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TwitterThis report includes data on the number of applications requested or restored and cases added during the month. This dataset is a selected subset of the entire report, available on the California Department of Social Services, Research and Data Reports (RADR) website at http://www.cdss.ca.gov/research/. CalWORKs is a welfare program that gives cash aid and services to eligible needy California families. The program serves all 58 counties in the state and is operated locally by county welfare departments. If a family has little or no cash and needs housing, food, utilities, clothing or medical care, they may be eligible to receive immediate short-term help. Families that apply and qualify for ongoing assistance receive benefits each month to help pay for housing, food and other necessary expenses. Monthly CalWORKs data is collected from the counties through submission of the CA 237CW CalWORKs Cash Grant Movement Report, which is used to report statistical information on CalWORKs caseload movement for Two Parent Families, Zero Parent Families, All Other Families, Temporary Assistance for Needy Families (TANF) Timed-Out Cases and Safety Net/Fleeing Felon/Long-Term Sanction Cases (SN/FF/LTS). NOTE: The presence of "-999" in data cells indicates that the number of applications is too small to be displayed and has been suppressed in order to protect individual clients' confidentiality.
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Graph and download economic data for Total Wages and Salaries in California (CAWTOT) from Q1 1998 to Q2 2025 about salaries, wages, CA, and USA.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for california in the U.S.
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TwitterVITAL SIGNS INDICATOR Jobs by Wage Level (EQ1)
FULL MEASURE NAME Distribution of jobs by low-, middle-, and high-wage occupations
LAST UPDATED January 2019
DESCRIPTION Jobs by wage level refers to the distribution of jobs by low-, middle- and high-wage occupations. In the San Francisco Bay Area, low-wage occupations have a median hourly wage of less than 80% of the regional median wage; median wages for middle-wage occupations range from 80% to 120% of the regional median wage, and high-wage occupations have a median hourly wage above 120% of the regional median wage.
DATA SOURCE California Employment Development Department OES (2001-2017) http://www.labormarketinfo.edd.ca.gov/data/oes-employment-and-wages.html
American Community Survey (2001-2017) http://api.census.gov
CONTACT INFORMATION vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator) Jobs are determined to be low-, middle-, or high-wage based on the median hourly wage of their occupational classification in the most recent year. Low-wage jobs are those that pay below 80% of the regional median wage. Middle-wage jobs are those that pay between 80% and 120% of the regional median wage. High-wage jobs are those that pay above 120% of the regional median wage. Regional median hourly wages are estimated from the American Community Survey and are published on the Vital Signs Income indicator page. For the national context analysis, occupation wage classifications are unique to each metro area. A low-wage job in New York, for instance, may be a middle-wage job in Miami. For the Bay Area in 2017, the median hourly wage for low-wage occupations was less than $20.86 per hour. For middle-wage jobs, the median ranged from $20.86 to $31.30 per hour; and for high-wage jobs, the median wage was above $31.30 per hour.
Occupational employment and wage information comes from the Occupational Employment Statistics (OES) program. Regional and subregional data is published by the California Employment Development Department. Metro data is published by the Bureau of Labor Statistics. The OES program collects data on wage and salary workers in nonfarm establishments to produce employment and wage estimates for some 800 occupations. Data from non-incorporated self-employed persons are not collected, and are not included in these estimates. Wage estimates represent a three-year rolling average.
Due to changes in reporting during the analysis period, subregion data from the EDD OES have been aggregated to produce geographies that can be compared over time. West Bay is San Mateo, San Francisco, and Marin counties. North Bay is Sonoma, Solano and Napa counties. East Bay is Alameda and Contra Costa counties. South Bay is Santa Clara County from 2001-2004 and Santa Clara and San Benito counties from 2005-2017.
Due to changes in occupation classifications during the analysis period, all occupations have been reassigned to 2010 SOC codes. For pre-2009 reporting years, all employment in occupations that were split into two or more 2010 SOC occupations are assigned to the first 2010 SOC occupation listed in the crosswalk table provided by the Census Bureau. This method assumes these occupations always fall in the same wage category, and sensitivity analysis of this reassignment method shows this is true in most cases.
In order to use OES data for time series analysis, several steps were taken to handle missing wage or employment data. For some occupations, such as airline pilots and flight attendants, no wage information was provided and these were removed from the analysis. Other occupations did not record a median hourly wage (mostly due to irregular work hours) but did record an annual average wage. Nearly all these occupations were in education (i.e. teachers). In this case, a 2080 hour-work year was assumed and [annual average wage/2080] was used as a proxy for median income. Most of these occupations were classified as high-wage, thus dispelling concern of underestimating a median wage for a teaching occupation that requires less than 2080 hours of work a year (equivalent to 12 months fulltime). Finally, the OES has missing employment data for occupations across the time series. To make the employment data comparable between years, gaps in employment data for occupations are ‘filled-in’ using linear interpolation if there are at least two years of employment data found in OES. Occupations with less than two years of employment data were dropped from the analysis. Over 80% of interpolated cells represent missing employment data for just one year in the time series. While this interpolating technique may impact year-over-year comparisons, the long-term trends represented in the analysis generally are accurate.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for oakland, ca in the U.S.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for stanton, ca in the U.S.
