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The Fragile Families Challenge: Predictability of Family and Child Well-being in Adolescence

Sun, August 12, 10:30am to 12:10pm, Philadelphia Marriott Downtown, Level 4, Franklin Hall 8

Abstract

Scholars have long hypothesized that childhood experiences play an important role in the process by which socioeconomic status is reproduced across generations. The predictive power of attainment models, however, has been so weak that pioneers of the field have commented that random chance must play an important role. We hypothesize another possible source of poor predictive performance: untapped modeling potential. Modern machine learning approaches often yield better predictions than parametric regression models, yet social scientists have not fully exploited this opportunity. In this paper, we report on how 159 research teams from 68 institutions in 7 countries used rich survey data covering 2,121 training observations on 12,942 variables to produce predictive models that together set a benchmark of predictive performance for outcomes identified by social scientists as important factors in the status attainment process. We narrow our focus to a critical point of the life course: predicting adolescent outcomes as a function of childhood experiences. Each team developed a predictive model that was evaluated on a set of outcome observations available only to the organizers. Results suggest that (a) predictive performance outpaced approaches more common in social science, but (b) overall predictive performance was poor. We close with a discussion of the potential reasons for poor predictive performance in social science research. Given the theoretical importance of childhood experiences in the process of stratification, our results should be of interest to scholars of stratification, socio-economic mobility, child development, and statistical methods.

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