About this dataset

Context

The dataset tabulates the population of Harvard by race. It includes the population of Harvard across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Harvard across relevant racial categories.

Key observations

The percent distribution of Harvard population by race (across all racial categories recognized by the U.S. Census Bureau): 64.71% are white, 0.51% are Black or African American, 0.29% are American Indian and Alaska Native, 0.52% are Asian, 10.18% are some other race and 23.80% are multiracial.

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: This column displays the racial categories (excluding ethnicity) for the Harvard
• Population: The population of the racial category (excluding ethnicity) in the Harvard is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Harvard total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Harvard Population by Race & Ethnicity. You can refer the same here

In Harvard University's Class of 2025, **** percent of Hispanic or Latinx students were first-generation college students. A further **** percent of South Asian students at Harvard in the Class of 2025 were first-generation students.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Harvard by race. It includes the distribution of the Non-Hispanic population of Harvard across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Harvard across relevant racial categories.

Key observations

Of the Non-Hispanic population in Harvard, the largest racial group is White alone with a population of 4,204 (92.44% of the total Non-Hispanic population).

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: This column displays the racial categories (for Non-Hispanic) for the Harvard
• Population: The population of the racial category (for Non-Hispanic) in the Harvard is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Harvard total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Harvard Population by Race & Ethnicity. You can refer the same here

This dataset tracks annual black student percentage from 1995 to 2023 for Harvard High School vs. Illinois and Harvard Community Unit School District 50

This dataset tracks annual black student percentage from 1988 to 2023 for Harvard Elementary School vs. Nebraska and Harvard Public Schools

We provide datasets that that estimate the racial distributions associated with first, middle, and last names in the United States. The datasets cover five racial categories: White, Black, Hispanic, Asian, and Other. The provided data are computed from the voter files of six Southern states -- Alabama, Florida, Georgia, Louisiana, North Carolina, and South Carolina -- that collect race and ethnicity data upon registration. We include seven voter files per state, sourced between 2018 and 2021 from L2, Inc. Together, these states have approximately 36MM individuals who provide self-reported race and ethnicity. The last name datasets includes 338K surnames, while the middle name dictionaries contains 126K middle names and the first name datasets includes 136K first names. For each type of name, we provide a dataset of P(race | name) probabilities and P(name | race) probabilities. We include only names that appear at least 25 times across the 42 (= 7 voter files * 6 states) voter files in our dataset. These data are closely related to the the dataset: "Name Dictionaries for "wru" R Package", https://doi.org/10.7910/DVN/7TRYAC. These are the probabilities used in the latest iteration of the "WRU" package (Khanna et al., 2022) to make probabilistic predictions about the race of individuals, given their names and geolocations.

A large and fast-growing number of studies across the social sciences use experiments to better understand the role of race in human interactions, particularly in the American context. Researchers often use names to signal the race of individuals portrayed in these experiments. However, those names might also signal other attributes, such as socioeconomic status (e.g., education and income) and citizenship. If they do, researchers need pre-tested names with data on perceptions of these attributes. Such data would permit researchers to draw correct inferences about the causal effect of race in their experiments. In this paper, we provide the largest dataset of validated name perceptions based on three different surveys conducted in the United States. In total, our data include over 44,170 name evaluations from 4,026 respondents for 600 names. In addition to respondent perceptions of race, income, education, and citizenship from names, our data also include respondent characteristics. Our data will be broadly helpful for researchers conducting experiments on the manifold ways in which race shapes American life.

This dataset tracks annual black student percentage from 1996 to 2020 for Harvard High School vs. Nebraska and Harvard Public Schools

About this dataset

Context

The dataset tabulates the population of Harvard town by race. It includes the population of Harvard town across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Harvard town across relevant racial categories.

Key observations

The percent distribution of Harvard town population by race (across all racial categories recognized by the U.S. Census Bureau): 80.99% are white, 6.10% are Black or African American, 0.36% are American Indian and Alaska Native, 5.17% are Asian and 7.37% are multiracial.

