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.

Except for JPMorgan Chase, Citigroup, Capital One and Bank of America, the share of minority employees in the total U.S.-based workforce of the leading U.S. banks was less than 50 percent. Among the observed banks, JPMorgan Chase had the most diverse workforce, with 56 percent of the employees who self-identified were racial minorities. JPMorgan Chase was followed by Citigroup, where the share of people of color was approximately 53 percent. Capital One ranked third in terms of racial diversity. Here, the share of non-white employees in the U.S.-based workforce was 51.4 percent. The share was the lowest at PNC Financial Services, where approximately 38 percent of the workforce were non-white.

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.

Americans have different views on how well the news media reflects the diversity of the population, a recent study found. Overall Americans were dissatisfied with the representation, with 39 percent of those surveyed responding that the performance is poor. However, Black respondents were the most positive when compared to other ethnic groups, with 31 percent stating that the media performs very well when reflecting public diversity. Adults of Hispanic ethnicity were found to be the most critical, with 40 percent unsatisfied with the portrayal of diversity in the media.

Bank of America's workforce diversity reveals a complex landscape, with white employees dominating executive and senior leadership roles at 71 percent in 2024. This stark contrast to other job categories highlights the ongoing challenges in achieving racial equity at the highest levels of the organization, despite progress in overall workforce diversity.

Diversity Index of Every US County using the Simpson Diversity Index: D = 1 - ∑(n/N)^2 (where n = number of people of a given race and N is the total number of people of all races, to get the probability of randomly selecting two people and getting two people of different races (ecological entropy))

Topographic diversity (D) is a surrogate variable that represents the variety of temperature and moisture conditions available to species as local habitats. It expresses the logic that a higher variety of topo-climate niches should support higher diversity (especially plant) and support species persistence given climatic change. To calculate D, the multi-scale Topographic Position Index (mTPI), being a dominant control of soil moisture (T), was used for measuring hillslope position. The mTPI was combined with the square-root transform for mTPI>0 (T') and with the standard deviation of the Continuous Heat-Insolation Load Index (CHILI), calculated at multiple scales (C') as: D = 1 - ((1-T') * (1-C'). It is based on the USGS's 10m NED DEM (available in EE as USGS/NED). The Conservation Science Partners (CSP) Ecologically Relevant Geomorphology (ERGo) Datasets, Landforms and Physiography contain detailed, multi-scale data on landforms and physiographic (aka land facet) patterns. Although there are many potential uses of these data, the original purpose for these data was to develop an ecologically relevant classification and map of landforms and physiographic classes that are suitable for climate adaptation planning. Because there is large uncertainty associated with future climate conditions and even more uncertainty around ecological responses, providing information about what is unlikely to change offers a strong foundation for managers to build robust climate adaptation plans. The quantification of these features of the landscape is sensitive to the resolution, so we provide the highest resolution possible given the extent and characteristics of a given index.

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  Dataset Card for dei_article_sentiment





  Dataset Summary

Diversity Equity and Inclusion related article title, content, url, sentiment and basis. Basis is a term I use to describe the underline topic related to diveristy I have four at the moment 1 = Gender, 2 = Race, 3 = Disability and 4 = Other.

  Supported Tasks and Leaderboards

[Needs More Information]

  Languages

English

  Dataset Structure





  Data Instances… See the full description on the dataset page: https://huggingface.co/datasets/deancgarcia/Diversity.

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.

Demographic Data - Diversity Efforts

Diversity, Equity, Inclusion, and Accessibility (DEIA): In FY 2022, DHS approved the FY 2022-FY 2026 ICE DEIA Strategic Plan and Directorate Implementation Plans, which illustrates why creating a diverse and inclusive workforce is fundamental to ICE’s continuing ability to perform its critical mission efficiently and effectively. During this time, DEIA policies issued to the ICE workforce included the ICE Anti-Harassment Policy, the Diversity Policy, and the Civil Rights and Civil Liberties Policy. Additionally, ODCR, in collaboration with OHC, drafted new requirements for ICE to mandate diverse interview panels when filling supervisory positions via the competitive procedures in support of the DHS Secretary’s priority to advance DEIA.

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 posi..., 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..., Google Sheets or Excel is required to open Lafferty et al. Data_File.xlsx Sankey Flow Show (THORTEC Software GmbH: www.sankeyflowshow.com) used to create the Sankey diagram Figure 2 produced in R

, Reference Information

Provenance for this README

• File name: README_Dataset-Academic-JEDI.txt
• Authors: Erin A. McKenney
• Other contributors: Diana J. R. Lafferty, Tru Hubbard, Sarah Trujillo, DeAnna Beasley
• Date created: 2023-06-08
• Date modified: 2023-10-18

Dataset Attribution and Usage

• Dataset Title: Data for the article “A path forward: creating an academic culture of justice, equity, diversity and inclusionâ€
• Persistent identifier: DOI:10.5061/dryad.cfxpnvxbb
• License: Use of these data is covered by the following license:
  • Title: CC0 1.0 Universal (CC0 1.0)
  • Specification: https://creativecommons.org/publicdomain/zero/1.0/; the authors respectfully request to be contacted by researchers interested in the re-use of these data so that the possibility of collaboration can be discussed.

Methodological Information

• All data were collected by the authors.
• Methods of data collection/generation: see manuscript and Supplemental Materials f...

This dataset tracks annual diversity score from 2021 to 2023 for American Indian Academy Of Denver vs. Colorado and School District No. 1 In The County Of Denver And State Of C

This dataset tracks annual diversity score from 2003 to 2023 for American Falls Joint School District vs. Idaho

Jaehun/data-diversity-nli-ood-test dataset hosted on Hugging Face and contributed by the HF Datasets community

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Stonington town, the largest racial group is White alone with a population of 15,411 (87% of the total Non-Hispanic population).

https://i.neilsberg.com/ch/stonington-town-ct-population-by-race-and-ethnicity.jpeg" alt="Stonington town Non-Hispanic population by race">

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: This column displays the racial categories (for Non-Hispanic) for the Stonington town
• Population: The population of the racial category (for Non-Hispanic) in the Stonington town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Stonington town 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 Stonington town Population by Race & Ethnicity. You can refer the same here

In 2022, racial diversity at Citigroup in the United States varied across job categories. On the executive and senior level, 66 percent of the officials and managers identified as white, 13.6 percent as Asian, approximately 8.7 percent as Hispanic or Latino, and Black or African American for each. The share of white employees decreased on lower corporate levels. The share of Asian employees was the highest among the professionals, at 27.1 percent. Hispanic employees were the most represented among technicians, at 29.2 percent, and the share of Black or African American employees was the highest among the administrative support workers, at 18.1 percent.

This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected as part of the Western Diversity Time Series (WDTS, formerly HyspIRI) program during nine flights aboard a NASA ER-2 aircraft over selected areas of California, U.S, from 2020-09-17 to 2020-10-15. The WDTS program will observe California's ecosystems and provide critical information on natural disasters such as volcanoes, wildfires, and drought. MASTER products can identify vegetation type and health and provide a benchmark for the state of the ecosystems against which future changes can be assessed. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each deployment, and browse images derived from each L1B data file.

Report on Demographic Data in New York City Public Schools, 2017-18 in response to Local Law No. 59. Test results, as provided in this report, only count students who were actively enrolled as of October 31, 2017. Therefore, they do not match numbers publicly available elsewhere, which include all test takers.

2017-18 Diversity Report Grades K-8 District