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From Commune to Household: Statistics and the Social Construction of Chaianov’s Theory of Peasant Economy DAVID DARROW University of Dayton Categorization plays an integral part in how we see and interpret the w orld. This is especially true when we attempt to comprehend the complexities of human society, where the heterogeneity of human activity across time and space de- mands that some criterion (class, gender, age, profession, etc.) be used to re- duce the number of variables examined. From the mid-nineteenth centuryas statistics evolved from the simple “political arithmetic” of tax collectors and army recruiters into a potential science of human behaviorcategorizing the population became a contentious issue that reflected the social and political agendas of data collectors. 1 At the same time, when data refused to be molded to researchers’ assumptions, the task of putting people and their activities into analytical categories challenged the validity of the categories themselves. In this way , statistical representations and categories became socially c onstructed knowledge. Attempts by Russia’s zemstvo statisticians to discover underlying “universal laws” of peasant society illustrate this tension in the process of collecting data and categorizing it for analysis. 2 These attempts reflected researchers’ as- sumptions and necessitated a shift in the way they perceived the ir subject. What began as investigations of the Russian peasant’s repartitional land commune (mir or obshchina) soon shifted focus to individual peasant households. An ex- amination of this process reveals the socially constructed nature of the house- hold model of peasant economy offered in the work of A. V . Chaianov a nd oth- ers of the so-called Organization and Production School. 3 On one hand, his approach to understanding the dynamics of the peasant economy differed sub- 788 0010-4175/01/788 –818 $9.50 © 2001 Society for Comparative Study of Society and History The ACTR-State Department Program for Research Scholarship in Russia and the University of Dayton Research Council provided generous funding for this research. The comments of Steven Hoch, Scott Seregny, and Tom Halverson were very helpful in refining the argument. I offer my deepest thanks in this regard to the editors at CSSH andespeciallyto the manuscript’s anony- mous reviewers. Errors that may remain are, of course, my own.