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: This column displays the racial categories (excluding ethnicity) for the Harvard town
• Population: The population of the racial category (excluding ethnicity) in the Harvard town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Harvard town total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Harvard town Population by Race & Ethnicity. You can refer the same here

This repository contains code to replicate each of the figures included in "Race and ethnicity data for first, middle, and surnames" by Rosenman, Olivella, and Imai. To run

A growing body of research uses names to cue experimental subjects about race, ethnicity, and gender. However, researchers have not explored the myriad of characteristics that might be signaled by these names. In this paper, we introduce a large, publicly available database of the attributes associated with common American first and last names. For 1,000 first names and 21 last names, we provide ratings of perceived race; for 336 first names, we provide ratings on 26 social and personal characteristics. We show that the traits associated with first names vary widely, even among names associated with the same race and gender. Researchers using names to signal group memberships are thus likely cuing a number of other attributes as well. We demonstrate the importance of name selection by replicating DeSante (2013). We conclude by outlining two approaches researchers can use to choose names that successfully cue race (and gender) while minimizing potential confounds.

This dataset tracks annual black student percentage from 2007 to 2023 for P.s. 34 John Harvard vs. New York and New York City Geographic District #29

This dataset tracks annual black student percentage from 1991 to 2023 for Harvard Elementary School vs. Washington and Franklin Pierce School District

What is political knowledge? This paper argues that the traditional measure of political knowledge is limited, as it represents one domain of facts that people should know about American politics. This domain of knowledge is rooted in the liberal-democratic face of the state and neglects other political knowledge generated from the carceral face of the state. We argue that knowledge of carceral violence, especially against African Americans, represents a separate domain of knowledge that is particularly relevant to marginalized communities, especially Black youth. Once we include carceral violence in our measures of political knowledge, established patterns of whites having more political knowledge than Blacks are reversed. Using a novel measurement strategy and based on a nationally representative survey of over 2,000 young people, we find that knowledge of carceral violence is distinct from measures of what has been called general political knowledge. Finally, we find, knowledge of carceral violence has distinct correlates from the standard knowledge battery and its relationship to political participation varies by racial group but tends to depress the political participation of African Americans. Our findings raise the question of what comprises relevant and important political knowledge today and for which communities.

Contains macropartisanship data disaggregated by race and ethnicity. The data will be updated each summer around July 1st.

This dataset tracks annual black student percentage from 1993 to 2011 for Delmar Harvard Elementary School vs. Missouri and University City School District

Data for a publication.

Why do countries welcome some refugees and treat others poorly? Existing explanations suggest that the assistance refugees receive is a reflection of countries’ wealth or compassion. However, statistical analysis of a global dataset on asylum admissions shows that states’ approaches to refugees are shaped by foreign policy and ethnic politics. States admit refugees from adversaries in order to weaken those regimes, but they are reluctant to accept refugees from friendly states. At the same time, policymakers favour refugee groups who share their ethnic identity. Aside from addressing a puzzling real-world phenomenon, this article adds insights to the literature on the politics of migration and asylum.

Few studies have considered the role of immigration in the rise of gentrification in the late twentieth century. Analysis of U.S. Census and American Community Survey data over 24 years and field surveys of gentrification in low-income neighborhoods across 23 U.S. cities reveal that most gentrifying neighborhoods were “ global” in the 1970s or became so over time. An early presence of Asians was positively associated with gentrification; and an early presence of Hispanics was positively associated with gentrification in neighborhoods with substantial shares of blacks and negatively associated with gentrification in cities with high Hispanic growth, where ethnic enclaves were more likely to form. Low-income, predominantly black neighborhoods and neighborhoods that became Asian and Hispanic destinations remained ungentrified despite the growth of gentrification during the late twentieth century. The findings suggest that the rise of immigration after 1965 brought pioneers to many low-income central-city neighborhoods, spurring gentrification in some neighborhoods and forming ethnic enclaves in others.

With the growth of Latino and Asian-American populations, candidates frequently must appeal to diverse electorates. Strategies for doing so include emphasizing candidates’ racial/ethnic identity and securing endorsements from racial/ethnic groups. While many scholars focus on candidates’ racial/ethnic attributes, ethnic group endorsements are understudied. Whether such endorsements induce voters to choose ideologically-similar candidates (spatial voting), or choose based on race/ethnicity (racial voting) is unclear. We address this question by examining elections in multiethnic local settings. Using original surveys and exit polls, we create comparable measures of candidate and voter ideology, and examine how race/ethnicity and ideology affect voters’ choices. We also embed experiments that manipulate ethnic group endorsements. We find that ideology influences voters’ choices, but that ethnic group endorsements weaken spatial voting. The latter effect among whites is driven by racial/ethnic stereotypes. These reactions explain why some candidates seek such endorsements and why others might prefer to avoid them.