This map service summarizes racial and ethnic diversity in the United States in 2012.

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). Diversity in the U.S. population is increasing. The diversity score for the entire United States in 2012 is 61.

The data shown is from Esri's 2012 Updated Demographics. The map adds increasing level of detail as you zoom in, from state, to county, to ZIP Code, to tract, to block group data. This map shows Esri's 2012 estimates using Census 2010 geographies.

In 2021, approximately **** percent of the U.S.-based employees at State Street Corporation were white. The second largest racial group in the workforce composition was Asian at **** percent, followed by Black or African American at *** percent, and Hispanic or Latino at *** percent. Racial diversity at State Street Corporation did not vary significantly between 2019 and 2021.

Explore demographic data on the Massachusetts executive branch workforce. Track our progress toward our goals to reflect the diversity of the people we serve, and to stand out as an employer of choice.

In 2021, the share of white employees at State Street Corporation was higher than ** percent in every position. It was the highest among the executive and senior-level officials and managers, where more than ** percent of the employees self-identified as white. The share of white employees was the lowest among the administrative support workers, where approximately ** percent of the employees were white.

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 2021, the annual Tier 1 diversity spend at State Street Corporation amounted to *** million U.S. dollars in the United States and in the United Kingdom. This was a ** percent increase compared to 2020. A new Tier 2 diverse spend program resulted in an additional ** million U.S. dollars on diversity spend in 2021.

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.

This dataset tracks annual diversity score from 1990 to 2022 for State Street Elementary School vs. California and Los Angeles Unified School District

About this dataset

Context

The dataset presents the median household income across different racial categories in United States. 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 United States population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 68.17% of the total residents in United States. Notably, the median household income for White households is $79,933. 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 $106,954. This reveals that, while Whites may be the most numerous in United States, Asian households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/united-states-median-household-income-by-race.jpeg" alt="United States 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 United States.
• 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 United States median household income by race. You can refer the same here

Reference Layer: Popular Demographics in the United States_This feature layer provides Esri 2018 demographic estimates for popular variables including: 2018 Total Population, 2018 Household Population, 2018 Median Age, 2018 Median Household Income, 2018 Per Capita Income, 2018 Diversity Index and many more. Data is available from country, state, county, ZIP Code, tract, and block group level with adjustable scale visibility. It is intended as a sample feature service to demonstrate smart mapping capabilities with Esri's Demographic data. Example feature views and web maps built from this layer include:Predominant Generations in the United StatesUnemployment in the United StatesMedian Home Value and IncomePopulation Growth or Decline?For more information, visit the Updated Demographics documentation. For a full list of variables, click the Data tab. Note: This layer will not being continuously updated or maintained. Note: This data has been filtered from a national dataset: https://bcgis.maps.arcgis.com/home/item.html?id=2718975e52e24286acf8c3882b7ceb18 to only show Broward County Statistics

Institutions of higher education (IHE) throughout the United States have a long history of acting out various levels of commitment to diversity advancement, equity, and inclusion (DEI). Despite decades of DEI “efforts,” the academy is fraught with legacies of racism that uphold white supremacy and prevent marginalized populations from full participation. Furthermore, politicians have not only weaponized education but passed legislation to actively ban DEI programs and censor general education curricula (https://tinyurl.com/antiDEI). Ironically, systems of oppression are particularly apparent in the fields of Ecology, Evolution, and Conservation Biology (EECB)–which recognize biological diversity as essential for ecological integrity and resilience. Yet, amongst EECB faculty, people who do not identify as cis-heterosexual, non-disabled, affluent white males are poorly represented. Furthermore, IHE lack metrics to quantify DEI as a priority. Here we show that only 30.3% of US-faculty positions advertised in EECB from Jan 2019-May 2020 required a diversity statement; diversity statement requirements did not correspond with state-level diversity metrics. Though many announcements “encourage women and minorities to apply,” empirical evidence demonstrates that hiring committees at most institutions did not prioritize an applicant’s DEI advancement potential. We suggest a model for change and call on administrators and faculty to implement SMART (i.e., Specific, Measurable, Achievable, Realistic, and Timely) strategies for DEI advancement across IHE throughout the United States. We anticipate our quantification of diversity statement requirements relative to other application materials will motivate institutional change in both policy and practice when evaluating a candidate’s potential “fit”. IHE must embrace a leadership role to not only shift the academic culture to one that upholds DEI, but to educate and include people who represent the full diversity of our society. In the current context of political censure of education including book banning and backlash aimed at Critical Race Theory, which further reinforce systemic white supremacy, academic integrity and justice are more critical than ever. Methods Here we investigated the (lack of) process in faculty searches at IHE for evaluating candidates’ ability to advance DEI objectives. We quantified the prevalence of required diversity statements relative to research and/or teaching statements for all faculty positions posted to the Eco-Evo Jobs Board (http://ecoevojobs.net) from January 2019 - May 2020 as a proxy for institutional DEI prioritization (Supplement). We also mapped the job posts that required diversity statements geographically to gauge whether and where diversity is valued in higher education across the US. Data analysis We pulled all faculty jobs posted on Eco-Evo jobs board (http://ecoevojobs.net) from Jan 1, 2019, to May 31, 2020. For each position, we recorded the Location (i.e., state), Subject Area, Closing Date, Rank, whether or not the position is Tenure Track, and individual application materials (i.e., Research statement, Teaching statement, combined Teaching and Research statement, Diversity statement, Mentorship statement). Of the 543 faculty positions posted during this time, we eliminated 299 posts because the web links were broken or application information was no longer available (i.e., “NA”), leaving 244 faculty job posts. For each of the retained posts, we coded the requirement of teaching, research, diversity, and/or mentorship statements as follows:

