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, 2024, unless otherwise indicated. *[WIN]: Workforce Information Network *[OPS]: Ontario Public Service

The General Practice Workforce series of Official Statistics presents a snapshot of the primary care general practice workforce. A snapshot statistic relates to the situation at a specific date, which for these workforce statistics is now the last calendar day each month. This monthly snapshot reflects the general practice workforce at 31 May 2024. These statistics present full-time equivalent (FTE) and headcount figures by four staff groups, (GPs, Nurses, Direct Patient Care (DPC) and administrative staff), with breakdowns of individual job roles within these high-level groups. For the purposes of NHS workforce statistics, we define full-time working to be 37.5 hours per week. Full-time equivalent is a standardised measure of the workload of an employed person. Using FTE, we can convert part-time and additional working hours into an equivalent number of full-time staff. For example, an individual working 37.5 hours would be classed as 1.0 FTE while a colleague working 30 hours would be 0.8 FTE. The term “headcount” relates to distinct individuals, and as the same person may hold more than one role, care should be taken when interpreting headcount figures. Please refer to the Using this Publication section for information and guidance about the contents of this publication and how it can and cannot be used. England-level time series figures for all job roles are available in the Excel bulletin tables back to September 2015 when this series of Official Statistics began. The Excel file also includes Sub-ICB Location-level FTE and headcount breakdowns for the current reporting period. CSVs containing practice-level summaries and Sub-ICB Location-level counts of individuals are also available. Please refer to the Publication content, analysis, and release schedule in the Using this publication section for more details of what’s available. We are continually working to improve our publications to ensure their contents are as useful and relevant as possible for our users. We welcome feedback from all users to PrimaryCareWorkforce@nhs.net.

Historical Employment Statistics 1990 - current. The Current Employment Statistics (CES) more information program provides the most current estimates of nonfarm employment, hours, and earnings data by industry (place of work) for the nation as a whole, all states, and most major metropolitan areas. The CES survey is a federal-state cooperative endeavor in which states develop state and sub-state data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor Statistics (BLS). Estimates produced by the CES program include both full- and part-time jobs. Excluded are self-employment, as well as agricultural and domestic positions. In Connecticut, more than 4,000 employers are surveyed each month to determine the number of the jobs in the State. For more information please visit us at http://www1.ctdol.state.ct.us/lmi/ces/default.asp.

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

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.

The Quarterly Census of Employment and Wages (QCEW) program (also known as ES-202) collects employment and wage data from employers covered by New York State's Unemployment Insurance (UI) Law. This program is a cooperative program with the U.S. Bureau of Labor Statistics. QCEW data encompass approximately 97 percent of New York's nonfarm employment, providing a virtual census of employees and their wages as well as the most complete universe of employment and wage data, by industry, at the State, regional and county levels. "Covered" employment refers broadly to both private-sector employees as well as state, county, and municipal government employees insured under the New York State Unemployment Insurance (UI) Act. Federal employees are insured under separate laws, but are considered covered for the purposes of the program. Employee categories not covered by UI include some agricultural workers, railroad workers, private household workers, student workers, the self-employed, and unpaid family workers. QCEW data are similar to monthly Current Employment Statistics (CES) data in that they reflect jobs by place of work; therefore, if a person holds two jobs, he or she is counted twice. However, since the QCEW program, by definition, only measures employment covered by unemployment insurance laws, its totals will not be the same as CES employment totals due to the employee categories excluded by UI.

In 2025, there were estimated to be approximately 3.6 billion people employed worldwide, compared to 2.23 billion people in 1991 - an increase of around 1.4 billion people. There was a noticeable fall in global employment between 2019 and 2020, when the number of employed people fell from due to the sudden economic shock caused by the COVID-19 pandemic. Formal vs. Informal employment globally Worldwide, there is a large gap between the informally and formally employed. Most informally employed workers reside in the Global South, especially Africa and Southeast Asia. Moreover, men are slightly more likely to be informally employed than women. The majority of informal work, nearly 90 percent, is within the agricultural sector, with domestic work and construction following behind. Women’s employment As the number of employees has risen globally, so has the number of employed women. Overall, care roles such as nursing and midwifery have the highest shares of female employees globally. Moreover, while the gender pay gap has shrunk over time, it still exists. As of 2024, the uncontrolled gender pay gap was 0.83, meaning women made, on average, 83 cents per every dollar earned by men.

