*Names in bold indicate Presenter
Extant experimental and quasi-experimental research has documented links between economic disadvantage and children’s academic development. Poverty, particularly in early childhood, predicts decreased cognitive skills and school success (Heckman, 2000; Magnuson & Votruba-Drzal, 2009). While associations between poverty and children’s reading and math achievement are well-established, it is less clear how and where gaps arise. Understanding how is important because processes linking poverty to academic development present targets for prevention and intervention services aimed at altering the developmental paths of poor children. Moreover, delineating where economic disadvantage is particularly detrimental and where it is counteracted by other contextual forces is similarly critical for targeting resources and better specifying theoretical models.
It is crucial to understand how the experiences of poor children differ across the urban-rural continuum, leading to divergent associations with academic skills development. Drawing on leading theoretical frameworks of poverty’s effects, we hypothesize that access to resources and investments, exposure to stress, and contact with maladaptive norms and behaviors at the family and community levels vary across urbanicity, resulting in heterogeneity in the academic skills of low-income children living in rural, suburban, and urban communities. Using nationally representative data from the Early Childhood Longitudinal Study, Kindergarten Class of 2010-2011 (ECLS-K:2011), this study will document differences in low-income kindergarteners’ academic skills across the urban to rural landscape and delineate how differences in resources, stress, and community norms at the family and community levels to explain this heterogeneity. This represents a unique focus on how resources/investments, stress, and norms processes function differently across contexts. Contextual process data will be derived from the ECLS-K:2011 and geocoded data on community resources, environmental stressors, and community norms and behaviors from several administrative databases. Analyses will incorporate econometric propensity score techniques to help control for differential selection of low-income families into communities based on urbanicity.
Preliminary differences (Table 1) illustrate that with respect to reading and math skills, low-income children in rural communities enter kindergarten with higher scores than their counter parts in large urban, small urban, suburban, and small town communities. Conversely, kindergarteners in large urban cities begin school with the fewest academic skills compared to peers in all other settings. Subsequent analyses will consider how differences in community resources, environmental stressors, and community norms contribute to these differences in early academic skills.