"Yes” = statement required “No” = statement not required “Other” = application materials did not explicitly require a Diversity Statement (i.e., option or suggested that applicants include a statement on diversity and inclusion as a component of their teaching and/or research statement or in their cover letter)

Data visualization We created a Sankey diagram using Sankey Flow Show (THORTEC Software GmbH: www.sankeyflowshow.com) to compare diversity and representation from the general population, through (Science, Technology, Engineering, and Mathematics) STEM academia (a career hierarchy often referred to as the “leaky pipeline”). We procured population data from the US Census Bureau (US Department of Commerce: https://www.census.gov/quickfacts/fact/table/US/PST045219) and quantified the diversity/representation in Conservation Biology (https://datausa.io/profile/cip/ecology-evolution-systematics-population-biology#demographics) and Ecology (https://datausa.io/profile/cip/conservation-biology) using Data USA (developed by Deloitte Touche Tohmatsu Limited and Datawheel). We used the 2015 Diversity Index (produced by PolicyLink and the USC Program for Environmental and Regional Equity: https://nationalequityatlas.org/indicators/Diversity_index/Ranking:33271/United_States/false/Year(s):2015/) to quantify relative ethnic diversity per state, and graphed Figure 2B using the tidyverse, rgdal, broom, and rgeos packages in R (see Base code used to produce Figure 2 in R, below). The Diversity index measures the representation of White, Black, Latino, Asian/Pacific Islander, Native American, and Mixed/other race in a given population. A maximum possible diversity score (1.79) would indicate even representation of all ethnic/racial groups. We checked all figures using the Color Blindness Simulator (ColBlindor: https://www.color-blindness.com/coblis-color-blindness-simulator/) to maintain inclusivity.

This statistic shows the beliefs of learning and development (L&D) professionals in the United States regarding diversity at their organization in 2019. During the survey, 33 percent of respondents stated that they believe their organization has a moderate amount of diversity.

Emergency medical services (EMS) workforce demographics in the United States do not reflect the diversity of the population served. Despite some efforts by professional organizations to create a more representative workforce, little has changed in the last decade. This scoping review aims to summarize existing literature on the demographic composition, recruitment, retention, and workplace experience of underrepresented groups within EMS. Peer-reviewed studies were obtained from a search of PubMed, CINAHL, Web of Science, ProQuest Thesis and Dissertations, and non-peer-reviewed (“gray”) literature from 1960 to present. Abstracts and included full-text articles were screened by two independent reviewers trained on inclusion/exclusion criteria. Studies were included if they pertained to the demographics, training, hiring, retention, promotion, compensation, or workplace experience of underrepresented groups in United States EMS by race, ethnicity, sexual orientation, or gender. Studies of non-EMS fire department activities were excluded. Disputes were resolved by two authors. A single reviewer screened the gray literature. Data extraction was performed using a standardized electronic form. Results were summarized qualitatively. We identified 87 relevant full-text articles from the peer-reviewed literature and 250 items of gray literature. Primary themes emerging from peer-reviewed literature included workplace experience (n = 48), demographics (n = 12), workforce entry and exit (n = 8), education and testing (n = 7), compensation and benefits (n = 5), and leadership, mentorship, and promotion (n = 4). Most articles focused on sex/gender comparisons (65/87, 75%), followed by race/ethnicity comparisons (42/87, 48%). Few articles examined sexual orientation (3/87, 3%). One study focused on telecommunicators and three included EMS physicians. Most studies (n = 60, 69%) were published in the last decade. In the gray literature, media articles (216/250, 86%) demonstrated significant industry discourse surrounding these primary themes. Existing EMS workforce research demonstrates continued underrepresentation of women and nonwhite personnel. Additionally, these studies raise concerns for pervasive negative workplace experiences including sexual harassment and factors that negatively affect recruitment and retention, including bias in candidate testing, a gender pay gap, and unequal promotion opportunities. Additional research is needed to elucidate recruitment and retention program efficacy, the demographic composition of EMS leadership, and the prevalence of racial harassment and discrimination in this workforce.

