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.

This dataset contains annual average CES data for California statewide and areas from 1990 to 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.

California Government Employees - Historical chart and current data through 2025.

Long-term Industry Projections for a 10-year time horizon are produced for the State and its labor market regions to provide individuals and organizations with an insight into future industry trends to make informed decisions on individual career and organizational program development. Long-term projections are revised every year. Data are not available for geographies below the labor market regions. Detail may not add to summary lines due to suppression of confidential data.

The 2020 Public Service Employee Survey (PSES) was administered by Advanis, on behalf of the Office of the Chief Human Resources Officer, Treasury Board of Canada. This comprehensive survey measured federal government employees’ opinions about their engagement, leadership, workforce, workplace, workplace well-being, compensation, diversity and inclusion, and the impacts of COVID-19. The 2020 Public Service Employee Survey was conducted from November 30, 2020 to January 29, 2021. A total of 188,786 employees in 87 federal departments and agencies responded to the 2020 Public Service Employee Survey, for a response rate of 61%. The 2020 Public Service Employee Survey datasets contain the results of the survey by year (2020, 2019 and 2018) for the Public Service and departments/agencies, and the results broken down by demographic characteristics (e.g., age, gender) and organizational units. Results for 2019 and 2018 are only provided for questions repeated in the 2020 Public Service Employee Survey.

Long-term Occupational Projections for a 10-year time horizon are provided for the State and its labor market regions to provide individuals and organizations with an occupational outlook to make informed decisions on individual career and organizational program development. Long-term projections are revised annually. Data are not available for geographies below the labor market regions. Detail may not add to summary lines due to suppression of data because of confidentiality and/or quality.

The Quarterly Census of Employment and Wages (QCEW) Program is a Federal-State cooperative program between the U.S. Department of Labor’s Bureau of Labor Statistics (BLS) and the California EDD’s Labor Market Information Division (LMID). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by California Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit industry codes from the North American Industry Classification System (NAICS) at the national, state, and county levels. At the national level, the QCEW program publishes employment and wage data for nearly every NAICS industry. At the state and local area level, the QCEW program publishes employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. In accordance with the BLS policy, data provided to the Bureau in confidence are used only for specified statistical purposes and are not published. The BLS withholds publication of Unemployment Insurance law-covered employment and wage data for any industry level when necessary to protect the identity of cooperating employers. Data from the QCEW program serve as an important input to many BLS programs. The Current Employment Statistics and the Occupational Employment Statistics programs use the QCEW data as the benchmark source for employment. The UI administrative records collected under the QCEW program serve as a sampling frame for the BLS establishment surveys. In addition, the data serve as an input to other federal and state programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses the QCEW data as the base for developing the wage and salary component of personal income. The U.S. Department of Labor’s Employment and Training Administration (ETA) and California's EDD use the QCEW data to administer the Unemployment Insurance program. The QCEW data accurately reflect the extent of coverage of California’s UI laws and are used to measure UI revenues; national, state and local area employment; and total and UI taxable wage trends. The U.S. Department of Labor’s Bureau of Labor Statistics publishes new QCEW data in its County Employment and Wages news release on a quarterly basis. The BLS also publishes a subset of its quarterly data through the Create Customized Tables system, and full quarterly industry detail data at all geographic levels.

This table contains 14 series, with data for years 1999 - 2011 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) Federal public sector employment (14 items: Federal public sector employees, as per Statistics Canada's statistical universe; Federal government business enterprise employees, as per Statistics Canada's statistical universe; Federal government employees, as per Statistics Canada's statistical universe; Employees common to Treasury Board of Canada Secretariat, Public Service Commission of Canada and Statistics Canada statistical universes; ...).

