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.

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

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.

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

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.

The source of Employee Demographic data is an employee self-reported system in our City of Asheville ERP software (Tyler Technology - Munis). Employees self-identify for Race and Ethnicity.

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

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.

Filtered view of current employees as of dataset refresh date and includes employee job title, department name, EEO Category and Sworn status. This view redacts age group, race/ethnicity, gender and date of hire. For race/ethnicity and gender employee demographics see https://citydata.mesaaz.gov/Human-Resources/Employee-Demographics-Race-Ethnicity-Public/ty4p-25y2/about_data.

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.

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 dataset provides demographic information about City of Norfolk employees. The data is provided by Norfolk's Department of Human Resources and is updated daily. To view the most updated version of the dataset, please click here: https://data.norfolk.gov/Government/Employee-Demographics/vv96-9m5c/data_preview

The GIST Impact DEI data offers a glimpse into the gender pay gap trends at top European companies and delves deeper into how these pay disparities materialize at different levels of the hierarchy.

By analysing labour force participation and pay gap data, we provide a picture of how well these businesses are performing in terms of Diversity, Equity, and Inclusion (DEI). The analysis also serves as a benchmark to help gauge corporate progress on DEI commitments, particularly related to gender diversity.

GIST Impact’s analysis delivers meaningful quantitative data insights concerning women's workforce participation and career progression, drawing upon publicly available and secondary data sources. This method provides a more nuanced depiction of the impact of gender-inclusive policies and practices than simply presenting gender equality scores based on qualitative data.

Our workplace diversity Data analysis also gives context to theoretical frameworks such as the "glass ceiling" effect that underscores the discrimination faced by women in the workplace. The glass ceiling effect can have a significant impact on an individual's professional development, and addressing it requires proactive efforts to promote diversity, equity, and inclusion in the workplace.

GIST Impact's DEI data can be used to: - Measure diversity and gender pay gap of companies and portfolios - Benchmark companies within their sector - Benchmark a portfolio against indices - Screen companies for risk and opportunity - Integrate sustainability into portfolio decision-making

Status of employment for people aged 15+. Number of people who are in/out of the labour force, employed or unemployed. The "employed" category is disaggregated by Status in employment (for the main job). Status of employment is divided into 5 categories: employees, employers, own-account workers, contributing family workers and workers not classified by status. "Employees" comprises all individuals working in the public and private sector, "Contributing family workers" contains all individuals working to sell their products, producing goods for family use and those working to help a family business.

Find more Pacific data on PDH.stat.

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.

In 2024, the employment rate of the workforce of 55 years and older decreased to 37.3 percent. Employment rate among young adults (age 16-24) was at 50.9 percent in 2024. For monthly updates on employment in the United States visit the annual national employment rate here.

The Dimension Series provides a more in-depth analysis of census data. The publications employ large numbers of variables and address topics of special interest. They apply to Canada, the provinces and territories, with smaller sets of variables being used for smaller geographic units. Census variables are grouped into the following categories: counts and demographic data, ethnic origin, population group, place of birth, citizenship and immigration, language, Aboriginal peoples, schooling, household activities, labour force, income, families and households, housing, institutions and other collectives, as well as disability. The aggregate data tables are presented in Beyond 20/20 Format (.ivt).

Please note: This is a Synthetic data file, also known as a Dummy file - it is not real data. This synthetic file should not be used for purposes other than to develop an test computer programs that are to be submitted by remote access. Each record in the synthetic file matches the format and content parameters of the real Statistics Canada Master File with which it is associated, but the data themselves have been 'made up'. They do NOT represent responses from real individuals and should NOT be used for actual analysis. These data are provided solely for the purpose of testing statistical package 'code' (e.g. SPSS syntax, SAS programs, etc.) in preperation for analysis using the associated Master File in a Research Data Centre, by Remote Job Submission, or by some other means of secure access. If statistical analysis 'code' works with the synthetic data, researchers can have some confidence that the same code will run successfully against the Master File data in the Resource Data Centres. The Workplace and Employee Survey (WES) is designed to explore a broad range of issues relating to employers and their employees. The survey aims to shed light on the relationships among competitiveness, innovation, technology use and human resource management on the employer side and technology use, training, job stability and earnings on the employee side. The survey is unique in that employers and employees are linked at the micro data level; employees are selected from within sampled workplaces. Thus, information from both the supply and demand sides of the labour market is available to enrich studies on either side of the market. To create the best conditions for growth in the knowledge-based economy, governments need to fine-tune their policies on education, training, innovation, labour adjustment, workplace practices, industrial relations and industry development. The results from the survey will help clarify many of these issues and will assist in policy development. The Workplace and Employee Survey offers potential users several unique innovations: chief among these is the link between events occurring in workplaces and the outcomes for workers. In addition, being longitudinal, it allows for a clearer understanding of changes over time. There are two reference periods used for the WES. Questions concerning employment breakdown use the last pay period of March for the reference year while other questions refer to the last 12-month period ending in March of the reference year.

This dataset contains annual average CES data for California statewide and areas from 1990 - 2023. The Current Employment Statistics (CES) program is a Federal-State cooperative effort in which monthly surveys are conducted to provide estimates of employment, hours, and earnings based on payroll records of business establishments. The CES survey is based on approximately 119,000 businesses and government agencies representing approximately 629,000 individual worksites throughout the United States. CES data reflect the number of nonfarm, payroll jobs. It includes the total number of persons on establishment payrolls, employed full- or part-time, who received pay (whether they worked or not) for any part of the pay period that includes the 12th day of the month. Temporary and intermittent employees are included, as are any employees who are on paid sick leave or on paid holiday. Persons on the payroll of more than one establishment are counted in each establishment. CES data excludes proprietors, self-employed, unpaid family or volunteer workers, farm workers, and household workers. Government employment covers only civilian employees; it excludes uniformed members of the armed services. The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is responsible for the concepts, definitions, technical procedures, validation, and publication of the estimates that State workforce agencies prepare under agreement with BLS.

39.8% of workers from the Indian ethnic group were in 'professional' jobs in 2021 – the highest percentage out of all ethnic groups in this role.