In the fall of 2022, *** undergraduate students at Harvard University were Hispanic or Latino. This compares to ***** White undergraduate 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 678 (97.13% 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

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 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): 80.62% are white, 0.60% are Black or African American, 1.50% are American Indian and Alaska Native, 10.29% are some other race and 6.99% 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

Users can obtain descriptions, maps, profiles, and ranks of U.S. metropolitan areas pertaining to quality of life, diversity, and opportunities for racial and ethnic groups in the U.S. BackgroundThe Diversity Data project operates a website for users to explore how U.S. metropolitan areas perform on evidence-based social measures affecting quality of life, diversity and opportunity for racial and ethnic groups in the United States. These indicators capture a broad definition of quality of life and health, including opportunities for good schools, housing, jobs, wages, health and social services, and safe neighborhoods. This is a useful resource for people inter ested in advocating for policy and social change regarding neighborhood integration, residential mobility, anti-discrimination in housing, urban renewal, school quality and economic opportunities. The Diversity Data project is an ongoing project of the Harvard School of Public Health (Department of Society, Human Development and Health). User FunctionalityUsers can obtain a description, profile and rank of U.S. metropolitan areas and compare ranks across metropolitan areas. Users can also generate maps which demonstrate the distribution of these measures across the United States. Demographic information is available by race/ethnicity. Data NotesData are derived from multiple sources including: the U.S. Census Bureau; National Center for Health Statistics' Vital Statistics Natality Birth Data; Natio nal Center for Education Statistics; Union CPS Utilities Data CD; National Low Income Housing Coalition; Freddie Mac Conventional Mortgage Home Price Index; Neighborhood Change Database; Joint Center for Housing Studies of Harvard University; Federal Financial Institutions Examination Council Home Mortgage Disclosure Act (HMD); Dr. Russ Lopez, Boston University School of Public Health, Department of Environmental Health; HUD State of the Cities Data Systems; Agency for Healthcare Research and Quality; and Texas Transportation Institute. Years in which the data were collected are indicated with the measure. Information is available for metropolitan areas. The website does not indicate when the data are updated.

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 4,223 (93.55% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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

The 2018 edition of Woods and Poole Complete U.S. Database provides annual historical data from 1970 (some variables begin in 1990) and annual projections to 2050 of population by race, sex, and age, employment by industry, earnings of employees by industry, personal income by source, households by income bracket and retail sales by kind of business. The Complete U.S. Database contains annual data for all economic and demographic variables for all geographic areas in the Woods & Poole database (the U.S. total, and all regions, states, counties, and CBSAs). The Complete U.S. Database has following components: Demographic & Economic Desktop Data Files: There are 122 files covering demographic and economic data. The first 31 files (WP001.csv – WP031.csv) cover demographic data. The remaining files (WP032.csv – WP122.csv) cover economic data. Demographic DDFs: Provide population data for the U.S., regions, states, Combined Statistical Areas (CSAs), Metropolitan Statistical Areas (MSAs), Micropolitan Statistical Areas (MICROs), Metropolitan Divisions (MDIVs), and counties. Each variable is in a separate .csv file. Variables: Total Population Population Age (breakdown: 0-4, 5-9, 10-15 etc. all the way to 85 & over) Median Age of Population White Population Population Native American Population Asian & Pacific Islander Population Hispanic Population, any Race Total Population Age (breakdown: 0-17, 15-17, 18-24, 65 & over) Male Population Female Population Economic DDFs: The other files (WP032.csv – WP122.csv) provide employment and income data on: Total Employment (by industry) Total Earnings of Employees (by industry) Total Personal Income (by source) Household income (by brackets) Total Retail & Food Services Sales ( by industry) Net Earnings Gross Regional Product Retail Sales per Household Economic & Demographic Flat File: A single file for total number of people by single year of age (from 0 to 85 and over), race, and gender. It covers all U.S., regions, states, CSAs, MSAs and counties. Years of coverage: 1990 - 2050 Single Year of Age by Race and Gender: Separate files for number of people by single year of age (from 0 years to 85 years and over), race (White, Black, Native American, Asian American & Pacific Islander and Hispanic) and gender. Years of coverage: 1990 through 2050. DATA AVAILABLE FOR 1970-2019; FORECASTS THROUGH 2050

Users can download data or view data tables on topics related to the labor force of the United States. Background Current Population Survey is a joint effort between the Bureau of Labor Statistics and the Census Bureau. It provides information and data on the labor force of the United States, such as: employment, unemployment, earnings, hours of work, school enrollment, health, employee benefits and income. The CPS is conducted monthly and has a sample of approximately 50,000 households. It is representative of the non-institutionalized US population. The sample provides estimates for the nation as a whole and serves as part of model-based estimates for individual states and other geographic areas. User Functionality Users can download data sets or view data tables on their topic of interest. Data can be organized by a variety of demographic variables, including: sex, age, race, marital status and educational attainment. Data is available on a national or state level. Data Notes The CPS is conducted monthly and has a sample of approximately 50,000 households. It is representative of the non-institutionalized US population. The sample provides estimates for th e nation as a whole and serves as part of model-based estimates for individual states and other geographic areas.

