According to a survey conducted in 2022, ** percent of all adults in the United States said that college admissions should not consider race or ethnicity when deciding which students to accept to their school. ** percent of Americans who were White shared this belief, along with ** percent who were Hispanic.

In 2018, 66 percent of students at highly selective colleges were white. However, if SAT scores were the sole factor in admissions, this percentage would increase to 75 percent.

Students from the Chinese ethnic group had the highest entry rate into higher education in every year from 2006 to 2024.

In 2021, about 20.6 percent of postsecondary students in the United States were Hispanic. This is a slight increase from 20.3 percent in the previous year. In that same year, White students made up more than half of postsecondary students, at 53.4 percent.

In large urban districts, schools enrolling more white students tend to have higher performance ratings. We use an instrumental variables strategy leveraging centralized school assignment to explore the drivers of this relationship. Estimates from Denver and New York City suggest the correlation between widely-reported school performance ratings and white enrollment shares reflects selection bias rather than causal school value-added. In fact, value-added in these two cities is essentially unrelated to white enrollment shares. A simple regression adjustment is shown to yield school ratings that are uncorrelated with race, while predicting value-added as well or better than the corresponding unadjusted measures.

Graph and download economic data for Consumer Unit Characteristics: Percent College by Race: White and All Other Races, Not Including Black or African American (CXU980310LB0903M) from 2003 to 2023 about consumer unit, tertiary schooling, white, education, percent, and USA.

In 2029, the projected number of White high school students enrolled in four-year colleges in the United States was around 1,913,800, a decrease when compared to 2,266,000 in 2019. For Hispanic high school students, however, the projected number of those enrolled in college in 2029 was approximately 620,000, an increase from 607,400 in 2019.

Enrollment is a head count of all students receiving their primary PK-12 educational services through Wisconsin public schools. This map is in a series of maps that show enrollments by district for a particular student group (demographic) for every school year since the 2008-2009 school year. Additional enrollment data are available for the public to view on the WISEdash Public Portal. Enrollment data is sourced from the WISEdata system. DPI collects data to meet all required school, district, state, and federal reporting mandates, e.g., Every Student Succeeds Act (ESSA), Individuals with Disabilities Education Act (IDEA), and Title II Higher Education Act. These data inform education research and data analysis. Multiple teams from IT and content areas work together at DPI to build tools for data collection, to support districts in data collection, and to report on and facilitate the use of data based on federal and state reporting mandates. Through the DPI dashboard and reporting tools, DPI staff, teachers, administrators, parents, and researchers are better able to understand and improve educational outcomes for Wisconsin students.

K-12 teachers have become targets of political censorship in many states, with anti-CRT laws designed to eliminate racial truth-telling, or curricular content related to race and racism. Higher education has been targeted as well, most recently with anti-DEI initiatives, but college professors generally retain more curricular autonomy than their high school counterparts. As such, dual enrollment (DE)--college coursework delivered to high school students through a partnering postsecondary institution--may provide an avenue for students to learn about race and racism. Through the lens of racialized organizations, this study uses case study methodology to explore how a community college in Texas constrains or enables racial truth-telling in its DE courses. The findings show how the college's ostensibly race-neutral response to K-12 curricular censorship placed the burden to defend racial truth-telling on individual DE faculty, with implications for their ability to do it. The paper closes with recommendations for policy and practice.

In 2022, there were approximately 107,700 students with American Indian or Alaskan Native heritage enrolled at a university in the United States. This is a slight increase from the previous year, when there were 106,600 students with American Indian or Alaska Native heritage enrolled in postsecondary education.

Faced with demographic change, many colleges are offering courses on race and ethnicity. How does taking race-centered courses affect public opinion? We theorize that while White, Latino, and Asian American students develop inclusive political attitudes through race-centered coursework, Black Americans may already enter college with a deeper understanding about racial issues. We test these expectations using two longitudinal multi-racial datasets. First, using a national panel survey of college students, we find that ethnic studies coursework is associated with increased recognition of racial discrimination among Whites, Latinos, and even Black Americans. Second, using an original panel survey from a public university, we find reduced racial resentment and increased affirmative action support - albeit varied - among Whites, Latinos, and Asian Americans after completing race-centered political science classes but not in placebo politics classes that were not focused on race. Our findings have implications for conversations about race-centered coursework in higher education.

Racial affirmative action policies are widespread in college admissions. Yet, evidence on their effects before college is limited. Using four data sets, we study a U.S. Supreme Court ruling that reinstated affirmative action in three states. Using nationwide SAT data for difference-in-differences and synthetic control analyses, we separately identify the aggregate effects of affirmative action for whites and underrepresented minorities. Using statewide Texas administrative data, we measure the effect of affirmative action on racial gaps across the pre-treatment test score distribution. When affirmative action is reinstated, racial gaps in SAT scores, grades, attendance, and college applications fall. Average SAT scores for both whites and minorities increase, suggesting that reductions in racial gaps are driven by improvements in minorities' outcomes. Increases in minorities' pre-college human capital and college applications are concentrated in the top half of the test score distribution among students with the largest increases in their returns to human capital investment in college admissions following the policy.