Overview: Each quarter, the Temporary Foreign Worker Program (TFWP) publishes Labour Market Impact Assessment (LMIA) statistics on Open Government Data Portal, including quarterly and annual LMIA data related to, but not limited to, requested and approved TFW positions, employment location, employment occupations, sectors, TFWP stream and temporary foreign workers by country of origin. The TFWP does not collect data on the number of TFWs who are hired by an employer and have arrived in Canada. The decision to issue a work permit rests with Immigration, Refugees and Citizenship Canada (IRCC) and not all positions on a positive LMIA result in a work permit. For these reasons, data provided in the LMIA statistics cannot be used to calculate the number of TFWs that have entered or will enter Canada. IRCC publishes annual statistics on the number of foreign workers who are issued a work permit: https://open.canada.ca/data/en/dataset/360024f2-17e9-4558-bfc1-3616485d65b9. Please note that all quarterly tables have been updated to NOC 2021 (5 digit and training, education, experience and responsibilities (TEER) based). As such, Table 5, 8, 17, and 24 will no longer be updated but will remain as archived tables. Frequency of Publication: Quarterly LMIA statistics cover data for the four quarters of the previous calendar year and the quarter(s) of the current calendar year. Quarterly data is released within two to three months of the most recent quarter. The release dates for quarterly data are as follows: Q1 (January to March) will be published by early June of the current year; Q2 (April to June) will be published by early September of the current year; Q3 (July to September) will be published by early December of the current year; and Q4 (October to December) will be published by early March of the next year. Annual statistics cover eight consecutive years of LMIA data and are scheduled to be released in March of the next year. Published Data: As part of the quarterly release, the TFWP updates LMIA data for 28 tables broken down by: TFW positions: Tables 1 to 10, 12, 13, and 22 to 24; LMIA applications: Tables 14 to 18; Employers: Tables 11, and 19 to 21; and Seasonal Agricultural Worker Program (SAWP): Tables 25 to 28. In addition, the TFWP publishes 2 lists of employers who were issued a positive or negative LMIA: Employers who were issued a positive LMIA by Program Stream, NOC, and Business Location (https://open.canada.ca/data/en/dataset/90fed587-1364-4f33-a9ee-208181dc0b97/resource/b369ae20-0c7e-4d10-93ca-07c86c91e6fe); and Employers who were issued a negative LMIA by Program Stream, NOC, and Business Location (https://open.canada.ca/data/en/dataset/f82f66f2-a22b-4511-bccf-e1d74db39ae5/resource/94a0dbee-e9d9-4492-ab52-07f0f0fb255b). Things to Remember: 1. When data are presented on positive or negative LMIAs, the decision date is used to allocate which quarter the data falls into. However, when data are presented on when LMIAs are requested, it is based on the date when the LMIA is received by ESDC. 2. As of the publication of 2022Q1- 2023Q4 data (published in April 2024) and going forward, all LMIAs in support of 'Permanent Residence (PR) Only' are included in TFWP statistics, unless indicated otherwise. All quarterly data in this report includes PR Only LMIAs. Dual-intent LMIAs and corresponding positions are included under their respective TFWP stream (e.g., low-wage, high-wage, etc.) This may impact program reporting over time. 3. Attention should be given for data that are presented by ‘Unique Employers’ when it comes to manipulating the data within that specific table. One employer could be counted towards multiple groups if they have multiple positive LMIAs across categories such as program stream, province or territory, or economic region. For example, an employer could request TFWs for two different business locations, and this employer would be counted in the statistics of both economic regions. As such, the sum of the rows within these ‘Unique Employer’ tables will not add up to the aggregate total.

Note: This dataset is no longer being updated as of June 2, 2025.

This dataset contains numbers of COVID-19 outbreaks and associated cases, categorized by setting, reported to CDPH since January 1, 2021.

