Event

Distributing Norms: Notes on the Normal Distribution from Quetelet through Kinsey

12-1 pm

PSTC Seminar Room 205

Jennifer Johnson-Hanks, Professor of Demography, UC Berkeley

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Johnson-Hanks will discuss denominators, exposure to risk, and selection into and out of social categories. She begins with an early genealogy of the Normal Distribution in the social sciences in the work of Adolphe Quetelet and Francis Galton, and then turns to the fact that most social distributions are not in fact Normal, contrary to popular assumption. Most social things, and perhaps especially those that are embarrassing, inconvenient, or immoral, are remarkably stable in their distributions, but those distributions are rarely Normal. The last part of her talk will explore how popular assumptions of statistical normalness matter through an analysis of the two most important surveys of American sexual practice of the 20th century:  the Kinsey and the Laumann. The central point is that although social scientists are careful to distinguish statistical from social norms, the Normal Distribution has come to so dominate the popular imagination that social norms are sometimes indeed reflections of statistical ones.

Johnson-Hanks is Professor and Chair of Demography and Professor of Sociology at UC Berkeley. She also directs the NICHD Training Grant in Demography at Berkeley. Her work explores relationships between cultural and population systems: how do values matter for rates, and vice versa? How can we think in an integrated way about individual actions, cultural norms, and population aggregates? She is author of Uncertain Honor: Modern Motherhood in an African Crisis (Chicago, 2006) and the forthcoming book, How We Count: Why Quantitative Social Science Matters, as well as co-author (with C. Bachrach, S.P. Morgan, and H-P. Kohler) of Understanding Family Change and Variation: Structure, Conjuncture, and Action (Springer, 2011).