SummaryThe Enrollments dataset contains basic information for local workforce program enrollments with OhioMeansJobs|Cleveland-Cuyahoga County (July 2022 - March 2025). Includes jobseeker demographic, location, employment barrier, and program enrollment information from ARIES, the state-wide case management system for workforce programs. Update FrequencyQuarterlyRelated Data ItemsWorkforce Program DashboardWorkforce Program Placements DatasetContactsGreater Cleveland Works (formerly Cleveland-Cuyahoga County Workforce Development Board) oversees the public workforce system – helping employers find and develop the skilled workers they need and helping jobseekers find good-paying jobs. Greater Cleveland Works currently serves over 10,000 jobseekers a year – helping the region prosper.1910 Carnegie Avenue, Cleveland, OH 44115 216-777-8200greaterclevelandworks.orgDashboard/Data-specific questions: email bryan.metlesitz@jfs.ohio.gov Data GlossaryField | Definition Customer_ID | A unique identification number for workforce data systemsCurrently_Enrolled | Identifies which customers are currently enrolled in a local workforce program. (snapshot in time of active enrollments) Enrollment_Program | Workforce programs available to job seekers. Enrollment_Program_Start_Date | The day a customer begins receiving services funded by a specific workforce program. Enrollment_Program_Completion_Date | The day a program enrollment is concluded. Enrollment_Completion_Reason | The outcome of a program enrollment. (the reason why a customer program enrollment is concluded) Customer_Age | The age of a customer determined by the Date of Birth entered into ARIESCustomer_Gender | The gender of a customerCustomer_Race | The race of a customerCustomer_Ethnicity | The ethnicity of a customerProgram_Year | The Program Year associated with the Employment Start DateThe CCWDB Program Year runs from July-JunePY_Quarter | The Program Quarter associated with the Employment Start Date (Q1 = July - September, Q2 = October - December, Q3 = January - March, Q4 = April - June)barriers_Low_Income | An individual or member of a family who receives now or in the last 6 months, income-based public assistance; in a family whose income is not higher than the poverty line or 705 of the lower living standard income level; is homeless; eligible for free or reduced price lunch; foster child for whom government payments are made or is an individual with a disability. barriers_Foster_Care_Status | An individual with a temporary living situation for kids whose parents cannot take care of them and whose need for care has come to the attention of child welfare agency staff. barriers_Homeless | Individual lacks a fixed, regular, and adequate nighttime residencebarriers_Veteran_Flag | Individual is a veteranbarriers_Customer_Disability_Status |  An individual without the ability to work at a substantial gainful activity due to a physical or mental impairmentbarriers_Youth_Offender | A youth involved with the justice systembarriers_Adult_Offender | An Adult involved with the justice systembarriers_TANF_Recipient | An individual who receives income and/or benefits from the federal Temporary Assistance to Needy Families program barriers_SSI_Recipient | An individual who receives Supplemental Security Income from the federal Social Security Administrationbarriers_SNAP_Recipient | An individual who receives help to buy food through the Supplemental Nutrition Assistance Programbarriers_Other_Public_Assistance_Recipient | An individual who receives some form of means-tested assistanceindex | Unique identification number for the CCWDB Open Data Placement datasetCity | The City in which the customer residesPostal | The Zip Code in which the customer residesWard | The City of Cleveland Ward in which the customer resides

This report shows monthly numbers of NHS Hospital and Community Health Services (HCHS) staff working in NHS Trusts and other core organisations in England (excluding primary care staff). Data are available as headcount and full-time equivalents and for all months from 30 September 2009 onwards. These data are a summary of the validated data extracted from the NHS HR and Payroll system. Additional statistics on staff in NHS Trusts and other core organisations and information for NHS Support Organisations and Central Bodies are published each: September (showing June statistics) December/January (showing September statistics) March (showing December statistics) June (showing March statistics) Quarterly NHS Staff Earnings, monthly NHS Staff Sickness Absence reports, and data relating to the General Practice workforce and the Independent Healthcare Provider workforce are also available via the Related Links below. Please note: We intend ceasing publication of the GPs in alternative settings data file as of next month (May data) meaning April 2023 will be the last issue of these data. Please contact us if you require access to these data on an ongoing basis. We welcome feedback on the methodology and tables within this publication. Please email us with your comments and suggestions, clearly stating Monthly HCHS Workforce as the subject heading, via enquiries@nhsdigital.nhs.uk or 0300 303 5678.

