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.

Introduction

Workplace Diversity Statistics: In recent years, many companies worldwide have focused on promoting diversity, equality, and inclusion (DEI) in their workplaces. They now see that having a diverse team is very important; it’s not just something they talk about but something that impacts all their activities. There are many benefits to DEI programs, and there are no drawbacks. A diverse workforce can lead to higher employee engagement and help attract new talent.

Overall, having a diverse team is one of the best ways to achieve high success and productivity. We shall shed more light on Workplace Diversity Statistics through this article.

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

Demographic Data - Diversity Efforts

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 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.

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

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.

Comprehensive demographic data including income distribution, education levels, age distribution, and household composition

Nzoia WeShareIt provides policymakers with an understanding of the complexity of making water allocation trade-offs between food, energy and nature. It is a multi-player hybrid cooperation game, that was designed and applied in 2016. The game was designed by the Delft University of Technology, in collaboration with Moi University. Design of the original WeShareIt focused on the Nile Basin. The Nile river is one of the longest rivers in the world with a basin area that covers one-tenth of Africa’s total landmass. After the application of WeShareIt game, in October 2015, recommendations were made to redesign the game for a smaller river basin within the Nile basin.

Comparing the percentage of city residents (community) ethnicity to the percentage of city employee ethnicity. Employee information comes from Employee Demographics: Ethnicity https://citydata.mesaaz.gov/Human-Resources/Employee-Demographics-Ethnicity/6kd3-uaks. Community information comes from Community Demographics: Ethnicity at https://citydata.mesaaz.gov/Census/Community-Demographics-Ethnicity/g34w-9rxw

Employee demographic data produced by City of Long Beach Human Resources Department.

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.

In 2024, 4.3 percent of U.S. Google leadership employees were of Latinx ethnicity. The majority of leadership employees, about six in ten, were white. Asian Google employees accounted for the second-largest group of employees in leadership positions.

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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))

description: 2015-16 Demographic Data - Diversity Efforts; abstract: 2015-16 Demographic Data - Diversity Efforts

Demographic reports on TSP participant behavior and investment manager diversity are reported annually to Congress and available to the public via FRTIB’s Open Data Plan. Reports are in PDF format with included data tables.

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.

This dataset provides comprehensive, employee-level workforce diversity metrics, including demographic details, job roles, participation in inclusion programs, and career progression indicators. It enables HR teams to monitor representation, identify diversity gaps, and evaluate the effectiveness of targeted initiatives across departments and locations. The dataset supports compliance reporting, strategic planning, and in-depth diversity and inclusion analytics.