Using Big Data to Understand and Reduce Inequality in Youth Connectedness in an Era of Economic Polarization

Do community characteristics buffer low-income youth from the isolating effects of economic polarization?

the high and low wage work. In this context, youth living in high-poverty areas face structural disadvantages in their spatial and labor market connectedness or in their connection to social environments and economic opportunities that lead to higher wage work. But community characteristics such as tight connections to local organizations or high cohesion may lessen the strains of economic polarization on youth living in high-poverty areas. With this award, Cheng aims to examine the unequal distribution of spatial and labor market connectedness across geographic areas and time, examine the effect of economic polarization on connectedness, determine how much of this effect is mediated by the community context, examine spatial and labor market connectedness among youth in New York City. Cheng will expand her expertise working with mentor Patrick Sharkey, Professor of Sociology and Public Affairs at Princeton University, who will provide mentorship in the analysis of large-scale data and advanced causal inference methods. In addition, Elise Cappella, Vice Dean for Research and Applied Psychology at New York University, will provide mentorship on community practices related to youth, schools, and local organizations.

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