SummaryThe Placements dataset contains information on job placements attained through OhioMeansJobs|Cleveland-Cuyahoga County programs (July 2022 - March 2025). Includes basic job seeker information along with job placement information categorized to highlight local industry partnerships and initiatives. Data comes from ARIES, Ohio's system for workforce programs, but goes through an extensive manual cleaning and categorization. Update FrequencyQuarterlyRelated Data ItemsWorkforce Program DashboardWorkforce Program Enrollments DatasetContactsGreater Cleveland Works (formerly Cleveland-Cuyahoga County Workforce Development Board) oversees the public workforce system – helping employers find and develop the skilled workers they need and helping jobseekers find good-paying jobs. The Board currently serves over 10,000 jobseekers a year – helping the region prosper.1910 Carnegie Avenue, Cleveland, OH 44115 216-777-8200greaterclevelandworks.orgDashboard/Data-specific questions: email bryan.metlesitz@jfs.ohio.gov Data GlossaryField | Definition Customer_ID | A unique identification number for workforce data systemsCustomer_Age | The age of a customer determined by the Date of Birth entered into ARIESCustomer_Gender | The gender of a customerCustomer_Race | The race of a customerCustomer_Ethnicity | The ethnicity of a customerEmployer | The company hiring a CCWDB customerEmployer_City | The City in which the Employer is hiring a CCWDB customerEmployer_ZIP | The Zip Code in which the Employer is hiring a CCWDB customerJob_Title | The job title associated with a CCWDB customer job placement. CCWDB_Sector | A categorization of the job placement as it relates to CCWDB industry partnerships (Healthcare, Manufacturing, Information Technology)CCWDB_Job_Family | A categorization of the job placement as it related to the ONET Job Family, with minor adjustments to emphasize CCWDB industry partnerships (Built Environment, Healthcare)Program_Year | The Program Year associated with the Employment Start DateThe CCWDB Program Year runs from July-JunePY_Quarter | The Program Quarter associated with the Employment Start Date (Q1 = July - September, Q2 = October - December, Q3 = January - March, Q4 = April - June)Employment_Start_Date |Date customer begins employmentWage | The compensation associated with a new job placement. ($/hour) Enrollment_Program | Most recent workforce program a customer was enrolled before finding employmentbarriers_Low_Income | An individual or member of a family who receives now or in the last 6 months, income-based public assistance; in a family whose income is not higher than the poverty line or 705 of the lower living standard income level; is homeless; eligible for free or reduced price lunch; foster child for whom government payments are made or is an individual with a disability. barriers_Foster_Care_Status | An individual with a temporary living situation for kids whose parents cannot take care of them and whose need for care has come to the attention of child welfare agency staff. barriers_Homeless | Individual lacks a fixed, regular, and adequate nighttime residencebarriers_Veteran_Flag | Individual is a veteranbarriers_Customer_Disability_Status |  An individual without the ability to work at a substantial gainful activity due to a physical or mental impairmentbarriers_Youth_Offender | A youth involved with the justice systembarriers_Adult_Offender | An Adult involved with the justice systembarriers_TANF_Recipient | An individual who receives income and/or benefits from the federal Temporary Assistance to Needy Families program barriers_SSI_Recipient | An individual who receives Supplemental Security Income from the federal Social Security Administrationbarriers_SNAP_Recipient | An individual who receives help to buy food through the Supplemental Nutrition Assistance Programbarriers_Other_Public_Assistance_Recipient | An individual who receives some form of means-tested assistanceindex | Unique identification number for the CCWDB Open Data Placement datasetCity | The City in which the customer residesPostal | The Zip Code in which the customer residesWard | The City of Cleveland Ward in which the customer resides

