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Research on shadow education-i.e., one-on-one or group learning intended to supplement children's experiences in school-has documented persistent social class and racial/ethnic inequalities. Yet, as with many things during the Covid-19 pandemic, the nature of shadow education changed dramatically. Much supplemental education shifted online, potentially increasing accessibility; many universities became testoptional, potentially reducing the demand for the shadow education industry; and a new form of shadow education-learning pods-emerged to take pandemic schooling from a more individual to a more collective experience. In this article, we use data from a sample of U.S. parents of K-12 students stratified by race/ethnicity (N = 1911) to assess social class and racial/ethnic inequalities in shadow education in 2020-21, the first full academic year of the Covid-19 pandemic. We are also the first scholars, to our knowledge, to assess high-quality data on the use of learning pods. We find that during the pandemic, African American and South Asian students were more likely than White student to use test preparation services and online supplemental education, and that African Americans, East Asians and Latinx were more likely to utilize private tutoring. We find few disparities by family income, however, thus supporting the idea that some forms of shadow education have become more accessible than they once were. Regarding learning pods, we find that pods were most common among African American families and families with parents who were less educated and worked fulltime. Thus, most learning pods were not a means of "opportunity hoarding," as some scholars originally feared, but instead provided sorely needed childcare and support during a time of social turbulence.

This study explores disparities in reclassification outcomes between Chinese and Latinx English learner (EL) students in one large school district, along with possible mechanisms that drive these differences. Using mixed methods including discrete-time hazard modeling of longitudinal administrative data and analysis of in-depth interviews with veteran EL educators and administrators, we find large and persistent ethnic differences in reclassification outcomes across grade levels. Drawing on prior research on inequalities among immigrant students, we find evidence that individual background characteristics, social capital, school and instructional contexts, and stereotypes and bias all contribute to variation in reclassification patterns. Importantly, reclassification processes may be sensitive to racial and ethnic biases, disproportionately limiting Latinx EL students' reclassification.

In this article, we propose a shift in race research from a one-dimensional hierarchical approach to a multidimensional system of racial stratification. Building upon Claire Kim's (1999) racial triangulation theory, we examine how the American public rates Asians relative to blacks and whites along two dimensions of racial stratification: racial valorization and civic acceptance/ostracism. Using selected years from the General Social Survey, our analyses provide support for the multidimensional racial triangulation perspective as opposed to a singular hierarchical approach, although findings do not match all predictions by the racial triangulation thesis. Our results also suggest that on average whites are more likely than blacks to have more favorable views of the relative positions of Asians, particularly for family commitment, nonviolence and wealth, but blacks are more likely to assume racially egalitarian views than do whites.

The increase in high-skilled immigrants to the United States coincided with the expansion of the high-technology sector, and now a large share of Asian immigrants concentrate in high-tech industries. Despite much research on the relationship between ethnic concentration and labor market outcomes, the association between ethnic niche employment and earnings within the high-technology sector of the labor market has yet to be examined. This study compares the relationship between employment in ethnic niches and earnings within high- and low-tech industries among Asian immigrants. In low-technology industries, ethnic niches are generally associated with lower earnings compared with non-niches, but in high-technology industries, employment in an ethnic niche is associated with higher earnings. These patterns vary by gender and ethnic group. This association is partly explained by the industries that comprise ethnic niches, as non-Hispanic white immigrants also experience some of the same advantages and disadvantages.