The percent chance that two people picked at random within an area will be of a different race/ethnicity. This number does not reflect which race/ethnicity is predominant within an area. The higher the value, the more racially and ethnically diverse an area. Source: U.S. Bureau of the Census, American Community Survey Years Available: 2010, 2011-2015, 2012-2016, 2013-2017, 2014-2018, 2015-2019, 2017-2021, 2018-2022

According to a survey conducted in 2023, 78 percent of employed adults who were Black believed that focusing on increasing diversity, equity, and inclusion at work was a good thing in the United States while 47 percent of employed adults who were White shared this belief.

Racial diversity is measured by a diversity index that is calculated using United States Census racial and ethnic population characteristics from the PL-94 data file. The diversity index is a quantitative measure of the distribution of the proportion of five major ethnic populations (non-Hispanic White, non-Hispanic Black, Asian and Pacific Islander, Hispanic, and Two or more races). The index ranges from 0 (low diversity meaning only one group is present) to 1 (meaning an equal proportion of all five groups is present). The diversity score for the United States in 2010 is 0.60. The diversity score for the San Francisco Bay Region is 0.84. Within the region, Solano (0.89) and Alameda (0.90) Counties are the most diverse and the remaining North Bay (0.55 - 0.64) Counties are the least diverse.

In 2023, the majority of the employees at Kickstarter identified as white or European. The share of white or European employees was the lowest in the leadership team, where 44.44 percent of the employees identified as such. The most represented racial minority group at Kickstarter was Asian.

ObjectiveVisible minorities are disproportionately affected by musculoskeletal disorders (MSD) and other diseases; yet are largely underrepresented in health research. The purpose of this scoping review was to identify barriers and strategies associated with increasing recruitment of visible minorities in MSD research.MethodsElectronic databases (MEDLINE, EMBASE, CINAHL, and PsycInfo) were searched. Search strategies used terms related to the concepts of ‘race/ethnicity’, ‘participation’, ‘research’ and ‘musculoskeletal’. All research designs were included. Two reviewers independently screened titles and abstracts, completed full-text reviews, and extracted data. Papers that did not focus on musculoskeletal research, include racial minorities, or focus on participation in research were excluded. Study characteristics (study location, design and methods; sample characteristics (size, age, sex and race); MSD of interest) as well as barriers and strategies to increasing participation of visible minorities in MSD research were extracted from each article and summarized in a table format.ResultsOf the 4,282 articles identified, 28 met inclusion criteria and were included. The majority were conducted in the United States (27 articles). Of the included studies, the groups of visible minorities represented were Black (25 articles), Hispanic (14 articles), Asian (6 articles), Indigenous (3 articles), Middle Eastern (1 article), and Multiracial (1 article). The most commonly cited barriers to research participation were mistrust, logistical barriers (e.g., transportation, inaccessible study location, financial constraints), and lack of awareness or understanding of research. Strategies for increasing diversity were ensuring benefit of participants, recruiting through sites serving the community of interest, and addressing logistical barriers.ConclusionUnderstanding the importance of diversity in MSD research, collaborating with communities of visible minorities, and addressing logistical barriers may be effective in reducing barriers to the participation of visible minorities in health research. This review presents strategies to aid researchers in increasing inclusion in MSD-related research.

About this dataset

Context

The dataset presents the median household income across different racial categories in Oklahoma County. 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 Oklahoma County population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 64.96% of the total residents in Oklahoma County. Notably, the median household income for White households is $71,592. 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 $80,596. This reveals that, while Whites may be the most numerous in Oklahoma County, Asian households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/oklahoma-county-ok-median-household-income-by-race.jpeg" alt="Oklahoma County 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) 2022 1-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 Oklahoma County.
• 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 Oklahoma County median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Fallston. 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 Fallston population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 99.05% of the total residents in Fallston. Notably, the median household income for White households is $58,591. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $58,591.

https://i.neilsberg.com/ch/fallston-pa-median-household-income-by-race.jpeg" alt="Fallston 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 Fallston.
• 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 Fallston median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in San Francisco township. 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 San Francisco township population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 95.31% of the total residents in San Francisco township. Notably, the median household income for White households is $133,763. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $133,763.

https://i.neilsberg.com/ch/san-francisco-township-mn-median-household-income-by-race.jpeg" alt="San Francisco township 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 San Francisco township.
• 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 San Francisco township median household income by race. You can refer the same here

In the map, each dot represents 100 people in four race categories: white (non-Hispanic), black (non-Hispanic), Hispanic/Latino, and Asian/Pacific Islander. Thus, the map also depicts population densities throughout the region. While the rural/ suburban areas in the region have largely white populations, many urban/densely populated areas in the region are racially diverse, with two or more ethnicities living in relatively non-segregated neighborhoods.

