Radha Jagannathan, Louis Donnelly, Sara McLanahan, Michael J Camasso, Yu Yang
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Growing up poor but doing well: Contextual factors that predict academic success.
This paper combines data on family, school, neighborhood, and city contexts with survey data from the Year 9 (n = 2,193) and Year 15 (n = 2, 236) Fragile Families and Child Wellbeing Study to study children in America's inner-cities who are "beating the odds". We identify children as beating the odds if they were born to families of low socio-economic status but scored above the state average in reading, vocabulary and math at age 9, and were academically on-track by age 15. We also examine if the influences of these contexts are developmentally nuanced. We find that living in two parent households where harsh parenting methods are absent (family context) and living in neighborhoods where two parent families predominate (neighborhood context) are protective factors that help children beat the odds. We also find that city-wide contexts of higher levels of religiosity and fewer single parent households contribute to children beating the odds, however, these macro predictors are weaker when compared with family/neighborhood contexts. We find that these contextual effects are indeed developmentally nuanced. We conclude with a discussion of some interventions and policies that could help increase the number of at-risk children who beat the odds.
期刊介绍:
The Journal of Economic Inequality provides a forum for analysis of ''economic inequality'', broadly defined. Its scope includes: · Theoretical and empirical analysis· Monetary measures of ''well-being'' such as earnings, income, consumption, and wealth; non-monetary measures such as educational achievement and health and health care; multidimensional measures· Inequality and poverty within and between countries, and globally, and their trends over time· Inequalities of opportunity· Income mobility and poverty persistence· The factor distribution of income· Differences in ''well-being'' between socioeconomic groups, for example between men and women, generations, or ethnic groups· The effects of inequality on macroeconomic and other phenomena, and vice versa· Related statistical methods and data issues · Related policy analysis Papers need to prioritize the ''economic inequality'' dimension. For example, papers about trade and inequality, or inequality and growth, should not primarily be about trade or growth (in which case they should target a different journal). The same is true for papers considering the inter-relationships between the income distribution and the labour market, public policy, or demography.
Officially cited as: J Econ Inequal