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Race, ethnicity and culture
We use linked individual-level data on school enrollment, physician services received, and prescription medications to measure the effect of the COVID-19 pandemic and associated disruptions on mental health treatment received by adolescents in British Columbia. We also investigate whether these effects are mediated by socioeconomic status and schooling mode. The results suggest substantial increases for non-Indigenous English home language girls in treatment for depression/anxiety, ADHD, eating disorders and other mental health conditions. Indigenous and non-English home language girls also show increases in treatment for depression/anxiety, and Indigenous girls show increases in treatment for ADHD. In contrast, boys show no change or even reductions in treatment for most mental health conditions. These effects vary somewhat by socioeconomic status, but we find no evidence that they vary substantially by schooling mode.
The US teaching force remains disproportionately white while the student body grows more diverse. It is therefore important to understand how and under what conditions white teachers learn racial competency. This study applies a mixed-methods approach to investigate the hypothesis that Black peers improve white teachers’ effectiveness when teaching Black students. The quantitative portion of this study relies on longitudinal data from North Carolina to show that having a Black same-grade peer significantly improves the achievement and reduces the suspension rates of white teachers’ Black students. These effects are persistent over time and largest for novice teachers. Qualitative evidence from open-ended interviews of North Carolina public school teachers reaffirms these findings. Broadly, our findings suggest that the positive impact of Black teachers’ ability to successfully teach Black students is not limited to their direct interaction with Black students but is augmented by spillover effects on early-career white teachers, likely through peer learning.
School mobility, compounding socioeconomic inequities, can undermine academic achievement and behavior, particularly during middle school years. This study investigates the effect of a school-based integrated student support intervention – City Connects – on the achievement and behavior of middle school students who experience school mobility. Using administrative data from a large, urban, public school district in the U.S., we apply student fixed effects and event studies methods to analyze the academic and behavioral performance of students changing schools. The results indicate that students who moved to schools implementing the City Connects intervention performed better academically and behaviorally than other students.
Low-socioeconomic status (SES), minority, and male students perform worse than their high-SES, non-minority, and female peers on standardized tests. This paper investigates how within-school differences in school quality contribute to these educational achievement gaps. Using individual-level data on the universe of public-school students in California, I estimate school quality using a value added methodology that accounts for the fact that students sort to schools on observable characteristics. I allow for within-school heterogeneity by estimating a distinct value added for each school's low-/high-SES, minority/non-minority, and male/female students. Standard value added models suggest that on average schools provide less value added to their low-SES, minority, and male students, particularly on postsecondary enrollment. However, value added models that control for neighborhood, older-sibling, and peer characteristics suggest that schools provide similar value added to low-/high-SES students and minority/non-minority students but more value added to female students. Within-school heterogeneity accounts for 6% of the test-score achievement gap and 22% of the difference in postsecondary enrollment between men and women.
The media discourse on student loans plays a significant role in the way that policy actors conceptualize challenges and potential solutions related to student debt. This study examines the racialized language in student loan news articles published in eight major news outlets between 2006 and 2021. We found that 18% of articles use any racialized language, though use has accelerated since 2018. This increase appears to be driven by terms that denote groups of people instead of structural problems, with 8% of articles mentioning “Black” but less than 1% mentioning “racism.” These findings emphasize the importance of treating the media as a policy actor capable of shaping the salience of racialization in discussions about student loans.
U.S. public school students increasingly attend schools with sworn law enforcement officers present. Yet, little is known about how these school resource officers (SROs) affect school environments or student outcomes. Our study uses a fuzzy regression discontinuity (RD) design with national school-level data from 2014 to 2018 to estimate the impacts of SRO placement. We construct this discontinuity based on the application scores for federal school based policing grants of linked police agencies. We find that SROs effectively reduce some forms of violence in schools, but do not prevent gun-related incidents. We also find that SROs intensify the use of suspension, expulsion, police referral, and arrest of students. These increases in disciplinary and police actions are consistently largest for Black students, male students, and students with disabilities.
Broadband is not equally accessible among students despite its increasing importance to education. We investigate the relationship between broadband and housing policy by joining two measures of broadband access with Depression-era redlining maps that classified neighborhoods based in part on racist and classist beliefs. We find that despite internet service provider selfreports of similar technological availability, broadband access generally decreases in tandem with historic neighborhood classification, with further heterogeneity by race/ethnicity and income. Our findings demonstrate how past federally-developed housing policies connect to the digital divide and should be considered in educational policies that require broadband for success.
Inequality related to standardized tests in college admissions has long been a subject of discussion; less is known about inequality in non-standardized components of the college application. We analyzed extracurricular activity descriptions in 5,967,920 applications submitted through the Common Application platform. Using human-crafted keyword dictionaries combined with text-as-data (natural language processing) methods, we found that White, Asian American, high-SES, and private school students reported substantially more activities, more activities with top-level leadership roles, and more activities with distinctive accomplishments (e.g., honors, awards). Black, Latinx, Indigenous, and low-income students reported a similar proportion of activities with top-level leadership positions as other groups, although the absolute number was lower. Gaps also lessened for honors/awards when examining proportions, versus absolute number. Disparities decreased further when accounting for other applicant demographics, school fixed effects, and standardized test scores. However, salient differences related to race and class remain. Findings do not support a return to required standardized testing, nor do they necessarily support ending consideration of activities in admissions. We discuss reducing the number of activities that students report and increasing training for admissions staff as measures to strengthen holistic review.
Books shape how children learn about society and norms, in part through representation of different characters. We introduce new artificial intelligence methods for systematically converting images into data and apply them, along with text analysis methods, to measure the representation of skin color, race, gender, and age in award-winning children’s books widely read in homes, classrooms, and libraries over the last century. We find that more characters with darker skin color appear over time, but the most influential books persistently depict characters with lighter skin color, on average, than other books, even after conditioning on race; we also find that children are depicted with lighter skin than adults on average. Relative to their growing share of the U.S. population, Black and Latinx people are underrepresented in these same books, while White males are overrepresented. Over time, females are increasingly present but appear less often in text than in images, suggesting greater symbolic inclusion in pictures than substantive inclusion in stories. We then present analysis of the supply of, and demand for, books with different levels of representation to better understand the economic behavior that may contribute to these patterns. On the demand side, we show that people consume books that center their own identities. On the supply side, we document higher prices for books that center non-dominant social identities and fewer copies of these books in libraries that serve predominantly White communities. Lastly, we show that the types of children's books purchased in a neighborhood are related to local political beliefs.
This paper conceptualizes segregation as a phenomenon that emerges from the intersection of public policy and individual decision-making. Contemporary scholarship on complex decision-making describes a two-step process—1) Editing and 2) Selection— and has emphasized the individual decision-maker’s agency in both steps. We build on this work by exploring, both theoretically and empirically, how policy can structure the choices individuals face at each step. We conduct this exploration within the empirical context of enrollment decisions among families in the Wake County Public School System (WCPSS), which used a controlled school choice system to help achieve diversity aims. We first investigate the schooling choice sets that WCPSS constructed for families and then examine families’ schooling selections. We find that families were offered choice sets containing schools varying racial compositions, but that the racial makeup of schools in families’ choice set systematically varied by schooling type and student race/ethnicity. We further show that a majority of families enrolled in their district-assigned default school, with Black and Hispanic families more likely than white or Asian families to attend this option. Finally, we demonstrate that white or Asian families enroll in their default school at lower rates as the share of Black students increases.