The resources in this dataset contain demographic information for the Oklahoma state government workforce. The resources present data from the current fiscal year along with demographic trends over time. The data can be used for workforce planning purposes.

List of Arlington County employees in permanent positions at the start of the current Fiscal Year. Data includes demographic information as well as the employee’s Department and Job Title.

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.

The dataset highlights key OPS workforce demographics extracted from the OPS payroll reporting system (WIN), including: * OPS size * Age and tenure * Annual sick leave credit usage * OPS salaries * OPS compensation data by gender A data dictionary is included to define all workforce demographics, metrics and limitations. This data has been released due to the demand expressed through a public vote to determine which datasets the Government of Ontario should publish. This was the fourth most voted on dataset out of a pool of approximately 1000 entries. The Data in this report is as of March 31, 2025, unless otherwise indicated. *[WIN]: Workforce Information Network *[OPS]: Ontario Public Service

Data updated quarterly.Data Attributes and Definitions -- Department: The department the employee works in.- Department ID: The numeric identifier for the department (typically 4 digits).- Job: The name for the job assigned to the employee.- Category: Grouping of employees in similar jobs/leadership roles.- Sub Category: Secondary grouping of employees within a category.- Race/Ethnicity: The race/ethnicity category which the employee identifies with (self-identified).- Gender: Designates the employee's gender (self-identified).- Age: The chronological number (age) assigned to the employee based on date of birth.- Age Group: Grouping of employees having approximately the same age or age range.- Original Hire Date: Date upon which the employee was originally hired.- Last Hire Date: Date upon which an employee was hired; may be a rehire date.- Pay Class: Defines how the employee gets paid for hours worked based on defined rules (full-time, part-time, hourly, etc.)- Data As of: The date to which the given data applies to.

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 dataset is provided by the department of Human Resources (HR) which details each City of Saint Paul department's or office's total workforce by race, gender, disability within E.E.O job groups.

County workforce job data, demographics, and job categories as defined by the Equal Employment Opportunity Commission. More information about the job categories can be found in Appendix 2 at the following link: https://eeocdata.org/EEO4/howto/instructionbooklet

This data asset was created in response to House Report 117-401, which stated, "The Committee directs the USAID Administrator, in consultation with the Director of the Office of Personnel Management and the Director of the Office of Management and Budget, to submit a report to the appropriate congressional committees, not later than 180 days after enactment of this Act, on USAID's workforce data that includes disaggregated demographic data and other information regarding the diversity of the workforce of USAID. Such report shall include the following data to the maximum extent practicable and permissible by law: 1) demographic data of USAID workforce disaggregated by grade or grade-equivalent; 2) assessment of agency compliance with the Equal Employment Opportunity Commission Management Directive 715; and 3) data on the overall number of individuals who are part of the workforce, including all U.S. Direct Hires, personnel under personal services contracts, and Locally Employed staff at USAID. The report shall also be published on a publicly available website of USAID in a searchable database format." This data asset fulfills the final part of this requirement, to publish the data in a searchable database format. The data are compiled from USAID's 2021 MD-715 report, available at https://www.usaid.gov/reports/md-715. The original data source is the system National Finance Center Insight owned by the Treasury Department.

Between 2020 and 2023, the total professional workforce of PwC in the United States had a majority of white employees. Those of an Asian background were the next most populous workforce, totaling approximately one-third of the white employment figures.

In June 2025, the civilian labor force amounted to 170.38 million people in the United States. The term civilian labor force is used by the U.S. Bureau of Labor Statistics (BLS) to describe the subset of Americans who have jobs or are seeking a job, are at least 16 years old, are not serving in the military, and are not institutionalized.

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

Workforce Population Showing Representation by Employment Equity Occupational Groups for Women, Aboriginal Peoples, Persons with Disabilities and Visible Minorities, 2021 Census and 2022 Canadian Survey on Disability.

Analysis of ‘City of Austin Workforce Demographics’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/c7247724-04ab-49ac-b2fe-b8fe53fba452 on 13 February 2022.

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

This dataset represents data beginning from 2010 to current date. The values represent the entire City of Austin workforce.

The goal of the City of Austin’s Employee Demographic data site is to provide information that is transparent and available to the public in a format that can be easily researched, filtered, analyzed and consumed. The Human Resource Department believes that by providing data sets to the public that are key to setting City priorities and assisting in making better informed decisions, it will enhance the collaboration among City departments and their external partners that will help bring a higher level of civic engagement with the public on local civic issues and concerns.

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

This dataset represents data beginning from 2010 to current date. The values represent the entire City of Austin workforce.

The goal of the City of Austin’s Employee Demographic data site is to provide information that is transparent and available to the public in a format that can be easily researched, filtered, analyzed and consumed. The Human Resource Department believes that by providing data sets to the public that are key to setting City priorities and assisting in making better informed decisions, it will enhance the collaboration among City departments and their external partners that will help bring a higher level of civic engagement with the public on local civic issues and concerns.

This transformed view of Employee Demographics - Public dataset counts the number of and percentage of city employees by race as self-reported by employee based on EEOC classification. This information is used by "City Employee vs. Community Demographics dataset" at https://citydata.mesaaz.gov/Economic-Development/Chart-Data-for-City-Employee-vs-Community-Demograp/bt2n-zimw

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.

Dataset provides the public with a snapshot of the County of Los Angeles workforce including the count of full-time permanent employees by department, employee demographics (i.e., ethnicity and gender) EEO Job Categories and, EEO Functions.