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 **** percent in 2019 to **** 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 **** to **** percent.

Report on Demographic Data in New York City Public Schools, 2020-21Enrollment counts are based on the November 13 Audited Register for 2020. Categories with total enrollment values of zero were omitted. Pre-K data includes students in 3-K. Data on students with disabilities, English language learners, and student poverty status are as of March 19, 2021. Due to missing demographic information in rare cases and suppression rules, demographic categories do not always add up to total enrollment and/or citywide totals. NYC DOE "Eligible for free or reduced-price lunch” counts are based on the number of students with families who have qualified for free or reduced-price lunch or are eligible for Human Resources Administration (HRA) benefits. English Language Arts and Math state assessment results for students in grade 9 are not available for inclusion in this report, as the spring 2020 exams did not take place. Spring 2021 ELA and Math test results are not included in this report for K-8 students in 2020-21. Due to the COVID-19 pandemic’s complete transformation of New York City’s school system during the 2020-21 school year, and in accordance with New York State guidance, the 2021 ELA and Math assessments were optional for students to take. As a result, 21.6% of students in grades 3-8 took the English assessment in 2021 and 20.5% of students in grades 3-8 took the Math assessment. These participation rates are not representative of New York City students and schools and are not comparable to prior years, so results are not included in this report. Dual Language enrollment includes English Language Learners and non-English Language Learners. Dual Language data are based on data from STARS; as a result, school participation and student enrollment in Dual Language programs may differ from the data in this report. STARS course scheduling and grade management software applications provide a dynamic internal data system for school use; while standard course codes exist, data are not always consistent from school to school. This report does not include enrollment at District 75 & 79 programs. Students enrolled at Young Adult Borough Centers are represented in the 9-12 District data but not the 9-12 School data. “Prior Year” data included in Comparison tabs refers to data from 2019-20. “Year-to-Year Change” data included in Comparison tabs indicates whether the demographics of a school or special program have grown more or less similar to its district or attendance zone (or school, for special programs) since 2019-20. Year-to-year changes must have been at least 1 percentage point to qualify as “More Similar” or “Less Similar”; changes less than 1 percentage point are categorized as “No Change”. The admissions method tab contains information on the admissions methods used for elementary, middle, and high school programs during the Fall 2020 admissions process. Fall 2020 selection criteria are included for all programs with academic screens, including middle and high school programs. Selection criteria data is based on school-reported information. Fall 2020 Diversity in Admissions priorities is included for applicable middle and high school programs. Note that the data on each school’s demographics and performance includes all students of the given subgroup who were enrolled in the school on November 13, 2020. Some of these students may not have been admitted under the admissions method(s) shown, as some students may have enrolled in the school outside the centralized admissions process (via waitlist, over-the-counter, or transfer), and schools may have changed admissions methods over the past few years. Admissions methods are only reported for grades K-12. "3K and Pre-Kindergarten data are reported at the site level. See below for definitions of site types included in this report. Additionally, please note that this report excludes all students at District 75 sites, reflecting slightly lower enrollment than our total of 60,265 students

Diversity in Tech Statistics: In today's tech-driven world, discussions about diversity in the technology sector have gained significant traction. Recent statistics shed light on the disparities and opportunities within this industry. According to data from various sources, including reports from leading tech companies and diversity advocacy groups, the lack of diversity remains a prominent issue. For example, studies reveal that only 25% of computing jobs in the United States are held by women, while Black and Hispanic individuals make up just 9% of the tech workforce combined. Additionally, research indicates that LGBTQ+ individuals are underrepresented in tech, with only 2.3% of tech workers identifying as LGBTQ+. Despite these challenges, there are promising signs of progress. Companies are increasingly recognizing the importance of diversity and inclusion initiatives, with some allocating significant resources to address these issues. For instance, tech giants like Google and Microsoft have committed millions of USD to diversity programs aimed at recruiting and retaining underrepresented talent. As discussions surrounding diversity in tech continue to evolve, understanding the statistical landscape is crucial in fostering meaningful change and creating a more inclusive industry for all. Editor’s Choice In 2021, 7.9% of the US labor force was employed in technology. Women hold only 26.7% of tech employment, while men hold 73.3% of these positions. White Americans hold 62.5% of the positions in the US tech sector. Asian Americans account for 20% of jobs, Latinx Americans 8%, and Black Americans 7%. 83.3% of tech executives in the US are white. Black Americans comprised 14% of the population in 2019 but held only 7% of tech employment. For the same position, at the same business, and with the same experience, women in tech are typically paid 3% less than men. The high-tech sector employs more men (64% against 52%), Asian Americans (14% compared to 5.8%), and white people (68.5% versus 63.5%) compared to other industries. The tech industry is urged to prioritize inclusion when hiring, mentoring, and retaining employees to bridge the digital skills gap. Black professionals only account for 4% of all tech workers despite being 13% of the US workforce. Hispanic professionals hold just 8% of all STEM jobs despite being 17% of the national workforce. Only 22% of workers in tech are ethnic minorities. Gender diversity in tech is low, with just 26% of jobs in computer-related sectors occupied by women. Companies with diverse teams have higher profitability, with those in the top quartile for gender diversity being 25% more likely to have above-average profitability. Every month, the tech industry adds about 9,600 jobs to the U.S. economy. Between May 2009 and May 2015, over 800,000 net STEM jobs were added to the U.S. economy. STEM jobs are expected to grow by another 8.9% between 2015 and 2024. The percentage of black and Hispanic employees at major tech companies is very low, making up just one to three percent of the tech workforce. Tech hiring relies heavily on poaching and incentives, creating an unsustainable ecosystem ripe for disruption. Recruiters have a significant role in disrupting the hiring process to support diversity and inclusion. You May Also Like To Read Outsourcing Statistics Digital Transformation Statistics Internet of Things Statistics Computer Vision Statistics