This graph shows the population of the U.S. by race and ethnic group from 2000 to 2023. In 2023, there were around 21.39 million people of Asian origin living in the United States. A ranking of the most spoken languages across the world can be accessed here. U.S. populationCurrently, the white population makes up the vast majority of the United States’ population, accounting for some 252.07 million people in 2023. This ethnicity group contributes to the highest share of the population in every region, but is especially noticeable in the Midwestern region. The Black or African American resident population totaled 45.76 million people in the same year. The overall population in the United States is expected to increase annually from 2022, with the 320.92 million people in 2015 expected to rise to 341.69 million people by 2027. Thus, population densities have also increased, totaling 36.3 inhabitants per square kilometer as of 2021. Despite being one of the most populous countries in the world, following China and India, the United States is not even among the top 150 most densely populated countries due to its large land mass. Monaco is the most densely populated country in the world and has a population density of 24,621.5 inhabitants per square kilometer as of 2021. As population numbers in the U.S. continues to grow, the Hispanic population has also seen a similar trend from 35.7 million inhabitants in the country in 2000 to some 62.65 million inhabitants in 2021. This growing population group is a significant source of population growth in the country due to both high immigration and birth rates. The United States is one of the most racially diverse countries in the world.

The relationship between resident species diversity and invasion is generally negative in experimental studies, but takes various forms in observational studies of natural communities. We hypothesized that stochastic species colonization, which applies to natural communities but not experimental communities generally assembled through simultaneous species introduction, may lead to non-negative diversity-invasion relationships via incurring priority effects. To test this hypothesis, we manipulated both resident species diversity and colonization history in sequentially assembled communities of bacterivorous protist species. We found that despite a significant effect of assembly history on invader abundance, invader abundance declined with diversity. This result was largely driven by positive selection effects associated with the dominant influence of an invasion-resistant species, which shared the most similar resource use pattern with the invader, and by the overall weak priority effects observed for the resident communities. Increasing species diversity, however, significantly strengthened priority effects, providing the first experimental support for the idea that larger species pools promote alternative community states. We suggest that elucidating mechanisms regulating the strength of priority effects may help understand variation in diversity-invasion relationships among natural communities.

This dataset contains the digitized treatments in Plazi based on the original journal article Smith-Pardo, Allan H., Carpenter, James M., Kimsey, Lynn (2020): The Diversity of Hornets in the Genus Vespa (Hymenoptera: Vespidae; Vespinae), Their Importance and Interceptions in the United States. Insect Systematics and Diversity 4 (3), No. 2: 1-27, DOI: 10.1093/isd/ixaa006

This dataset contains Hospital Supplier Diversity Plans.

As outlined in Health and Safety Code Section 1339.85-1339.87, licensed hospitals with operating expenses of fifty million dollars ($50,000,000) or more, and each licensed hospital with operating expenses of twenty-five million dollars ($25,000,000) or more that is part of a hospital system, shall submit an annual report to the department on its minority, women, LGBT, and disabled veteran business enterprise procurement efforts during the previous year.

Details on reporting requirements can be found in Section 1339.87.

For more on Hospital Supplier Diversity Plans.

Data notes: The information contained in a hospital’s plan on minority, women, LGBT, and disabled veteran business enterprises is provided for informational purposes only.

Suppliers are not required to disclose the above information to hospitals, and therefore not all diverse spending will be accurately identified.

This dataset tracks annual diversity score from 1991 to 2023 for State College Area High School vs. Pennsylvania and State College Area School District

The statistic shows the share of U.S. population, by race and Hispanic origin, in 2016 and a projection for 2060. As of 2016, about 17.79 percent of the U.S. population was of Hispanic origin. Race and ethnicity in the U.S. For decades, America was a melting pot of the racial and ethnical diversity of its population. The number of people of different ethnic groups in the United States has been growing steadily over the last decade, as has the population in total. For example, 35.81 million Black or African Americans were counted in the U.S. in 2000, while 43.5 million Black or African Americans were counted in 2017.

The median annual family income in the United States in 2017 earned by Black families was about 50,870 U.S. dollars, while the average family income earned by the Asian population was about 92,784 U.S. dollars. This is more than 15,000 U.S. dollars higher than the U.S. average family income, which was 75,938 U.S. dollars.

The unemployment rate varies by ethnicity as well. In 2018, about 6.5 percent of the Black or African American population in the United States were unemployed. In contrast to that, only three percent of the population with Asian origin was unemployed.

About this dataset

Context

The dataset presents the median household income across different racial categories in State Center. 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 State Center population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 88.04% of the total residents in State Center. Notably, the median household income for White households is $79,138. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $79,138.

https://i.neilsberg.com/ch/state-center-ia-median-household-income-by-race.jpeg" alt="State Center 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 State Center.
• 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 State Center median household income by race. You can refer the same here