These are the data used for the Racial and Ethnic Diversity for the Austin MSA story map. The story map was published July 2024 but displays data from 2000, 2010, and 2020. Decennial census data were used for all three years. 2000: DEC Summary File 1, P004 2010: DEC Redistricting Data (PL 94-171), P2 2020: DEC Redistricting Data (PL 94-171), P2 Geographic crosswalks were used to harmonize 2000, 2010, and 2020 geographies. Racial and Ethnic Diversity Index for the Austin MSA Storymap: https://storymaps.arcgis.com/stories/88ee265f00934af7a750b57f7faebd2c City of Austin Open Data Terms of Use – https://data.austintexas.gov/stories/s/ranj-cccq

About this dataset

Context

The dataset presents the median household income across different racial categories in Oak Lawn. 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 Oak Lawn population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 76.78% of the total residents in Oak Lawn. Notably, the median household income for White households is $80,124. Interestingly, despite the White population being the most populous, it is worth noting that Some Other Race households actually reports the highest median household income, with a median income of $103,362. This reveals that, while Whites may be the most numerous in Oak Lawn, Some Other Race households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/oak-lawn-il-median-household-income-by-race.jpeg" alt="Oak Lawn 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 Oak Lawn.
• 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 Oak Lawn median household income by race. You can refer the same here

Bank of America's workforce has undergone a significant shift in racial diversity over the past six years. The share of white employees decreased from 53.2 percent in 2019 to 47.2 percent in 2024, marking a notable change in the company's demographic composition. Meanwhile, the representation of Hispanic, Asian, and Black racial groups grew steadily. The second-largest racial group in the observed period was Hispanic, whose share increased from 17.9 to 19.2 percent.

This map shows a comparison of diversity and median household income in the US by tract. Esri's Diversity Index measures the likelihood that two persons, chosen at random from the same area, belong to different races or ethnic groups. In theory, the index ranges from 0 (no diversity) to 100 (complete diversity). If an area's entire population is divided evenly into two race groups and one ethnic group, then the diversity index equals 50. As more race groups are evenly represented in the population, the diversity index increases. Minorities accounted for 30.9 percent of the population in 2000 and are expected to make up 42.3 percent of the population by 2023. Vintage of data: 2023Areas in a darker orange are less diverse than light blue areas with higher diversity. Median household income is symbolized by size. The national median household income is $58,100 and any household below the national value has the smallest symbol size. The largest size has a median household income over $100,000 per year. Esri Updated Demographics represent the suite of annually updated U.S. demographic data that provides current-year and five-year forecasts for more than two thousand demographic and socioeconomic characteristics, a subset of which is included in this layer. Included are a host of tables covering key characteristics of the population, households, housing, age, race, income, and much more. Esri's Updated Demographics data consists of point estimates, representing July 1 of the current and forecast years.Esri Updated Demographics DocumentationMethodologyUnderstanding Esri’s Updated Demographics portfolioEssential Esri Demographics vocabularyThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. This layer requires an ArcGIS Online subscription and does not consume credits. Please cite Esri when using this data.

In 2023, about 44 percent of Citigroup's U.S.-based employees identified as white, making them the largest demographic group at the American banking giant. Hispanic or Latino employees accounted for around 19 percent, while employees of Asian origin represented just over 20 percent. Approximately 11.5 percent of the workforce identified as Black or African American. Between 2019 and 2023, the share of white employees gradually declined, while the representation of non-white employees steadily increased.

This project is the first census of all local councillors in all four constitutive nations of the UK, conducted in 2018 and 2019. The local level, so important to our democracy, is too often ignored, and political representation is predominantly studied at the national level. The particular importance of local level to ethnic representation cannot be overstated as it is often the first step in politics and political careers for many minority politicians, and a first line of contact for minority individuals and communities in need of help. This project seeks to fill this research gap and to put local representation at the heart of studying how ethnic minorities are politically represented in Britain. Our research design was developed to study the experiences of ethnic minority local councillors from visibly racialised backgrounds of both genders, to further our understandings of the mechanisms that underpin representational inequalities. We collected the ethnicity, gender and political party of every local councillor in the UK by referring to council websites. We sought to sample our interviewees to reflect a range of non-white backgrounds and political experience as well as gender balance. Interviewees were asked about how they became involved in local politics, their views on the extent of demand for greater diversity in local government and their experiences of running for selection and election for local government as well as serving as a local councillor. The collection consists of interview transcripts with 95 ethnic minority local councillors, candidates and activists, or white British councillors in local government leadership positions.

