Spring 2019

The importance of early childhood (ages 0-8) is well established, but less is known about the educational, community, and social services interventions that can set children on successful long-term paths. The Early Childhood Initiative (ECI), established by the Center for Child and Family Policy, seeks to bring together scholars from across Duke to address these challenges and produce world-class scholarship that will help maximize the potential of all children during the early childhood years. ECI Seminar Series speakers will range across disciplines but will share an interest in bringing cutting-edge science to bear on policies affecting young children. This is the first talk in the series.

UCLA'S Rodrigo Pinto examines a range of questions regarding social experiments concerning young adults: inference under compromised randomization, cost-benefit analysis, external validity and impact evaluation. He also discusses the economics of human capital accumulation of early childhood interventions, policy evaluation, and causality.

James S. House is the Angus Campbell Distinguished University Professor of Survey Research, Public Policy and Sociology. His primary appointment is in the Survey Research Center, the Institute for Social Research, with a joint retention appointment in Sociology in addition to his primary academic appointment in Public Policy. His research has focused on the role of social and psychological factors in the etiology and course of health and illness, including the role of psychosocial factors in understanding and alleviating social disparities in health and the way health changes with age. He has been elected to the American Academy of Arts and Sciences, the Institute of Medicine, and the National Academy of Sciences. At the Ford School he teaches courses in socioeconomic policy and health policy. In the last decade, Jim co-edited Making Americans Healthier: Social and Economic Policy as Health Policy (2008, with Bob Schoeni of the Ford School and others) and A Telescope on Society: Survey Research & Social Science at the University of Michigan and Beyond (2004, with others). He received his BA in History from Haverford College, his Ph.D. in Social Psychology from the University of Michigan, and taught at Duke University before joining University of Michigan faculty in 1978 and the Ford School in January 2008.

Using individually linked data for all RI children born between 1991 and 2005 that includes early childhood blood lead levels, in-school disciplinary infractions and juvenile detention, Anna Aizer examines the impact of early lead exposure on future delinquency. She discusses how exposure to lead is associated with a significantly greater likelihood of in-school disciplinary infractions and juvenile detention.

Oxford University's Melinda Mills discusses her projects, which combine demographic, sociological, biological and molecular genetic research to study the life course.

In recent years, polygenic scores have become the favored tool for summarizing the influence of genetic predispositions on phenotypic characteristics and behavior when the genetic effect arises from the accumulation of small effects from a potentially very large number of genetic markers. Columbia University's Thomas DiPrete discusses the potential use of polygenic scores as proxies for unobservables in the context of a returns to schooling estimation.

Research computing has changed dramatically in the last few years, and those changes are reshaping how Duke provides research computing support to Duke researchers. The scope and characteristics of computing for research has long come in "large packages" that have unyielding rules and restrictions -- to which researchers conformed their research projects. Increasingly, the emphasis has shifted, so that researchers now have the opportunity to tailor computing resources to fit their particular needs. Duke's Mark DeLong explores this transformation in research computing and presents offerings that Duke Research Computing has developed.

In the past few years, the Social Science Genetic Association Consortium (SSGAC) has been conducting large-scale genome-wide association study (GWAS) meta-analyses of behavioral phenotypes, including educational attainment, subjective well-being (i.e., happiness), and fertility. Dan Benjamin reviews the results of these studies and also provides some background on the SSGAC and discusses ongoing work-in-progress.

Social status is one of the strongest predictors of disease risk and mortality in humans, and may influence Darwinian fitness in social mammals more generally. Duke's Noah Snyder-Mackler discusses how his study combined genomics with a social status manipulation in female rhesus macaques to investigate how status alters immune function. He also reviews how his findings provide insight into the direct biological effects of social inequality on immune function, thus contributing to an improved understanding of social gradients in health and the evolution of social hierarchies.

Elizabeth Bruch discusses how she applied rich activity data from a large, U.S. online dating site to examine how population composition interacts with mate-seeking behavior to shape men and women's romantic outcomes. She also reviews how local markets shape dating experiences both directly, by constraining the type and number of people one is exposed to, and indirectly, through the dynamic interplay between human behavior and experience.