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A wide research base has documented the unequal access to and enrollment in K-12 gifted and talented services and other forms of advanced learning opportunities. This study extends that knowledge base by integrating multiple population-level datasets to better understand correlates of access to and enrollment in gifted and talented services, seventh-grade Algebra 1, and eighth-grade Geometry. Results show that states vary widely with some serving 20% of their students as gifted while others serve 0%. Similarly, within-district income segregation, income-related achievement gaps, and the percent of parents with a college degree are the dominant predictors of a school offering these opportunities and the size of the school population served.
At least 25 million K-12 students in the U.S.—disproportionately children of color from low-income families—have been physically out of school for a full year due to the COVID-19 pandemic. These children are at risk of significant academic, social, mental, and physical harm now and in the long-term. We must determine how to help all students gain access to safe, in-person schooling. In this interdisciplinary Viewpoint, we review the literature about the association between school reopening and COVID-19 transmission rates, and about the political, social, and environmental conditions that shape families’ and teachers’ choices to return to in-person schooling. Even though schools can safely be opened with appropriate mitigation measures, we find four reasons for schooling hesitancy: high community transmission rates; the Trump administration’s politicization of school re-openings in Summer 2020; long-term histories of mutual mistrust and racialized disinvestment in urban districts; and rational calculation about vulnerability due to the social determinants of health that have led Black and Latinx parents disproportionately to keep their children at home and White families disproportionately to send their children to school. Given the deep interconnections between the social determinants of health and of learning, and between schooling hesitancy and community vulnerability, stark inequities in in-person schooling access and take-up are likely to persist. In addition to ramping up safe and speedy school reopening now, we must make a long-term commitment to supporting schools as both sites of and contributors to public health, especially in historically marginalized communities.
Despite the growing evidence of informational interventions on college and major choices, we know little about how such light-touch interventions affect the gender gap in STEM majors. Linking survey data to administrative records of Chinese college applicants, we conducted a large-scale randomized experiment to examine the STEM gender gap in the major preference beliefs, application behaviors, and admissions outcomes. We find that female students are less likely to prefer, apply to, and enroll in STEM majors, particularly Engineering majors. In a school-level cluster randomized controlled trial, we provided treated students with major-specific wage information. Students’ major preferences are easily malleable that 39% of treated students updated their preferences after receiving the wage informational intervention. The wage informational intervention has no statistically significant impacts on female students’ STEM-related major applications and admissions. In contrast, those male students in rural areas who likely lack such information are largely shifted into STEM majors as a result of the intervention. We provide supporting evidence of heterogeneous major preferences for extrinsic incentives: even among those students who are most likely to be affected by the wage information (prefer high paying majors and lack the wage information), female students are less responsive to the informational intervention.
Graduate student teaching assistants from underrepresented groups may provide salient role models and enhanced instruction to minority students in STEM fields. We explore minority student-TA interactions in an important course in the sciences and STEM – introductory chemistry labs – at a large public university. The uncommon assignment method of students to TA instructors in these chemistry labs overcomes selection problems, and the small and active learning classroom setting with required attendance provides frequent interactions with the TA. We find evidence that underrepresented minority students are less likely to drop courses and are more likely to pass courses when assigned to minority TAs, but we do not find evidence of effects for grades and medium-term outcomes. The effects for the first-order outcomes are large with a decrease in the drop rate by 5.5 percentage points on a base of 6 percent, and an increase in the pass rate of 4.8 percentage points on a base of 93.6 percent. The findings are similar when we focus on Latinx student - Latinx TA interactions. The findings are robust to first-time vs. multiple enrollments in labs, specifications with different levels of fixed effects, limited choice of TA race, limited information of TAs, and low registration priority students. The findings have implications for debates over increasing diversity among PhD students in STEM fields because of spillovers to minority undergraduates.
Many state governments impose tuition regulations on universities in pursuit of college affordability. How effective are these regulations? We study how universities' "sticker price'' and institutional financial aid change during and after tuition caps and freezes by leveraging temporal and geographic variation in the United States from 1990 to 2013. We find that listed tuition is lower than it would have been in the absence of the regulation by 6.3 (9.3) percentage points at four-year (two-year) colleges during the regulation. Meanwhile, the negative impact on institutional aid at four-year colleges during a tuition cap/freeze is nearly double (-11.3 percentage points) the impact on listed tuition, implying that universities adjust institutional aid in order to recoup some of their losses from the tuition cap/freeze. Effects are long-lasting at four-year institutions; two years after the regulation is lifted, tuition is 7.3 percentage points lower and institutional aid is 19.5 percentage points lower than it would have been without the regulation. Meanwhile at two-year colleges, tuition "catches up" so that by three years after the end of the regulation tuition is not statistically different from what it would have been in the absence of the regulation. Universities that are not research-intensive and universities that have a greater dependency on tuition revenue exhibit larger negative impacts on institutional aid with smaller impacts on "sticker price''. Our estimates suggest that tuition caps and freezes do not simply lower the prices that students pay for college and that the benefit of tuition regulations is unequally spread across types of universities and students.
