Abstract: Researchers have long theorized about the processes through which family background and childhood experiences shape life outcomes. However, statistical models that use data on family background and childhood experiences to predict life outcomes often have poor predictive performance. In this talk, we present results from the Fragile Families Challenge, a scientific mass collaboration designed assess the limits of predictability of life outcomes and improve our understanding of these limits. Using data from the Fragile Fragile Families and Child Wellbeing Study, a high-quality, birth cohort study that has followed thousands of mainly disadvantaged families for the past 15 years, 457 participants built predictive models of six life outcomes, such as a child’s grades in school or whether the family would be evicted from their home. Research participants in the Challenge could use any theoretical, statistical, or machine learning approach they wished and could draw on the more than 12,000 variables that had been measured about the child, parents, and family since the birth of the child. All predictions were evaluated on held-out data. Our empirical results have implications for social science theory, data, and methods and for algorithmic decision-making in high-stakes settings, such as child protective services and criminal justice. [Joint work with Ian Lundberg, Alex Kindel, Sara McLanahan and hundreds of researchers].
The Sociology Seminar Series for Hilary Term is convened by Richard Breen and Janne Jonsson. For more information about this or any of the seminars in the series, please contact firstname.lastname@example.org.