AB 685 (Chapter 84, Statutes of 2020) and the Cal/OSHA COVID-19 Emergency Temporary Standards (Title 8, Subchapter 7, Sections 3205-3205.4) required non-healthcare employers in California to report workplace COVID-19 outbreaks to their local health department (LHD) between January 1, 2021 – December 31, 2022. Beginning January 1, 2023, non-healthcare employer reporting of COVID-19 outbreaks to local health departments is voluntary, unless a local order is in place. More recent data collected without mandated reporting may therefore be less representative of all outbreaks that have occurred, compared to earlier data collected during mandated reporting. Licensed health facilities continue to be mandated to report outbreaks to LHDs.

LHDs report confirmed outbreaks to the California Department of Public Health (CDPH) via the California Reportable Disease Information Exchange (CalREDIE), the California Connected (CalCONNECT) system, or other established processes. Data are compiled and categorized by setting by CDPH. Settings are categorized by U.S. Census industry codes. Total outbreaks and cases are included for individual industries as well as for broader industrial sectors.

The first dataset includes numbers of outbreaks in each setting by month of onset, for outbreaks reported to CDPH since January 1, 2021. This dataset includes some outbreaks with onset prior to January 1 that were reported to CDPH after January 1; these outbreaks are denoted with month of onset “Before Jan 2021.” The second dataset includes cumulative numbers of COVID-19 outbreaks with onset after January 1, 2021, categorized by setting. Due to reporting delays, the reported numbers may not reflect all outbreaks that have occurred as of the reporting date; additional outbreaks may have occurred that have not yet been reported to CDPH.

While many of these settings are workplaces, cases may have occurred among workers, other community members who visited the setting, or both. Accordingly, these data do not distinguish between outbreaks involving only workers, outbreaks involving only residents or patrons, or outbreaks involving both.

Several additional data limitations should be kept in mind:

• Outbreaks are classified as “Insufficient information” for outbreaks where not enough information was available for CDPH to assign an industry code.

• Some sectors, particularly congregate residential settings, may have increased testing and therefore increased likelihood of outbreak recognition and reporting. As a result, in congregate residential settings, the number of outbreak-associated cases may be more accurate.

• However, in most settings, outbreak and case counts are likely underestimates. For most cases, it is not possible to identify the source of exposure, as many cases have multiple possible exposures.

• Because some settings have been at times been closed or open with capacity restrictions, numbers of outbreak reports in those settings do not reflect COVID-19 transmission risk.

• The number of outbreaks in different settings will depend on the number of different workplaces in each setting. More outbreaks would be expected in settings with many workplaces compared to settings with few workplaces.

Percentage of employees required to be bilingual in English and French, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, third quarter of 2022.

VITAL SIGNS INDICATOR Change in Jobs by Industry (EC2)

FULL MEASURE NAME Employment by place of work by industry sector

LAST UPDATED May 2019

DESCRIPTION Change in jobs by industry is the percent change and absolute difference in the number of people who have jobs within a certain industry type in a given geographical area

DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2017 http://www.labormarketinfo.edd.ca.gov/

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment by place of work and by industry. Industries are classified by their North American Industry Classification System (NAICS) code. Vital Signs aggregates employment into 11 industry sectors: Farm, Mining, Logging and Construction, Manufacturing, Trade, Transportation and Utilities, Information, Financial Activities, Professional and Business Services, Educational and Health Services, Leisure and Hospitality, Government, and Other. EDD counts all public-sector jobs under Government, including public transportation, public schools, and public hospitals. The Other category includes service jobs such as auto repair and hair salons and organizations such as churches and social advocacy groups. Employment in the technology sector are classified under three categories: Professional and Business Services, Information, and Manufacturing. The latter category includes electronic and computer manufacturing. For further details of typical firms found in each sector, refer to the 2012 NAICS Manual (http://www.census.gov/cgi-bin/sssd/naics/naicsrch?chart=2012).

The Bureau of Labor Statistics (BLS) provides industry estimates for non-Bay Area metro areas. Their main industry employment estimates, the Current Employment Survey and Quarterly Census of Employment and Wages, do not provide annual estimates of farm employment. To be consistent, the metro comparison evaluates nonfarm employment for all metro areas, including the Bay Area. Industry shares are thus slightly different for the Bay Area between the historical trend and metro comparison sections.