This paper takes a novel time series perspective on K-12 school spending. About half of school spending is financed by state government aid to local districts. Because state aid is generally income conditioned, with low-income districts receiving more aid, state aid acts as a mechanism for risk sharing between school districts. We show that temporal inequality, due to state and local business cycles, is prevalent across the income distribution. We estimate a model of local revenue and state aid, and its allocation across districts, and use the parameters to simulate impulse response functions. We find that state aid provides risk sharing for local shocks, although slow speed of adjustment results in temporal inequality. There is little risk sharing for statewide income shocks, and the risk from such shocks to school spending is more severe in low income districts because of their greater reliance on state aid.
Well-documented racial disparities in rates of exclusionary discipline may arise from differences in hard-to-observe student behavior or bias, in which treatment for the same behavior varies by student race or ethnicity. We provide evidence for the presence of bias using statewide administrative data that contain rich details on individual disciplinary infractions. Two complementary empirical strategies identify bias in suspension outcomes. The first uses within-incident variation in disciplinary outcomes across White and under-represented minority students. The second employs individual fixed effects to examine how consequences vary for students across incidents based on the race of the other student involved in the incident. Both approaches find that Black students are suspended for longer than Hispanic or White students, while there is no evidence of Hispanic-White disparities. The similarity of findings across approaches and the ability of individual fixed effect models to account for unobserved characteristics common across disciplinary incidents provide support that remaining racial disparities are likely not driven by behavior.
The segregation of students by socioeconomic status has been on the rise in American public education between schools during the past several decades. Recent work has demonstrated that segregation is also increasing within schools at the classroom level. In this paper, we contribute to our understanding of the determinants of this increase in socioeconomic segregation within schools. We assess whether growth in the presence and number of nearby charter schools have affected the segregation of socioeconomically disadvantaged students by classroom in traditional public schools (TPS). Using data from North Carolina, we estimate a series of models exploit variation in the number and location of charter schools over time between 2007 and 2014 to estimate the impact of charter school penetration and proximity on levels of within school segregation in TPS classrooms serving grades 3-8. We find that socioeconomic segregation in math and English language arts increase in grades 3-6 when additional charter schools open within large urban districts. We find the largest impacts on schools that are closest to the new charter schools. We estimate that the impact of charter schools can account for almost half of the overall growth in socioeconomic segregation we see over the course of the panel within grades 3-6 in large urban districts.
Mixed evidence on the relationship between school closure and COVID-19 prevalence could reflect focus on large-scale levels of geography, limited ability to address endogeneity, and demographic variation. Using county-level CDC COVID-19 data through June 15, 2020, two matching strategies address potential heterogeneity: nearest geographic neighbor and propensity scores. Within nearest neighboring pairs in different states with different school closure timing, each additional day from a county’s first case until state-ordered school closure is related to 1.5%-2.4% higher cumulative COVID-19 deaths per capita (1,227-1,972 deaths for a county with median population and deaths/capita). Results are consistent using propensity score matching, COVID-19 data from two alternative sources, and additional sensitivity analyses. School closure is more strongly related to COVID-19 deaths in counties with a high concentration of Black or poor residents, suggesting schools play an unequal role in transmission and earlier school closure is related to fewer lives lost in disadvantaged counties.
The decades-long resistance to federally imposed school desegregation entered a new phase at the turn of the new century, when federal courts stopped pushing racial balance as a remedy for past segregation, adopting in its place a color-blind approach in judging local school districts’ assignment plans. Using data that span 1998 to 2016 from North Carolina, one of the first states to come under this color-blind dictum, we examine the ways in which households and policymakers took actions that had the effect of reducing the amount of interracial contact in K-12 schools within counties. We divide these reductions in interracial contact into portions due to the private school and charter school sectors, the existence of multiple school districts, and racial disparities between schools within districts and sectors. For most counties, the last of these proves to be the biggest, though in some counties private schools, charter schools, or multiple districts played a deciding role. In addition, we decompose segregation in the state’s 13 metropolitan areas, finding that more than half can be attributed to racial disparities inside school districts. We also measure segregation by economic status, finding that it, like racial segregation, increased in the largest urban counties, but elsewhere changed little over the period.