Historical Dataset of Harvard Avenue Performance Academy School District is provided by PublicSchoolReview and contain statistics on metrics:Comparison of Diversity Score Trends,Total Revenues Trends,Total Expenditure Trends,Average Revenue Per Student Trends,Average Expenditure Per Student Trends,Reading and Language Arts Proficiency Trends,Math Proficiency Trends,Science Proficiency Trends,Overall School District Rank Trends,Hispanic Student Percentage Comparison Over Years (2017-2023),Black Student Percentage Comparison Over Years (2007-2023),Two or More Races Student Percentage Comparison Over Years (2017-2023),Comparison of Students By Grade Trends

Includes brief description/table of contents, dataset in .txt format, variable codebook, and Stata do file.

This catalog record includes detailed variable-level descriptions, enabling data discovery and comparison. The data are not archived at ICPSR. Users should consult the data owners (via the Roper Center for Public Opinion Research) directly for details on obtaining the data. This collection includes variable-level metadata of the 2017 Discrimination in the United States Survey, a survey from Harvard T.H. Chan School of Public Health/Robert Wood Johnson Foundation/National Public Radio conducted by Social Science Research Solutions (SSRS). Topics covered in this survey include:Belief in discrimination against racial/ethnic minoritiesDiscrimination against men/womenDiscrimination against lesbian/gay/bisexual peopleDiscrimination against transgender peopleBiggest problem with discrimination against lesbian/gay/bisexual/transgender/queer (LGBTQ) peopleLive on tribal landsLocal/tribal government Discrimination based on raceDiscrimination based on genderDiscrimination based on being part of the LGBTQ communityReasons for avoiding seeking health careExperiences with discriminationDiscrimination resulting in fewer employment opportunitiesDiscrimination resulting in unequal payDiscrimination resulting in fewer chances for quality educationEncouraged to/discouraged from applying to collegePredominant groups living in respondent's areaNot feeling/being welcomed in neighborhood due to raceNot feeling/being welcomed in neighborhood due to being part of LGBTQ communityConsidered moving to another area because of discriminationComparing respondent's area to othersPolice using unnecessary force based on race/ethnicityAvoiding activities to avoid discrimination from policeExperiences caused by racial discriminationExperiences caused by gender discriminationExperiences caused by discrimination against LGBTQ communityLocal police force does/does not reflect racial/ethnic background of communityContacted by political representatives about voting/supporting causeRegistered to voteVote in 2016 presidential electionPhysical health statusMental health statusDisabilityChronic illnessVeterans AdministrationIndian Health ServicesSeeking health careInsurance coverageThe data and documentation files for this survey are available through the Roper Center for Public Opinion Research [Roper #31114655]. Frequencies and summary statistics for the 235 variables from this survey are available through the ICPSR social science variable database and can be accessed from the Variables tab.

Block-level (sumlev = 750) 2020 U.S. Census P.L. 94-171 data, with both Total Population and Voting-Age Population by major race/ethnicity categories. Generated via the "PL94171" package (https://corymccartan.github.io/PL94171/index.html) in R from original Census datasets on August 12, 2021. Note that the dataset is not an official Census Bureau product, and should not be claimed as such. Many thanks to Cory McCartan and Christopher T. Kenny for their work on the PL94171 package.

This catalog record includes detailed variable-level descriptions, enabling data discovery and comparison. The data are not archived at ICPSR. Users should consult the data owners (via the Roper Center for Public Opinion Research) directly for details on obtaining the data. This collection includes variable-level metadata of Quality of Health Care, a survey from the Harvard School of Public Health and the Robert Wood Johnson Foundation conducted by Social Science Research Solutions (SSRS). Topics covered in this survey include: Grading aspects of health care Value of health care versus cost Quality of care among local hospitals Familiar hospital versus higher-quality hospital Familiar surgeon versus higher-rated surgeon African Americans and health care quality Latinos and health care quality The data and documentation files for this survey are available through the Roper Center for Public Opinion Research [Roper #31092346]. Frequencies and summary statistics for the 64 variables from this survey are available through the ICPSR social science variable database and can be accessed from the Variables tab.