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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.
Disclaimer: For information regarding future updates or preliminary/final data releases, please refer to the Bureau of Labor Statistics Release Calendar: https://www.bls.gov/cew/release-calendar.htm
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Information on all public sector employees who were paid $85,000 or more in the year beginning in 2023 and are subject to the Public Sector Salary Disclosure Act. The Manitoba government discloses annually the compensation paid in the fiscal year or in the calendar year to a person who is a member of the civil service or who holds a specified public office if their annual compensation is equivalent to or exceeds the minimum legislated threshold for disclosure.This table lists those individuals defined above, along with related information described in the ‘fields’ below. This table is presented in the Manitoba Public Sector Compensation Disclosure application, which is a user-friendly interactive tool that adds functionality such as filtering, search, and data export.Fields included (Alias (Field name): Field description.) Sector (Sector): A standard set of sectors that will allow for searching and categorizing similar organizations.First Name (First_Name): First name or first initial based on the past practice of the organizationLast Name (Last_Name): Last name or badge number based on the past practice of your organizationTotal Compensation (Total_Compensation): Total compensation that includes employment contract, total value of all cash and non-cash salary or payments, allowances, bonuses, commissions and perquisites.Job Title (Job_Title): Job title, position name or position category, based on the past practice of the organization.Employer (Employer): This field will contain the name of the employer.Department/Region (Department_Region): This is an optional field for organizations that currently report departmentReporting Year (Reporting_Year): The fiscal year or calendar year in which the reporting period ended. (e.g. a fiscal year ending March 2021 and a calendar year ending December 2021 will both be listed as 2021)Reporting Schedule (Reporting_Schedule): This field will indicate which of the two reporting calendars the information reflects, based on the past practice of the organization.For more information on proactive disclosure by the Manitoba government, please visit the following site: https://www.gov.mb.ca/openmb/infomb/index.html Have thoughts on how this tool could be improved? Visit EngageMB.ca/OpenMB
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TwitterAverage hourly and weekly wage rate, and median hourly and weekly wage rate by North American Industry Classification System (NAICS), type of work, gender, and age group.
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Data is from Transparent California is provided by the Nevada Policy Research Institute as a public service and is dedicated to providing accurate, comprehensive and easily searchable information on the compensation of public employees in California.
Complete and accurate information is necessary to increase public understanding of government and help decision makers, including elected officials and voters, make informed decisions.
NPRI has been increasing transparency in government since first launching TransparentNevada.com in 2008.
All data on Transparent California has been compiled from public records requested and received from the associated political entity and is provided as a public service. We are not responsible for errors contained in those public records. Some jurisdictions are violating California's public records law and are refusing to provide names or other requested compensation information. In those cases, we have worked to provide as much information as we have received. Government jurisdictions in California do not maintain payroll and pension records in a uniform fashion. As such, and to help make the data easier to comprehend, we have consolidated some compensation categories. For instance, the “Overtime pay” column includes overtime compensation as the reporting agency classifies it. The "Other pay" category includes the compensation in the numerous other pay categories some public employees receive. "Total benefits" only includes benefits directly received by the employee: medical insurance (health, dental, and vision) and employer-paid retirement contributions. The total cost of the employee will be higher than the values reported here as there are associated costs (such as workman's comp, state unemployment insurance, medicare/SS costs, etc) that we do not report as employee compensation. The "Total pay & benefits" column underreports the total compensation of government employees whose government employer did not provided complete salary or benefit information. For pensions, all values reflect the actual monetary value of benefits received during the respective year reported.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for folsom, ca in the U.S.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for sunnyvale, ca in the U.S.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for riverside, ca in the U.S.
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Graph and download economic data for Number of Private Establishments for All Industries in Marin County, CA (ENU0604120510) from Q1 1990 to Q1 2025 about Marin County, CA; San Francisco; establishments; private industries; CA; private; industry; and USA.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for newark, ca in the U.S.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for upland, ca in the U.S.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for rialto, ca in the U.S.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for lawndale, ca in the U.S.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for norco, ca in the U.S.
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TwitterThis report includes data on the number of applications requested or restored and cases added during the month. This dataset is a selected subset of the entire report, available on the California Department of Social Services, Research and Data Reports (RADR) website at http://www.cdss.ca.gov/research/. CalWORKs is a welfare program that gives cash aid and services to eligible needy California families. The program serves all 58 counties in the state and is operated locally by county welfare departments. If a family has little or no cash and needs housing, food, utilities, clothing or medical care, they may be eligible to receive immediate short-term help. Families that apply and qualify for ongoing assistance receive benefits each month to help pay for housing, food and other necessary expenses. Monthly CalWORKs data is collected from the counties through submission of the CA 237CW CalWORKs Cash Grant Movement Report, which is used to report statistical information on CalWORKs caseload movement for Two Parent Families, Zero Parent Families, All Other Families, Temporary Assistance for Needy Families (TANF) Timed-Out Cases and Safety Net/Fleeing Felon/Long-Term Sanction Cases (SN/FF/LTS). NOTE: The presence of "-999" in data cells indicates that the number of applications is too small to be displayed and has been suppressed in order to protect individual clients' confidentiality.