The Occupational Employment Statistics (OES) program conducts a semi-annual mail survey designed to produce estimates of employment and wages for specific occupations. The OES program collects data on wage and salary workers in nonfarm establishments in order to produce employment and wage estimates for about 800 occupations. Data from self-employed persons are not collected and are not included in the estimates. The OES program produces these occupational estimates by geographic area and by industry. Estimates based on geographic areas are available at the National, State, Metropolitan, and Nonmetropolitan Area levels. The Bureau of Labor Statistics produces occupational employment and wage estimates for over 450 industry classifications at the national level. The industry classifications correspond to the sector, 3-, 4-, and 5-digit North American Industry Classification System (NAICS) industrial groups. More information and details about the data provided can be found at http://www.bls.gov/oes

1990 to present (approximate 2 month lag) Virginia Labor Force and Unemployment estimates by Month by County.

Special data considerations: Period values of "M01-M12" represent Months of Year; "M13" is the Annual Average.

U.S. Bureau of Labor Statistics; Local Area Unemployment Statistics, table la.data.54.Virginia Data accessed from the Bureau of Labor Statistics public database LABSTAT (https://download.bls.gov/pub/time.series/la/)

Supporting documentation can be found on the U.S. Bureau of Labor Statistics website under Local Area Unemployment Statistics, Handbook of Methods (https://www.bls.gov/opub/hom/lau/home.htm)

Survey Description: Labor force and unemployment estimates for States and local areas are developed by State workforce agencies to measure local labor market conditions under a Federal-State cooperative program. The Department of Labor develops the concepts, definitions, and technical procedures which are used by State agencies for preparation of labor force and unemployment estimates.

These estimates are derived from a variety of sources, including the Current Population Survey, the Current Employment Statistics survey, the Quarterly Census of Employment and Wages, various programs at the Census Bureau, and unemployment insurance claims data from the State workforce agencies.

To establish uniform labor force concepts and definitions in all States and areas consistent with those used for the U.S. as a whole, monthly national estimates of employment and unemployment from the Current Population Survey are used as controls (benchmarks) for the State labor force statistics.

Summary Data Available: Monthly labor force and unemployment series are available for approximately 7,500 geographic areas, including cities over 25,000 population, counties, metropolitan areas, States, and other areas.

For each area, the following measures are presented by place of residence:

• Total civilian labor force,
• Total number of people employed,
• Total number of people unemployed, and
• Unemployment rate

Data Characteristics: Rates are expressed as percents with one decimal place. Levels are measured as individual persons (not thousands) and are stored with no decimal places.

Mexico MX: Part Time Employment: % of Total Employment data was reported at 22.920 % in 2018. This records a decrease from the previous number of 23.210 % for 2017. Mexico MX: Part Time Employment: % of Total Employment data is updated yearly, averaging 24.385 % from Dec 2005 (Median) to 2018, with 14 observations. The data reached an all-time high of 25.090 % in 2009 and a record low of 22.660 % in 2005. Mexico MX: Part Time Employment: % of Total Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Employment and Unemployment. Part time employment refers to regular employment in which working time is substantially less than normal. Definitions of part time employment differ by country.; ; International Labour Organization, ILOSTAT database. Data retrieved in April 2019.; Weighted average; Relevance to gender indicator: More and more women are working part-time and one of the concern is that part time work does not provide the stability that full time work does.

This dataset contains data on full-time and part-time employment according to:

• a common definition of 30-usual weekly hours of work in the main job
• national definitions

In order to facilitate analysis and comparisons over time, historical data for OECD members have been provided over as long a period as possible, often even before a country became a member of the Organisation. Information on the membership dates of all OECD countries can be found at OECD Ratification Dates.

For detailed information on labour force surveys for all countries please see LFS_NOTES_SOURCES.

Means of transportation to work for workers 16 and older

This dataset provides classification level detail and definitions regarding the City's employment classifications. See the City Employment Compensation Plan dataset for hourly compensation rates.

This dataset contains incidences and gender composition of part-time employment with standardised (15-24, 25-54, 55-64, 65+, total) and detailed age groups. Data are further broken down by professional status - employees, total employment. Part-time employment is based on national definitions.