This is code for replicating results in the paper "The Long-Run Impacts of Same-Race Teachers." The abstract for the paper is below.We examine the long-run impacts of exposure to a Black elementary school teacher for both Black and white students. Data from the Tennessee STAR class-size experiment show that Black students randomly assigned to at least one Black teacher in grades K-3 are 9 percentage points (13%) more likely to graduate from high school and 6 percentage points (19%) more likely to enroll in college than their Black schoolmates who are not. However, we find no statistically significant long-run effects on white students' long-run outcomes. Enrollment results are driven by enrollments in two-year colleges and concentrated among disadvantaged males. Neither pattern is evident in short-run analyses of test scores, underscoring the importance of examining long-run effects. Quasi-experimental methods applied to rich North Carolina administrative data produce generally similar findings. These effects do not appear to be driven by within-school racial differences in teacher effectiveness. While we cannot definitively identify the mechanisms at work, heterogeneity analyses provide suggestive evidence of larger effects in counties with higher unemployment rates and when Black teachers are the same sex as their students, both of which are consistent with role model effects being one of the multiple channels through which these effects likely operate.

About this dataset

Context

The dataset presents the median household income across different racial categories in University Heights. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of University Heights population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 71.33% of the total residents in University Heights. Notably, the median household income for White households is $101,601. Interestingly, despite the White population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $176,594. This reveals that, while Whites may be the most numerous in University Heights, Asian households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/university-heights-oh-median-household-income-by-race.jpeg" alt="University Heights median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in University Heights.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for University Heights median household income by race. You can refer the same here

Recently in Brazil, public policies have begun to be implemented to reduce discrimination and promote the inclusion of excluded social groups based on a specific individual characteristic: race. However, there is little public consensus about such policies, especially among whites. In this work, I look at the racial attitudes towards affirmative action among white college students. I make use of new research methods for the empirical study of socially sensitive issues and ask whether these attitudes stem from prejudice, conflicts between social groups or individual political predispositions. Furthermore, I ask what is the relationship between political knowledge and such racial attitudes. I use the list experiment method because of its potential to offset the under-representation of opinions and attitudes. This approach allows respondents to be indirectly questioned, ensuring greater sincerity in their answers and, hence, providing more accurate portrayal of attitudes. This study shows that white respondents’ answers on affirmative action policies are strongly affected by social desirability. Only 6% of white respondents agreed that it is important to have a quota policy for blacks at the Federal University of Santa Catarina (UFSC). Individuals with greater political knowledge tend to express greater support for affirmative action and hold more coherent racial attitudes Results also reveal that negative racial attitudes and political predispositions are both determinants of the white student’s attitudes towards affirmative action policies.

In 2024, white respondents had the highest rates of confidence about being able to meet the costs of a college education in the United States. Meanwhile, ** percent of Hispanic respondents and ** of Black respondents were completely confident about being able to pay the costs of college education. On the other side of the spectrum, *** percent of white and Black respondents were unconfident about being able to meet these costs.

About this dataset

Context

The dataset presents the median household income across different racial categories in University Park. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of University Park population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 84.52% of the total residents in University Park. Notably, the median household income for White households is $250,001. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $250,001.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in University Park.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for University Park median household income by race. You can refer the same here

The purpose of this study is to advance our thinking about race and racism in geospatial analyses of school choice policy. To do so, we present a critical race spatial analysis of Detroit students’ suburban school choices. To frame our study, we describe the racial and spatial dynamics of school choice, drawing in particular on the concepts of opportunity hoarding and predatory landscapes. We find that Detroit students’ suburban school choices were circumscribed by racial geography and concentrated in just a handful of schools and districts. We also find notable differences between students in different racial groups. For all Detroit exiters, their schools were significantly more segregated and lower quality than those of their suburban peers. We propose future directions for research on families’ school choices as well as school and district behavior at the intersection of race, geography, and school choice policy.This research result used data structured and maintained by the MERI-Michigan Education Data Center (MEDC). MEDC data are modified for analysis purposes using rules governed by MEDC and are not identical to those data collected and maintained by the Michigan Department of Education (MDE) and/or Michigan’s Center for Educational Performance and Information (CEPI). Results, information, and opinions solely represent the analysis, information, and opinions of the author and are not endorsed by, or reflect the views or positions of, grantors, MDE, and CEPI or any employee thereof. All errors are my own.

Historical Dataset of School For Human Rights is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2005-2023),Total Classroom Teachers Trends Over Years (2007-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2007-2023),American Indian Student Percentage Comparison Over Years (2019-2023),Asian Student Percentage Comparison Over Years (2006-2023),Hispanic Student Percentage Comparison Over Years (2005-2023),Black Student Percentage Comparison Over Years (2005-2023),White Student Percentage Comparison Over Years (2005-2023),Two or More Races Student Percentage Comparison Over Years (2019-2023),Diversity Score Comparison Over Years (2005-2023),Free Lunch Eligibility Comparison Over Years (2006-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2007-2023),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2011-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2011-2022),Graduation Rate Comparison Over Years (2012-2022)

Schools may have important impacts on children’s exposure to ambient air pollution, yet ambient air quality at schools is not consistently tracked. We characterize ambient air quality at home and school locations in the United States using satellite-based empirical model (i.e., land use regression) estimates of outdoor annual nitrogen dioxide (NO2). We report disparities by race–ethnicity and impoverishment status, and investigate differences by level of urbanicity. Average NO2 levels at home and school for racial–ethnic minoritized students are 18–22% higher than average (and 37–39% higher than for non-Hispanic, white students). Minoritized students are less likely than their white peers to live (0.55 times) and attend school (0.58 times) in areas below the World Health Organization’s NO2 guideline. Predominantly minoritized schools (i.e.,

50% minoritized students) are less likely than predominantly white schools (0.43 times) to be in locations below the guideline. Income and race–ethnicity impacts are intertwined, yet in large cities, racial disparities persist after controlling for income.