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Inequality

Fernanda Ramirez-Espinoza.

This paper presents evidence that women and men benefit from having a higher percentage of female peers in post-secondary vocational STEM programs. I use idiosyncratic variation in gender composition across cohorts within majors within branches (campuses) for identification. Having a higher percentage of female peers positively affects students in STEM majors, decreasing women's dropout rates and increasing GPA. The peer effect seems to be mediated by the gender of the instructors: as female students have fewer female instructors, the effect of having more female peers intensifies. For men, a higher percentage of female peers reduces dropouts and increases GPA to a lesser extent, suggesting that policies that increase the representation of women need not entail a trade-off for male STEM students.

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Matthew A. Kraft, Manuel Monti-Nussbaum.

Narrative accounts of classroom instruction suggest that external interruptions, such as intercom announcements and visits from staff, are a regular occurrence in U.S. public schools. We study the frequency, nature, and duration of external interruptions in the Providence Public School District (PPSD) using original data from a district-wide survey and classroom observations. We estimate that a typical classroom in PPSD is interrupted over 2,000 times per year, and that these interruptions and the disruptions they cause result in the loss of between 10 to 20 days of instructional time. Administrators appear to systematically underestimate the frequency and negative consequences of these interruptions. We propose several organizational approaches schools might adopt to reduce external interruptions to classroom instruction.

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Zach Sullivan, Benjamin L. Castleman, Gabrielle Lohner, Eric Bettinger.

In-person college advising programs generate large improvements in college persistence and success for low-income students but face numerous barriers to scale. Remote advising models offer a promising strategy to address informational and assistance barriers facing the substantial majority of low-income students who do not have access to community-based advising, yet the existing evidence base on the efficacy of remote advising is limited. We present a comprehensive, multi-cohort experimental evaluation of CollegePoint, a national remote college advising program for high-achieving low- and moderate-income students. Students assigned to CollegePoint are modestly more likely (1.3 percentage points) to attend higher-quality institutions. Results from mechanism experiments we conducted within CollegePoint indicate that moderate changes to the program model, such as a longer duration of advising and modest expansions of the pool of students academically eligible to participate, do not lead to larger program effects. We also capitalize on across-cohort variation in whether students were affected by COVID-19 to investigate whether social distancing required by the pandemic increased the value of remote advising. CollegePoint increased attendance at higher-quality institutions by 3.2 percentage points for the COVID-19-affected cohort. Acknowledgements.

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Amanda P. Williford, Pilar Alamos, Jessica E. Whittaker, Maria R. Accavitti.

We documented (1) the use of strategies, beyond suspensions and expulsions, that exclude young students from learning opportunities and (2) how teacher-reported use of these strategies varied according to student racial/ethnic composition. In a sample of 2,053 teachers and 40,771 kindergarten students, teachers reported on their use of five exclusionary strategies including isolated seating, removal from an activity, and loss of recess. Teachers reported substantive use of all exclusionary strategies and use varied depending on strategy. Teachers reported using certain exclusionary practices (break outside of classroom, loss of recess or free time, and limit talking) more frequently when they rated more Black versus White students to be lowest on self-regulation and social skills. Findings illustrate the value of looking beyond suspensions and expulsions in the early years to advance equity in young children’s opportunities to engage with teachers, peers, and learning tasks at school.

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Plamen Nikolov, Steve Yeh.

Cognition, a component of human capital, is fundamental for decision-making, and understanding the causes of human capital depreciation in old age is especially important in aging societies. Using various proxy measures of cognitive performance from a longitudinal survey in South Africa, we study how education affects cognition in late adulthood. We show that an extra year of schooling improves memory performance and general cognition. We find evidence of heterogeneous effects by gender: the effects are stronger among women. We explore potential mechanisms, and we show that a more supportive social environment, improved health habits, and reduced stress levels likely play a critical role in mediating the beneficial effects of educational attainment on cognition among the elderly.

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Mark J. Chin.

In this paper I study the impact of court-mandated school desegregation by race on student suspensions and special education classification. Simple descriptive statistics using student enrollment and outcome data collected from the largest school districts across the country in the 1970s and 1980s show that Black-White school integration was increasing for districts under court order, but not for a set of comparison districts. Similarly, Black student suspension rates were increasing at faster rates in integrating districts relative to comparison districts, and their classification rates as having an intellectual disability were decreasing at slower rates. Differences-in-differences and event study models confirm these patterns I observe in the raw data: after integration, school districts experienced statistically and practically significant reductions in racial isolation across schools and growth in racial disparities in discipline and special education classification. The impacts of integration are immediate, sustained, and robust for student suspensions in particular. My results thus provide causal evidence confirming prior descriptive and theoretical work suggesting that the racial composition of schools may influence measures of categorical inequality by race.

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Charles T. Clotfelter, Helen F. Ladd, Calen R. Clifton.

Using detailed classroom-level data for North Carolina, we build on previous research to examine racial gaps in access to high-quality teachers. We calculate the exposure of White, Black and Hispanic students to teachers with various characteristics in 4th grade, 7th grade math and English, and 10th grade math and English. We find that across the state White students enjoy sizable advantages over both Black and Hispanic students in the form of higher exposure to teachers with strong credentials and lower exposure to teachers with weak credentials. Remarkably, we also find this pattern of White advantage in most individual counties, with the largest White advantage occurring in the largest counties by enrollment. A decomposition of the White advantages shows that the bulk of them can be attributed to differences across counties and differences between schools within counties. Only in 10th grade are differences across classrooms within schools important in explaining the White advantage.

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Lauren C. Russell, Lei Yu, Michael J. Andrews.

We investigate how the presence of a college affects local educational attainment using historical natural experiments in which "runner-up" locations were strongly considered to become college sites but ultimately not chosen for as-good-as-random reasons. While runner-up counties have since had opportunity to establish their own colleges, winners are still more likely to have a college today. Using this variation, we find that winning counties today have college degree attainment rates 58% higher than runner-up counties and have larger shares of employment in high human capital sectors. These effects are not driven primarily by college employees, migration, or local development.

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Lauren P. Bailes, Sarah Guthery.

This study investigates whether a principal’s likelihood of hiring a teacher of color is sensitive to the racial composition of students in the school. We used an administrative dataset from Texas including 59,157 principal observations and 662,997 teacher observations spanning 2000 to 2017 in order to consider whether or not the disappearing diversity from a majority white school is a factor in principals’ decisions to hire teachers of color. We examined the hiring patterns of principals within schools where 50% of the students were white and compared the probability that a nonwhite teacher would be hired as the homogeneity of the student body increased (that is, as increasing proportions of the student body were white). We found that white principals were less likely to hire teachers of color as the proportion of white students approached 100%. This study provides initial evidence that teacher hires are not only sensitive to the principal’s race but also to the racial composition of the student body. Specifically, as the diversity of the student body disappears, so too does the principal’s likelihood of hiring a teacher of color.

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Kelli A. Bird, Benjamin L. Castleman, Zachary Mabel, Yifeng Song.

Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two important dimensions: (1) different approaches to sample and variable construction and how these affect model accuracy; and (2) how the selection of predictive modeling approaches, ranging from methods many institutional researchers would be familiar with to more complex machine learning methods, impacts model performance and the stability of predicted scores. The relative ranking of students’ predicted probability of completing college varies substantially across modeling approaches. While we observe substantial gains in performance from models trained on a sample structured to represent the typical enrollment spells of students and with a robust set of predictors, we observe similar performance between the simplest and most complex models.

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