Daniel Schrage. Organizing Pollution: Organizational Demography, Neighborhoods, and Racial Inequality in Exposure to Toxic Chemicals, 1987-2012

Monday, April 16, 2018 - 2:00pm to 3:30pm
Blumer Room - 402 Barrows Hall

Organizing Pollution: Organizational Demography, Neighborhoods, and Racial Inequality in Exposure to Toxic Chemicals, 1987-2012

Many organizations release toxic chemicals that disproportionately affect residents of African-American and Latino communities. To understand the sources of racial environmental inequality, we must understand what drives differences across organizations in polluting behavior. I draw on recent theories of organizational practices that emphasize the importance of managers to help explain these differences. I examine two related questions: How does racial diversity in an organization's managers affect its polluting behavior, and how does that behavior depend on the racial diversity of the community where the organization is embedded? To examine this, I use longitudinal data on firms' pollution, linked to data on the racial composition of those firms' workers. I find that when organizations are located in predominantly African-American and Latino neighborhoods, adding more African-American and Latino managers makes those firms pollute less. These findings link managers' behavior inside organizations to important resources in the external communities surrounding those organizations.

Dan Schrage is an assistant professor of sociology at the University of Southern California. He received his PhD in sociology from Harvard in 2017. He studies racial inequality in the United States. He focuses in particular on labor-market inequality: how the spatial organization of urban labor markets creates racial inequality in access to employment; how organizations mediate racial inequality in exposure to environmental pollutants; and how organizational hiring and promotion practices affect diversity in those organizations. He also studies mass incarceration, another institution with racial inequality at its core. Finally, he develops novel statistical methods for causal inference, record linkage, change-point analysis, and covariance regression.