Understandings of ethnic inequalities in the UK have developed substantially as a result of the work of The Centre on Dynamics of Ethnicity (CoDE). CoDE has successfully carried out an innovative programme of research, pursued challenging scientific objectives, and worked closely with a range of non-academic partners to impact on policy debates and development.

In a rapidly evolving political and policy context, we propose a further, ambitious programme of work that takes us in new directions with a distinct focus. We will move beyond nuanced description to understanding processes and causes of ethnic inequalities, and build directly on our established experience in interdisciplinary and mixed methods working. In addition, we will use a co-production approach, working with a range of partners, including key public institutions such as the BBC, universities, political parties, ethnic minority NGOs, activists, and individuals, in order to frame and carry out our research in ways that will maximise our societal impact and lead to meaningful change. Our overarching objectives are to: -Understand how ethnic inequalities develop in a range of interconnected domains -Examine how these processes relate to and are shaped by other social categories, such as gender, class, religion and generation -Understand how ethnic inequalities take shape, and are embedded, in institutional spaces and practices -Work closely with policy and practice partners to meaningfully address enduring ethnic inequalities -Pursue methodological developments with interdisciplinary mixed methods and co-production at their core -Achieve ongoing high quality international academic impact

Through a research plan divided into four work packages, we will examine ethnic inequalities in (1) higher education, (2) cultural production and consumption, (3) politics, representation and political parties and (4) pursue policy and institutional impact with our work in these areas. Alongside this, we are also conducting a programme of work on severe mental illness. These work packages will be organised around our ambition to understand, explain and impact on ethnic inequalities through a focus on institutional production of and responses to ethnic inequalities.

At the core of our methodological approach is interdisciplinary and mixed methods working. Our quantitative work will be predominantly secondary data analysis, making the best use of the wide range of resources in the UK (e.g. Understanding Society, Destination of Leavers of Higher Education Survey, British Election Study, ONS Longitudinal Studies). Our qualitative work will be based around ethnographic approaches that are attentive to the ways in which social processes play out differently in different sites and institutions. We are informed especially by the approach of institutional ethnography which prioritises an attention to the lived, everyday experience of inequality, but aims to clarify the wider social relations in which such experiences are embedded and by which they are shaped. Thus institutional ethnographies will be developed which begin with exploring the experience of those directly involved in institutional settings as a route to understanding how structures and practices of institutions shape individuals' experiences and...

This filtered view groups and sums parent dataset by Race (Not Hispanic or Latino) and Year (2022) and shows the count and percentage of city resident race. This information is used by the "City Employee vs. Community Demographics: Ethnicity" filtered view at https://citydata.mesaaz.gov/Diversity/Chart-Data-for-City-Employee-vs-Community-Demograp/bt2n-zimw

This layer summarizes racial and ethnic diversity in the United States. The Diversity Index shows the likelihood that two persons chosen at random from the same area, belong to different race or ethnic groups. The index ranges from 0 (no diversity) to 100 (complete diversity).The data shown is from Esri's 2020 Updated Demographic estimates using Census 2010 geographies. The map adds increasing level of detail as you zoom in, from state, to county, to ZIP Code, to tract, to block group data. Esri's U.S. Updated Demographic (2020/2025) Data: Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Additional Esri Resources:Esri DemographicsU.S. 2020/2025 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

About this dataset

Context

The dataset presents the median household income across different racial categories in Rock Island County. 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 Rock Island County population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 77.09% of the total residents in Rock Island County. Notably, the median household income for White households is $70,760. 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 $120,181. This reveals that, while Whites may be the most numerous in Rock Island County, Asian households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/rock-island-county-il-median-household-income-by-race.jpeg" alt="Rock Island County 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) 2022 1-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 Rock Island County.
• 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 Rock Island County median household income by race. You can refer the same here

How racially diverse are residents in Massachusetts? This topic shows the demographic breakdown of residents by race/ethnicity and the increases in the Non-white population since 2010.

About this dataset

Context

The dataset presents the median household income across different racial categories in Black Rock. 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 Black Rock population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 97.33% of the total residents in Black Rock. Notably, the median household income for White households is $65,485. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $65,485.

https://i.neilsberg.com/ch/black-rock-ar-median-household-income-by-race.jpeg" alt="Black Rock 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 Black Rock.
• 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 Black Rock median household income by race. You can refer the same here