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.
Between 2023 and 2027, the majority of companies worldwide expect ***** changes to their workforce strategies. Those surveyed stated that ** percent would invest in learning and training on the job. ** percent said that they would accelerate the automation of processes, and ** percent said they would reduce the current workforce significantly.
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/who-we-are/organization/independent-offices/office-civil-rights/md-715-reports. The original data source is the system National Finance Center Insight owned by the Treasury Department. This dataset reports demographic data for the USAID workforce for fiscal year 2021.
The report contains thirteen (13) performance metrics for City's workforce development programs. Each metric can be breakdown by three demographic types (gender, race/ethnicity, and age group) and the program target population (e.g., youth and young adults, NYCHA communities) as well.
This report is a key output of an integrated data system that collects, integrates, and generates disaggregated data by Mayor's Office for Economic Opportunity (NYC Opportunity). Currently, the report is generated by the integrated database incorporating data from 18 workforce development programs managed by 5 City agencies.
There has been no single "workforce development system" in the City of New York. Instead, many discrete public agencies directly manage or fund local partners to deliver a range of different services, sometimes tailored to specific populations. As a result, program data have historically been fragmented as well, making it challenging to develop insights based on a comprehensive picture. To overcome it, NYC Opportunity collects data from 5 City agencies and builds the integrated database, and it begins to build a complete picture of how participants move through the system onto a career pathway.
Each row represents a count of unique individuals for a specific performance metric, program target population, a specific demographic group, and a specific period. For example, if the Metric Value is 2000 with Clients Served (Metric Name), NYCHA Communities (Program Target Population), Asian (Subgroup), and 2019 (Period), you can say that "In 2019, 2,000 Asian individuals participated programs targeting NYCHA communities.
Please refer to the Workforce Data Portal for further data guidance (https://workforcedata.nyc.gov/en/data-guidance), and interactive visualizations for this report (https://workforcedata.nyc.gov/en/common-metrics).
The Asia-Pacific region shows significant variations in labor force participation rates (LFPR) among the population aged 15 to 64 years, with North Korea’s LFPR estimated at ** percent and Afghanistan’s at about ** percent in 2024. This stark contrast highlights the diverse economic and social landscapes across the region, influencing workforce engagement. Regional trends and forecasts APAC’s rapidly aging population is putting growing pressure on the labor market, with projections showing a declining labor force participation rate across the region between 2023 and 2050. East Asia, where demographic changes are most pronounced, is expected to see a significant decline in LFPR among those aged 15 to 54 years, while participation among those over 54 years is projected to rise notably during this period. In contrast, South Asia is the only sub-region anticipated to record a modest increase in participation rates for the 25-54 years age group, highlighting a regional divergence in labor force trends Youth engagement in the labor force The labor force participation rates among youth populations vary greatly across Asia-Pacific countries, reflecting diverse economic conditions, education systems, and social factors. For example, North Korea and Australia boast high youth labor force participation rates of more than ** percent for those aged 15 to 24 years, while South Korea's rate for the same age group is considerably lower at around ** percent. In Australia, strong labor market access for students and abundant part-time work opportunities could enable high youth engagement alongside education. Meanwhile, South Korea's strong societal focus on academic achievement and the pursuit of higher education qualifications often leads to prolonged periods of education, which delays young people's entry into the workforce. Moreover, many APAC countries have high NEET (not in education, employment, or training) rates, particularly those in South Asia, underscoring challenges such as skills mismatches and limited job opportunities.
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The dataset contains estimates for the number of healthcare professionals in 15 different healthcare categories (e.g., Registered Nurse, Dentist, License Clinical Social Worker, etc.) based on completion of license renewal by Race/Ethnicity. There are two timeframes: all current licenses and recent licenses (since 2017). California population estimates are also included to provide a marker for each Race/Ethnicity. Each healthcare professional category can be compared across Race/Ethnicity groups and compared to statewide population estimates, so Race/Ethnicity shortages can be identified for each healthcare professional category. For instance, a notable difference between healthcare professional category and statewide population would indicate either underrepresentation or overrepresentation for that Race/Ethnicity, depending on the direction of the difference.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The series comes from the 'Current Population Survey (Household Survey)' The source code is: LNS11300000
The Labor Force Participation Rate is defined by the Current Population Survey (CPS) as “the number of people in the labor force as a percentage of the civilian noninstitutional population […] the participation rate is the percentage of the population that is either working or actively looking for work.”
The Labor Force Participation Rate is collected in the CPS and published by the BLS. It is provided on a monthly basis, so this data is used in part by macroeconomists as an initial economic indicator of current labor market trends. The labor force participation rate helps government agencies, financial markets, and researchers gauge the overall health of the economy.
Note that long-run changes in labor force participation may reflect secular economic trends that are unrelated to the overall health of the economy. For instance, demographic changes such as the aging of population can lead to a secular increase of exits from the labor force, shrinking the labor force and decreasing the labor force participation rate.
For more information, see: U.S. Bureau of Labor Statistics, CES Overview (https://www.bls.gov/web/empsit/cesprog.htm) U.S. Bureau of Labor Statistics, Concepts and Definitions (CPS) (https://www.bls.gov/cps/definitions.htm#lfpr)
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.
