Report famously highlighted the relationship between family socioeconomic status and student achievement. 2 Family socioeconomic characteristics continue to be among the strongest predictors of student achievement, but while there is a considerable body of research that seeks to tease apart this relationship, the causes and mechanisms of this relationship have been the subject of considerable disagreement and debate. Much of the scholarly research on the socioeconomic achievement gradient has focused largely on trying to understand the mechanisms through which factors like income, parental educational attainment, family structure, neighborhood conditions, school quality, as well as parental preferences, investments, and choices lead to dif-The Widening Academic Achievement Gap between the Rich and the Poor By Sean F. Reardon, Stanford University 1 ferences in children's academic and educational success. Still, we know little about the trends in socioeconomic achievement gaps over a lengthy period of time. The question posed in this article is whether and how the relationship between family socioeconomic characteristics and academic achievement has changed during the last fifty years, with a particular focus on rising income inequality. As the income gap between high-and low-income families has widened, has the achievement gap between children in high-and lowincome families also widened? The answer, in brief, is yes. The achievement gap between children from highand low-income families is roughly 40 percent larger among children born in 2001 than among those born twenty-five years earlier.

The measurement of residential segregation patterns and trends has been limited by a reliance on segregation measures that do not appropriately take into account the spatial patterning of population distributions. In this paper we define a general approach to measuring spatial segregation among multiple population groups. This general approach allows researchers to specify any theoretically based definition of spatial proximity desired in computing segregation measures. Based on this general approach, we develop a general spatial exposure/isolation index (P P*), and a set of general multigroup spatial evenness/ clustering indices: a spatial information theory index (H H), a spatial relative diversity index (R R), and a spatial dissimilarity index (D D). We review these and previously proposed spatial segregation indices against a set of eight desirable properties of spatial segregation indices. We conclude that the spatial exposure/isolation indexP P*-which can be interpreted as a

In this paper we derive and evaluate measures of multigroup segregation. After describing four ways to conceptualize the measurement of multigroup segregation-as the disproportionality in group (e.g., race) proportions across organizational units (e.g., schools or census tracts), as the strength of association between nominal variables indexing group and organizational unit membership, as the ratio of between-unit diversity to total diversity, and as the weighted average of two-group segregation indices-we derive six multigroup segregation indices: a dissimilarity index (D), a Gini index (G), an information theory index (H ), a squared coefficient of variation index (C), a relative diversity index (R), and a normalized exposure index (P ). We evaluate these six indices against a set of seven desirable properties of segregation indices. We conclude that the information theory index H is the most conceptually and mathematically satisfactory index, since it alone obeys the principle of transfers in the multigroup case. Moreover, H is the only multigroup index that can be decomposed into a sum of between-and within-group components.

This article investigates how the growth in income inequality from 1970 to 2000 affected patterns of income segregation along three dimensions: the spatial segregation of poverty and affluence, race-specific patterns of income segregation, and the geographic scale of income segregation. The evidence reveals a robust relationship between income inequality and income segregation, an effect that is larger for black families than for white families. In addition, income inequality affects income segregation primarily through its effect on the large-scale spatial segregation of affluence rather than by affecting the spatial segregation of poverty or by altering small-scale patterns of income segregation.

This article describes the developmental patterns of Hispanic-White math and reading achievement gaps in elementary school, paying attention to variation in these patterns among Hispanic subgroups. Compared to non-Hispanic White students, Hispanic students enter kindergarten with much lower average math and reading skills. The gaps narrow by roughly a third in the first 2 years of schooling but remain relatively stable for the next 4 years. The development of achievement gaps varies considerably among Hispanic subgroups. Students with Mexican and Central American origins—particularly first- and second-generation immigrants—and those from homes where English is not spoken have the lowest math and reading skill levels at kindergarten entry but show the greatest achievement gains in the early years of schooling.

Since the Supreme Court's 1954 Brown v. Board of Education decision, researchers and policy makers have paid close attention to trends in school segregation. Here we review the evidence regarding trends and consequences of both racial and economic school segregation since Brown. The evidence suggests that the most significant declines in black-white school segregation occurred in the late 1960s and early 1970s. There is disagreement about the direction of more recent trends in racial segregation, largely driven by how one defines and measures segregation. Depending on the definition used, segregation has either increased substantially or changed little, although there are important differences in the trends across regions, racial groups, and institutional levels. Limited evidence on school economic segregation makes documenting trends difficult, but students appear to be more segregated by income across schools and districts today than in 1990. We also discuss the role of desegregation litigation, demographic changes, and residential segregation in shaping trends in both racial and economic segregation. We develop a general conceptual model of how and why school segregation might affect students and review the relatively thin body of empirical evidence that explicitly assesses the consequences of school segregation. We conclude with a discussion of aspects of school segregation on which further research is needed. 9.1

The census tract-based residential segregation literature rests on problematic assumptions about geographic scale and proximity. We pursue a new tract-free approach that combines explicitly spatial concepts and methods to examine racial segregation across egocentric local environments of varying size. Using 2000 census data for the 100 largest U.S. metropolitan areas, we compute a spatially modified version of the information theory index H to describe patterns of black-white, Hispanic-white, Asian-white, and multi-group segregation at different scales. The metropolitan structural characteristics that best distinguish micro-segregation from macro-segregation for each group combination are identified, and their effects are decomposed into portions due to racial variation occurring over short and long distances. A comparison of our results to those from tract-based analyses confirms the value of the new approach.

Racial, ethnic, and income disparities in performance on standardized tests of academic achievement are a stubborn feature of the U.S. educational landscape. The White-Black and White-Hispanic achievement gaps in math and reading in Grades 4 to 12 range from roughly 0.50 to 0.85 standard deviations in recent years; the gap in achievement between kindergarten students from high-and low-income families was roughly 1.