calhoun, Roger Gould, Katherine Stovel, John Padgett, and Charles Tilly. Harrison White read an early draft of many of the ideas discussed in this article and made substantial contributions too deep to easily acknowledge. Papers that explored similar problems were presented at the University of Washington, the Chicago Business School, the Stanford Business School, New York University, Princeton University, and the Center for Social Sciences at Columbia University. We thank Margaret Levi, Edgar Kiser, Joel Podolny, Doug Guthrie, Paul DiMaggio, and Jesper Sorenson for providing these opportunities. Douglas White’s foundational work on bicomponents provided the impetus for many of the basic technical ideas we have pursued, and we gratefully acknowledge his important contributions. Finally, we thank Paula Baker for her support and encouragement. Address all correspondence to the senior author: Peter Bearman, Institute for Social and Economic Theory and Research, 801IAB, Columbia University, New York, NY 10027. E-mail: [email protected].

The figures in this article were done in Pajek, a software program created by Vladimir Batagelj and Andrej Mrvar, available on the World Wide Web.

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