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.

About this dataset

Context

The dataset presents the median household income across different racial categories in Wake Forest. 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 Wake Forest population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 70.43% of the total residents in Wake Forest. Notably, the median household income for White households is $116,222. 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 $137,159. This reveals that, while Whites may be the most numerous in Wake Forest, Asian households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/wake-forest-nc-median-household-income-by-race.jpeg" alt="Wake Forest 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 Wake Forest.
• 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 Wake Forest median household income by race. You can refer the same here

Demographic Data - Diversity Efforts

Diversity index information by neighborhoods in Johns Creek, GA.Neighborhood boundaries are created and maintained by Johns Creek, GA.Demographics data is from Esri GeoEnrichment Services.

Context

Workforce diversity is an increasingly salient issue, but it can be difficult to easily check how a specific company is performing. This dataset was created by Fortune to show what was discoverable by someone considering employment with one of the Fortune 500 firms and curious about their commitment to diversity and inclusion could find.

Content

This dataset contains the name of each firm, its rank in the 2017 Fortune 500, a link to its diversity and inclusion page or equal opportunity statement, and whether the company releases full, partial, or no data about the gender, race, and ethnicity of its employees. Additional detail is included where it was available. As there are over 200 fields in this dataset; please consult the data dictionary for details about specific features.

Acknowledgements

This dataset was assembled by Fortune.com data reporter Grace Donnelly. The details of her data preparation process can be found here.

Inspiration

Are the companies that release the most information more or less diverse than their peers? Are there any particular industries that stand out?

About this dataset

Context

The dataset presents the median household income across different racial categories in Savannah. 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 Savannah population by race & ethnicity, the population is predominantly Black or African American. This particular racial category constitutes the majority, accounting for 52.35% of the total residents in Savannah. Notably, the median household income for Black or African American households is $43,499. Interestingly, despite the Black or African American population being the most populous, it is worth noting that White households actually reports the highest median household income, with a median income of $71,602. This reveals that, while Black or African Americans may be the most numerous in Savannah, White households experience greater economic prosperity in terms of median household income.

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

Papua New Guinea is the most linguistically diverse country in the world. As of 2025, it was home to 840 different languages. Indonesia ranked second with 709 languages spoken. In the United States, 335 languages were spoken in that same year.

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

In 2024, more than ** percent of people employed in the motion picture and video industries in the United States identified as white. About one out of ten employees identified as Black or African American. That same year, almost ********** of employees in the U.S. film industry were male.

About this dataset

Context

The dataset presents the median household income across different racial categories in Sevier 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 Sevier County population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 92.54% of the total residents in Sevier County. Notably, the median household income for White households is $59,425. Interestingly, despite the White population being the most populous, it is worth noting that Black or African American households actually reports the highest median household income, with a median income of $111,137. This reveals that, while Whites may be the most numerous in Sevier County, Black or African American households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/sevier-county-tn-median-household-income-by-race.jpeg" alt="Sevier 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 Sevier 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 Sevier County median household income by race. You can refer the same here

Analysis of ‘2015-2016 Demographic Data - Diversity Efforts’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/ade5460e-c0fd-48ce-8245-913bfb2a5583 on 13 February 2022.