The location quotient (LQ) is used to evaluate level of concentration or clustering of an industry within the Bay Area and within each county of the region. A location quotient greater than 1 means there is a strong concentration for of jobs in an industry sector. For the Bay Area, the LQ is calculated as the share of the region’s employment in a particular sector divided by the share of the nation’s employment in that same sector. Because BLS does not provide national farm estimates, note that there is no LQ for regional farm employment. For each county, the LQ is calculated as the share of the county’s employment in a particular sector divided by the share of the region’s employment in that same sector.

This table contains 393 series, with data for years 1981 - 2012 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (16 items: Canada and outside Canada;Newfoundland and Labrador;Prince Edward Island ...), Public sector, components (2 items: Employment;Wages and salaries ...), Sector (12 items: Public sector;Federal general government;Provincial and territorial general government;Government ...), Seasonal adjustment (2 items: Unadjusted;Seasonally adjusted ...).

The Employment Equity Act prescribes that this report cover the portions of the public service of Canada set out in Schedules I and IV of the Financial Administration Act. Seventy-three departments, agencies and commissions comprise the core public administration (CPA), for which the Treasury Board is the employer (see Table 1). The statistics in this report include only employees working for these organizations, which numbered 181,356 on March 31, 2014. This report includes information on indeterminate employees, term employees of three months or more, and seasonal employees, with the exception of those seasonal employees who are on leave without pay at the end of March for each fiscal year. No information is reported on students, casual workers or employees on leave without pay, such as those on care and nurturing leave and educational leave. Statistics in this document also exclude Governor in Council appointees, ministerial staff, federal judges and deputy ministers, who are also on the public service payroll. As required under the Employment Equity Act, annual reports to Parliament present information for the fiscal year beginning April 1 and ending March 31. The statistics of separate employers, covered under Schedule V of the Financial Administration Act, are not included in this report. Under the Employment Equity Act, separate employers that have more than 100 employees (e.g., the Canada Revenue Agency and the Canadian Food Inspection Agency) are required to provide their reports to the Office of the Chief Human Resources Officer (OCHRO) of the Treasury Board of Canada Secretariat only for the purposes of tabling in Parliament at the same time as this report. To view their employment equity reports, readers should visit those organizations’ websites, or contact them directly. Reports on employment equity in the Canadian Forces and with respect to members of the Royal Canadian Mounted Police are prepared by those organizations and are also tabled in Parliament at the same time as those of separate employers. To assure the consistency of data presented in this report, OCHRO uses the incumbent file, which contains information on all employees for whom the Treasury Board is the employer, in accordance with Schedules I and IV of the Financial Administration Act. Since 2011–12, the executive category includes data on the LC Group (Law Management Occupational Group) in its total workforce, which will need to be taken into consideration when comparing data historically. All tabulations, other than those for women, contain data obtained through self-identification. This data is provided voluntarily by employees and maintained separately and confidentially in the Employment Equity Data Bank by OCHRO, and where applicable, through the self-declaration of individuals applying to the public service through the Public Service Commission of Canada’s (PSC’s) Public Service Resourcing System. A reconciliation process is carried out each year by OCHRO, the PSC and the departments of the CPA to ensure that information derived from the Public Service Resourcing System, the Employment Equity Data Bank, and incumbent file harmonizes with the information from departmental sources. The completeness and accuracy of employment equity data for the CPA depend on the willingness of employees to self-identify and on departments providing opportunities for them to do so. Employees, including those engaged as students or casual workers, are given an opportunity to provide this information when they are hired and during departmental self-identification surveys or other campaigns. Furthermore, they may complete a self-identification form, available from their departmental employment equity coordinator, at any time.