Nigeria's labor force continues to grow, with over 75.5 million people estimated to be economically active in 2023. This marks a significant increase from the previous year's figure of 73.3 million. The country's workforce has been steadily expanding over the past decade, reflecting the nation's demographic changes and economic development. Urban concentration and gender distribution The labor force in Nigeria is predominantly concentrated in urban areas, with approximately 51.3 million workers in cities compared to 37.6 million in rural communities. Interestingly, the gender distribution of the workforce shows a slight advantage for women, with about 45.4 million female workers compared to 43.6 million male workers. This gender balance in the labor force suggests progress in women's participation in the Nigerian economy. Age demographics and education levels The Nigerian workforce is relatively young, with the largest group being those aged 25 to 34 years, comprising around 23 million people. The second-largest group consists of individuals aged 35 to 44 years, numbering nearly 20.4 million. Education levels vary among workers, with a significant portion having completed secondary school. However, unemployment rates differ based on educational attainment, often with vocational or commercial training graduates experiencing the lowest unemployment rates. Notably, the State of Abia faces the highest unemployment rate at nearly 19 percent, while Lagos state boasts the lowest at 5.5 percent, highlighting regional disparities in job opportunities across the country.
Between 2021 and 2030, the highest growth in the Italian labor force will be among the population aged over 65 years (6.6 percent). On the contrary, the work force among the population aged 25 to 49 years is estimated to drop by 0.7 percent.
Italy's has, indeed, one of the oldest populations in the world. Its median age is forecasted to increase steadily and the number of births has been dropping constantly.
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2020 data excluded because the U.S. Census Bureau did not release 2020 ACS 1-year estimates due to COVID-19. Some racial and ethnic categories are suppressed to avoid misleading estimates when the relative standard error exceeds 30%.
Data Source: American Community Survey (ACS) 1-Year Estimates
Why This Matters
According to the U.S. Bureau of Labor Statistics, the labor force participation rate is an important measure of the health of the labor market, which represents the relative amount of labor resources available for the production of goods and services.
Changes in overall labor force participation reflect demographic, policy, and employer changes, whereas gaps in labor force participation between different segments of the working-age population reveal barriers to participation.
Black, Indigenous, and people of color participate in the labor market at lower rates than white people. These inequities reflect policies and practices, such as employment discrimination, racial segregation, and mass incarceration, among other factors.
The District's Response
Investing in targeted programs that provide pathways to higher wages and jobs, such as the Advanced Technical Centers (ATC), the DC Infrastructure Academy, and Career MAP, which aim to tackle the systemic barriers that keep people out of the labor force.
Administering federal and local safety net programs such as TANF For District Families, SNAP, unemployment insurance, and Medicaid that provide temporary cash and health benefits to address economic hardship.
Partners with the Department of Employment Services in building youth from the ground up through its various programs and services, including mentorship, counseling justice system services, job training development, and employment.
https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required
Graph and download economic data for Infra-Annual Labor Statistics: Working-Age Population Total: From 15 to 64 Years for United States (LFWA64TTUSM647S) from Jan 1977 to May 2025 about working-age, 15 to 64 years, population, and USA.
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Demographic trends in the BSSR workforce by gender, age, and citizenship.
This Indicator measures the percent of the unemployed population (ages 16 and up) in Oakland by race/ethnicity who did not participate in the City of Oakland’s Workforce Development program between 7/1/2016 and 6/30/2017. The percent that did participate for each race/ethnicity is calculated by dividing number of participants of that race/ethnicity by the number of unemployed people in the labor force in Oakland of that race/ethnicity. Percent that did not participate is 100% minus the percent that did participate. NOTE: Participation is not the most meaningful metric, but was the data available. In the future, we hope to replace this with a measurement of exit outcomes for participants by race/ethnicity (i.e., did participants successfully find jobs?).
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.
Number of persons in the labour force (employment and unemployment), unemployment rate, participation rate and employment rate by age group and gender. Data are presented for 12 months earlier, previous month and current month, as well as year-over-year and month-to-month level change and percentage change. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.
https://www.usa.gov/government-workshttps://www.usa.gov/government-works
State and county level demographic characteristics of the workforce. Source is the U.S. Census Longitudinal Employer-Household Dynamics Program, 2016 Annual Averages. Disability Characteristics are for 2012-2016 from the U.S. Census American Community Survey
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ACS 1-year estimates are based on data collected over one calendar year, offering more current information but with a higher margin of error. ACS 5-year estimates combine five years of data, providing more reliable information but less current. Both are based on probability samples. Some racial and ethnic categories are suppressed to avoid misleading estimates when the relative standard error exceeds 30%.
Data Source: American Community Survey (ACS) 1- & 5-Year Estimates
Why This Matters
According to the U.S. Bureau of Labor Statistics, the labor force participation rate is an important measure of the health of the labor market, which represents the relative amount of labor resources available for the production of goods and services.
Changes in overall labor force participation reflect demographic, policy, and employer changes, whereas gaps in labor force participation between different segments of the working-age population reveal barriers to participation.
Black, Indigenous, and people of color participate in the labor market at lower rates than white people. These inequities reflect policies and practices, such as employment discrimination, racial segregation, and mass incarceration, among other factors.
The District's Response
Investing in targeted programs that provide pathways to higher wages and jobs, such as the Advanced Technical Centers (ATC), the DC Infrastructure Academy, and Career MAP, which aim to tackle the systemic barriers that keep people out of the labor force.
Administering federal and local safety net programs such as TANF For District Families, SNAP, unemployment insurance, and Medicaid that provide temporary cash and health benefits to address economic hardship.
Partners with the Department of Employment Services in building youth from the ground up through its various programs and services, including mentorship, counseling justice system services, job training development, and employment.
https://www.enterpriseappstoday.com/privacy-policyhttps://www.enterpriseappstoday.com/privacy-policy
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
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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A summary of metrics to understand changes within occupations between 2016 and 2021, with a look at movements in and out of the workforce in addition to workforce demographics.
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.