This dissertation examines ethnic patronage, local conflict, and election fraud in Kenya in three separate essays. Fraud, violence, and ethnicity are difficult to measure, and they often play a central role in narratives and theories about African politics. The essays in this dissertation draw on natural language processing, spatial statistics, and demography to improve measurement of these concepts and, in turn, our understanding of how they function in Kenya. The approaches developed here can be generalized to conflict, ethnicity, and fraud in other contexts. The first essay presents a method for extracting ethnic information from names. Existing methods give biased estimates by ignoring uncertainty in the mapping between names and ethnicity. I apply my improved, approximately unbiased method to data on political appointments from 1963 to 2010 in Kenya, and find that existing narratives about distributive politics do not accord with empirical patterns. The second essay examines patterns of violent ethnic targeting during Kenya's 2007-2008 post-election violence. I focus on patterns of arson, one of the key types of violence used in the Rift Valley. I find that incidence of arson is related to the presence of ethnic outsiders, and even more strongly related to measures of land quality, accessibility, and electoral competition. Using a difference-in-differences design, I show that arson caused a significant decrease in the number of Kikuyu and other immigrant ethnic groups registered to vote; no such decline is observed in indigenous ethnic groups. The third essay documents the prevalence of dead voters on Kenya's voter register prior to the contentious 2007 presidential elections, and shows how dead registered voters may have facilitated electoral fraud. Simply accounting for the number of dead voters demonstrates that turnout was greater than 100% in several opposition constituencies, and implausibly high in most of the incumbent president's home province. Ecological inference suggests that ballot-s tuffing occurred in candidate strongholds, rather than competitive constituencies. These results are consistent with the opposition party's allegations of fraud.

This is a dataset on district spending, demographics, and legislator characteristics for 2,517 state legislative districts in six American states in the years 1921, 1941, and 1961.

The Race and Carceral State Survey was fielded from May 11 to June 9, 2017 via Survey Sampling International to a sample of 8,093 White and 3,073 Black Americans. The survey instrument includes several experiments, detailed questions on experiences with carceral state institutions, racial attitudes, and standard demographic questions.

This dataset contains indicators for both the decennial Census and American Community Survey (ACS). Decennial Census indicators exist as the block, block group, and tract levels. ACS indicators are only at the block group and tract levels. The American Community Survey is produced annually by the U.S. Census Bureau in one, three, and five year estimates. It details basic information on demographics, race and ethnicity, economics, education levels, transportation modes, family and households characteristics, etc. The indicators here are based off of five year estimates. Raw data and more information on the American Community Survey can be found at https://www.census.gov/programs-surveys/acs/. (2018-01-15)

Why do communities with larger shares of ethnic and racial minorities have worse public goods provision? Many studies have emphasized the role of diversity in hindering public outcomes, but the question of causality remains elusive. We contribute to this debate by tracing the roots of both contemporary racial demography and public goods provision to the uneven historical expansion of the state. Focusing on new historical data from Brazil, we show that more remote municipalities with lower levels of state capacity in the past were more frequently selected by escaped slaves to serve as permanent settlements. Consequently, such municipalities have worse public services and larger shares of Afro-descendants today. These results highlight the pervasive endogeneity of the relationship between ethnic demography and public outcomes. The failure to account for context-dependent historical confounders raises concerns over the validity of previous findings regarding the social costs and benefits of any particular demographic composition.

The Georeferenced U.S. County-Level Population Projections, Total and by Sex, Race and Age, Based on the SSPs, 2020-2100 consists of county-level population projection scenarios of total population, and by age, sex, and race in five-year intervals for all U.S. counties for the period 2020 - 2100. These data have numerous potential uses and can serve as inputs for addressing questions involving sub-national demographic change in the United States in the near, middle- and long-term. To provide subnational (county) population projection scenarios for the United States essential for understanding long-term demographic changes, planning for the future, and decision-making in a variety of applications.

Users can purchase data regarding health and nutrition of Hispanic-origin participants of a national survey. Topics include: dietary practices; diabetes; acculturation; and the health of children, adolescents and adults, among others. Background The Hispanic Health and Nutrition Examination Survey (HHANES) was conducted by the Centers for Disease Control and Prevention (CDC). This nation-wide survey was conducted among Hispanic-origin respondents. This survey was conducted to generate estimates of the health of Hispanics in general and Latino subgroups. Topics include, but are not limited to: dietary practices, diabetes, depression, dental health, alcohol consumption, acculturation, child health, adolescent he alth, and adult health. User Functionality Users can purchase the dataset. Demographic information is available by race/ethnicity, income, age group, sex/gender, education, and marital status. Data Notes Surveys were conducted among a national sample Hispanic-origin respondents ranging in age from 6 months to 74 years of age. Surveys were completed between 1982 and 1984 and information is available on a national level. Respondents include Mexican Americans living in the southwestern states; Cuban-Americans in Florida; and Puerto Ricans in New York, Connecticut, and New Jersey. Data can be purchased through the National Technical Information Service (NTIS).