The definition of part-time work varies considerably across OECD countries Essentially three main approaches can be distinguished: i) a classification based on the worker's perception of his/her employment situation; ii) a cut-off (generally 30 or 35 hours per week) based on usual working hours, with persons usually working fewer hours being considered part-timers; iii) a comparable cut-off based on actual hours worked during the reference week. A criterion based on actual hours will generally yield a part-time rate higher than one based on usual hours, particularly if there are temporary reductions in working time as a result of holidays, illness, short-timing, etc. On the other hand, it is not entirely clear whether a classification based on the worker's perception will necessarily yield estimates of part-time work that are higher or lower than one based on a fixed cut-off. In one country (France) which changed from 1981 to 1982 from a definition based on an actual hours cut-off (30 hours) to one based on the respondent's perception, the latter criterion appeared to produce slightly higher estimates.

In order to facilitate analysis and comparisons over time, historical data for OECD members have been provided over as long a period as possible, often even before a country became a member of the Organisation. Information on the membership dates of all OECD countries can be found at OECD Ratification Dates.

For detailed information on labour force surveys for all countries please see LFS_NOTES_SOURCES.

China Total Employment data was reported at 733,510.000 Person th in 2022. This records a decrease from the previous number of 746,520.000 Person th for 2021. China Total Employment data is updated yearly, averaging 746,470.000 Person th from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 763,490.000 Person th in 2014 and a record low of 647,490.000 Person th in 1990. China Total Employment data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s China – Table CN.OECD.MSTI: Population, Labour Force and Employment: Non OECD Member: Annual.

The national breakdown by source of funds does not fully match with the classification defined in the Frascati Manual. The R&D financed by the government, business enterprises, and by the rest of the world can be retrieved but part of the expenditure has no specific source of financing, i.e. self-raised funding (in particular for independent research institutions), the funds from the higher education sector and left-over government grants from previous years.

The government and higher education sectors cover all fields of NSE and SSH while the business enterprise sector only covers the fields of NSE. There are only few organisations in the private non-profit sector, hence no R&D survey has been carried out in this sector and the data are not available.

From 2009, researcher data are collected according to the Frascati Manual definition of researcher. Beforehand, this was only the case for independent research institutions, while for the other sectors data were collected according to the UNESCO concept of “scientist and engineer”.

In 2009, the survey coverage in the business and the government sectors has been expanded.

Before 2000, all of the personnel data and 95% of the expenditure data in the business enterprise sector are for large and medium-sized enterprises only. Since 2000 however, the survey covers almost all industries and all enterprises above a certain threshold. In 2000 and 2004, a census of all enterprises was held, while in the intermediate years data for small enterprises are estimated.

Due to the reform of the S&T system some government institutions have become enterprises, and their R&D data have been reflected in the Business Enterprise sector since 2000.

In this table you will find annual figures on the composition of the Dutch working population according to the international definition. The Dutch definition of the labor force deviates from the definition that applies as an international standard: that of the International Labor Organization (ILO). As a result, the size and composition of the labor force differs. Firstly, the Dutch definition uses a threshold value of twelve hours for the number of hours per week that someone works or wants to work. This is not the case in the international definition. Second, the unemployed labor force is defined differently. According to the international definition, someone should be able to start a job within two weeks. In the Dutch definition, in certain cases, a period of three months is used for the period in which someone can start working or has developed search activities. Data available from 1996/1998 to 2011/2013 Status of the figures Figures based on the EBB are always final. Changes as of February 26, 2015 None, this table has been discontinued. Changes as of April 1, 2014: The figures for 2013 have been added to this table. All data on the profession in 2012 and 2013 are not yet available. As soon as this data becomes available it will be added to this table. The data on the level of education from 2012 onwards are provisional. When will new numbers come out? This table has been discontinued. The update of 1 April 2014 was the last update of this table. On 26 February 2015, new revised tables on the labor force were published. This revision of labor force statistics has two parts. The definitions have been adapted to the internationally agreed definitions and the data collection has been improved by being the first statistics office in Europe to conduct surveys via the internet. For more information on the revision, see the link to the press release in section 3.