This dataset contains non-seasonally adjusted California Unemployment Rate by age groups, from the Current Population Survey (CPS). The age group ranges are as follows: 16-19; 20-24; 25-34; 35-44; 45-54; 55-64; 65+. This data is based on a 12-month moving average.

As part of the Transport Canada Multimodal Safety and Security Programs Oversight Delivery Indicators, this table contains, starting with the first quarter of the 2017-2018 federal government fiscal year, the number of employees delivering oversight, by programs.

The Departmental Results Framework (DRF) is the strategic view of Defence’s mandate, displaying its Core Responsibilities and key performance information. It represents the corporate framework used to demonstrate plans, achievements, expenditures and performance results. This helps Canadians and parliamentarians understand what we do, what we seek to achieve, and how we will determine if we have achieved it. This dataset presents DRF 3.2 entitled “The health and well-being of the Defence team is well supported” and its indicator (DRI) 3.2.4 entitled “% of civilian employees who describe the workplace as psychologically healthy”. The 2020 Public Service Employee Survey was conducted from November 30, 2020 to January 29, 2021. The survey was administered by Advanis, on behalf of the Office of the Chief Human Resources Officer and Treasury Board of Canada. This comprehensive survey measured federal government employees’ opinions about their engagement, leadership, workforce, workplace, workplace well-being, compensation, diversity and inclusion, and the impacts of COVID-19. This dataset provides National Defence survey results for public service employees’ responses to Question 78 of the survey: “I would describe my workplace as being psychologically healthy.”

This dataset contains non-seasonally adjusted California Labor Force Participation Rate by age groups, from the Current Population Survey (CPS). The age group ranges are as follows: 16-19; 20-24; 25-34; 35-44; 45-54; 55-64; 65+. This data is based on a 12-month moving average.

Business' or organization's current level of total sales revenue and inventory levels compared to pre-pandemic levels, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, third quarter of 2024.

This dataset has results and the model associated with the publication Ciulla et al., (2024). It contains a U-Net semantic segmentation model (unet_model.h5) and associated code implemented in tensorflow 2.0 for the model training and identification of oil and gas well symbols in USGS historical topographic maps (HTMC). Given a quadrangle map (7.5 minutes), downloadable at this url: https://ngmdb.usgs.gov/topoview/, and a list of coordinates of the documented wells present in the area, the model returns the coordinates of oil and gas symbols in the HTMC maps. For reproducibility of our workflow, we provide a sample map in California and the documented well locations for the entire State of California (CalGEM_AllWells_20231128.csv) downloaded from https://www.conservation.ca.gov/calgem/maps/Pages/GISMapping2.aspx. Additionally, the locations of 1,301 potential undocumented orphaned wells identified using our deep learning framework or the counties of Los Angeles and Kern in California, and Osage and Oklahoma in Oklahoma are provided in the file found_potential_UOWs.zip. The results of the visual inspection of satellite imagery in Osage County is in the file visible_potential_UOWs.zip. The dataset also includes a custom tool to validate the detected symbols in the HTMC maps (vetting_tool.py). More details about the methodology can be found in the associated paper: Ciulla, F., Santos, A., Jordan, P., Kneafsey, T., Biraud, S.C., and Varadharajan, C. (2024) A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma. Accepted for publication in Environmental Science and Technology. The geographical coordinates provided correspond to the locations of potential undocumented orphaned oil and gas wells (UOWs) extracted from historical maps. The actual presence of wells need to be confirmed with on-the-ground investigations. For your safety, do not attempt to visit or investigate these sites without appropriate safety training, proper equipment, and authorization from local authorities. Approaching these well sites without proper personal protective equipment (PPE) may pose significant health and safety risks. Oil and gas wells can emit hazardous gasses including methane, which is flammable, odorless and colorless, as well as hydrogen sulfide, which can be fatal even at low concentrations. Additionally, there may be unstable ground near the wellhead that may collapse around the wellbore. This dataset was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.