Punishing and toxic neighborhood environments independently predict the intergenerational social mobility of black and white children

Abstract

We use data on intergenerational social mobility by neighborhood to examine how social and physical environments beyond concentrated poverty predict children’s long-term well-being. First, we examine neighborhoods that are harsh on children’s development: those characterized by high levels of violence, incarceration, and lead exposure. Second, we examine potential supportive or offsetting mechanisms that promote children’s development, such as informal social control, cohesion among neighbors, and organizational participation. Census tract mobility estimates from linked income tax and Census records are merged with surveys and administrative records in Chicago. We find that exposure to neighborhood violence, incarceration, and lead combine to independently predict poor black boys’ later incarceration as adults and lower income rank relative to their parents, and poor black girls’ teenage motherhood. Features of neighborhood social organization matter less, but are selectively important. Results for poor whites also show that toxic environments independently predict lower social mobility, as do features of social organization, to a lesser extent. Overall, our measures contribute a 76% relative increase in explained variance for black male incarceration beyond that of concentrated poverty and other standard characteristics, an 18% increase for black male income rank (70% for whites), and a 17% increase for teenage motherhood of black girls (40% for whites).

The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility

“…For researchers, the Opportunity Atlas provides a tool to study the determinants of economic opportunity. For example, recent studies have used the Opportunity Atlas data to analyze the effects of lead exposure, pollution, and neighborhood redlining on children's long-term outcomes (Manduca and Sampson 2019, Colmer et al 2019, Park and Quercia 2020. Other studies use the Atlas statistics as inputs into models of residential sorting (Aliprantis et al 2019, Davis et al 2019 and to understand perceptions of inequality (Ludwig and Kraus 2019).…”

Language’s vanishing act in early literacy education

“…A toddler in a low-income home is more likely to have one parent instead of two and may therefore encounter that much less direct language interaction. Due to lower access to quality pre- and neonatal health care, the child is more likely to suffer from hearing impairments and other health hazards (Manduca & Sampson, 2019). Said child is more likely to live in a low-income neighborhood and thus be less likely to have access to quality preK education or day care, or even full-day kindergarten (Storch & Whitehurst, 2002).…”

No support for the genetic hypothesis of the Black-white achievement gap using polygenic scores and tests for divergent selection

“…One reason for this is that the scores might be biased by a variety of factors, including the non-random ways that society is geographically structured . For instance, Black people in the US, for reasons unrelated to genetics, live in areas with poorer air quality and more exposure to environmental toxins 39 . Polygenic scores are also known to be biased by the non-random ways that people choose their spouse/partner (assortative mating 40 ); the ways that genes interact with different environments (gene-environment interaction [41][42][43] ); or 7 160 165 170 175 180 differences in genetic features that genome-wide association studies rely on, which create the illusion of systematic differences between African and non-African populations (linkage disequilibrium, genetic drift, epistasis and ascertainment bias 32,44,45 ).…”