--- Dataset description provided by original source is as follows ---

Demographic Data - Diversity Efforts

--- Original source retains full ownership of the source dataset ---

About this dataset

Context

The dataset presents the median household income across different racial categories in South Pasadena. 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 South Pasadena population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 47.27% of the total residents in South Pasadena. Notably, the median household income for White households is $143,370. 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 $146,547. This reveals that, while Whites may be the most numerous in South Pasadena, Asian households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/south-pasadena-ca-median-household-income-by-race.jpeg" alt="South Pasadena 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 South Pasadena.
• 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 South Pasadena median household income by race. You can refer the same here

In 2023, the greatest share of players by ethnic group in the National Football League (NFL) were black or African American athletes, constituting just over ** percent of players within the NFL. Despite the large population of Hispanic or Latino people within the United States, there is a substantial underrepresentation within the NFL, with only *** percent of players identifying as such. National Football League The National Football League (NFL) is a professional American football league that was established in 1920 and now consists of 32 clubs divided into two conferences, the National Football Conference (NFC) and the American Football Conference (AFC). The league culminates in the Super Bowl, the NFL's annual championship game. As the league’s championship game, the Super Bowl has grown into one of the world's largest single-day sporting events, attracting high television ratings and generating billions of dollars in consumer spending. NFL revenues The NFL is one of the most profitable sports leagues in the world, generating a staggering **** billion U.S. dollars in 2022. This total revenue of all ** NFL teams has constantly increased over the past 15 years and, although this figure dropped significantly in 2020, this was largely as a result of the impact of coronavirus (COVID-19) containment measures. This significant drop in revenue demonstrates one of the primary impacts of COVID-19 on professional sports leagues. NFL franchises As a result of this profitability in non-pandemic times, the franchises of the NFL are attributed extremely high market values. The Dallas Cowboys were by far the most valuable franchise in the NFL, with a market value of **** billion US dollars in 2023. The high value of NFL franchises can be seen clearly when compared to those of the NBA, MLB, and NHL. Franchises within the NFL had an average market value of approximately *** billion U.S. dollars in 2023.

A number of characteristics of individuals are protected under the 2010 Equality Act, in order to limit the discrimination and disadvantage of groups with one or several shared characteristics. This table brings together a range of sources to present estimates of London's population by gender, age, ethnicity, religion, disability status, country of birth and sexual identity. It also shows population breakdowns for subgroups in each of these categories by broad age group and ethnicity.

The socio-economic position of individuals is not a protected characteristic, but is nonetheless an important factor affecting outcomes. The table therefore also includes social class at the household level.

Examination of the extent to which the immigrant population has become more diverse, using data from Switzerland as an example. Nationality is used as the basis, and diversity is expressed using the Herfindahl index. Considers changes between 1850 and 2010.

About this dataset

Context

The dataset presents the median household income across different racial categories in Sarasota. 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 Sarasota population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 73.92% of the total residents in Sarasota. Notably, the median household income for White households is $73,637. Interestingly, despite the White population being the most populous, it is worth noting that American Indian and Alaska Native households actually reports the highest median household income, with a median income of $140,593. This reveals that, while Whites may be the most numerous in Sarasota, American Indian and Alaska Native households experience greater economic prosperity in terms of median household income.

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

Clinical research is pivotal in assessing the safety and efficacy of new treatments in healthcare. However, the success of such research depends on the inclusion of a diverse and representative participant sample, which is currently lacking. This lack of diversity in biomedical research participants has significant repercussions, limiting the real-world applicability and accessibility of medical interventions, especially for underrepresented groups. Barriers to diverse participation include historical mistrust, logistical challenges, and financial constraints. Recent guidelines by government agencies and funding bodies emphasize the need for diversity in clinical trials, but specific strategies for inclusive recruitment are often lacking. This paper explores the use of digital methods to enhance diversity and inclusion in research recruitment. Digital tools, such as electronic medical records, social media, research registries, and mobile applications, offer promising opportunities for reaching diverse populations. Strategies include culturally tailored messaging, collaborations with community organizations, and the use of SEO to improve visibility and engagement. However, challenges such as privacy concerns, digital literacy gaps, and ethical considerations must be addressed. The promotion of diversity in clinical research recruitment is crucial for advancing health equity. By leveraging digital tools and adopting inclusive strategies, study teams can improve the diversity of study participants, ultimately leading to more applicable and equitable healthcare outcomes.