Jobless Claims - Federal Workers in the United States increased to 635 People in September 13 from 572 People in the previous week. This dataset includes a chart with historical data for the United States Initial Jobless Claims - Federal Workers.

Businesses provides a detailed list of businesses from Data Axle. It includes company name, Standard Industrial Classification (SIC) and North American Industry Classification System (NAICS) industry code and location coordinates for every business in the database.Civilian employed population 16 years and over: Federal government workers. (2023 ACS 5-year estimates)

Pursuant to Executive Order 13583 and to the Government-wide Strategic Plan, which was published on November 17, 2011, the OPM Office of Diversity and Inclusion (ODI) developed a Diversity and Inclusion (D&I) Dashboard for agency use in workforce planning and reporting, with information culled from the Federal Employee Viewpoint Survey (FEVS) and the Enterprise Human Resources Integration (EHRI) data sets. The D&I Dashboard is a government specific tool created to provide agencies with demographic data about hiring, group attrition, employee inclusion perceptions, and overall accountability in regard to D&I efforts. One of the goals of the D&I Dashboard is to provide data that is formatted in such a way that anyone can view it, explore it and readily understand it. We provide summary data that cannot be connected to individuals.

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.

Government Payrolls in the United States increased by 22 thousand in September of 2025. This dataset provides the latest reported value for - United States Government Payrolls - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Government Electronic Directory Services (GEDS) provides public access to Government of Canada employee contact information as provided by participating departments. Encoded with the Latin Alphabet 1 (ISO 8859-1) character set. This is the dataset that contains all of the raw data within the Government of Canada Employee Contact Information system, not the searchable lookup. To search for contact information, please go to Government Electronic Directory Services (GEDS). (​​http://geds.gc.ca)

The Survey of Federal Employees is the Office of Personnel Management's first major survey of the work force since 1983. The questionnaire was designed to provide policy-makers with information that was not available from existing sources. Questions covered various personnel areas such as employee characteristics, employees' satisfaction with their jobs, supervisors, and organizations, performance management, training, work schedule arrangements, leave benefits, and dependent care responsibilities and the ways employees fulfill these responsibilities. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR09983.v2. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

Job trends across the federal government using historical data from jobs posted to USAJOBS, the federal government’s official employment site. The tools include visualizations and infographics exploring jobs posted over time, trending occupations, and jobs by location. You can tailor the tools to your own needs by selecting filters and date ranges. ÂÂ

Continued Claims for UI released by the CT Department of Labor. Continued Claims are total number of individuals being paid benefits in any particular week. Claims data can be access directly from CT DOL here: https://www1.ctdol.state.ct.us/lmi/claimsdata.asp

Claims are disaggregated by age, education, industry, race/national origin, sex, and wages.

The claim counts in this dataset may not match claim counts from other sources.

Unemployment claims tabulated in this dataset represent only one component of the unemployed. Claims do not account for those not covered under the Unemployment system (e.g. federal workers, railroad workers or religious workers) or the unemployed self-employed.

Claims filed for a particular week will change as time goes on and the backlog is addressed.

For data on continued claims at the town level, see the dataset "Continued Claims for Unemployment Benefits by Town" here: https://data.ct.gov/Government/Continued-Claims-for-Unemployment-Benefits-by-Town/r83t-9bjm

For data on initial claims see the following two datasets:

"Initial Claims for Unemployment Benefits in Connecticut," https://data.ct.gov/Government/Initial-Claims-for-Unemployment-Benefits/j3yj-ek9y

"Initial Claims for Unemployment Benefits by Town," https://data.ct.gov/Government/Initial-Claims-for-Unemployment-Benefits-by-Town/twvc-s7wy

Employment by Industry reports several labor statistics related to employment and wage. Domain Frequency Annual Full Description Employment by Industry reports the total Number of Employers, the Annual Average Employment, and the Annual Average Wage by industry at the town, county, and state level. Industries included in this dataset vary from location to location. In as many locations as possible, five specific industry segments are consistently present (Construction, Manufacturing, Retail Trade, All Industries, Total Government) as well as the largest 3 out of the remaining segments for that location, ranked by Annual Average Employment. Not every location has data for every segment, and some may not have data for the five consistently reported segments. This data is from the Connecticut Department of Labor Quarterly Census of Employment and Wages (QCEW). The program produces a comprehensive tabulation of employment and wage information for workers covered by Connecticut Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program.

US Federal Funding Gaps History

Historical US Federal Funding Gaps & Political Party Control

By Throwback Thursday [source]

About this dataset

This dataset is a comprehensive historical record of federal funding gaps in the United States, spanning from 1976 to 2018. It provides detailed information on each funding gap, including the start and end dates, total duration in days, and whether or not employees were furloughed.

The dataset also includes data on the political party control during each funding gap, specifically for both the Senate and the House of Representatives. For each chamber, it indicates which party had control - either Democrats or Republicans - as well as any representation by Independent members.

Additionally, this dataset contains valuable insights into the impact of federal funding gaps on government employees. It records the number of employees who were furloughed during each gap, allowing for analysis of workforce disruption and potential economic consequences.

By leveraging this dataset's wealth of information on federal funding gaps in the United States over more than four decades, researchers can gain a deeper understanding of these significant events in governmental operations and their broader implications for various stakeholders

How to use the dataset

Introduction:

• Understanding the Columns: a) Start Date: The date when a federal funding gap began. b) End Date: The date when a federal funding gap ended. c) Total days: The duration of the federal funding gap in days. d) Employees furloughed: A boolean value indicating whether or not employees were furloughed during that specific funding gap. (True = Employees were furloughed, False = No employee was furloughed.) e) Number of Employees Furloughed: The actual count of employees who were furloughed during that specific funding gap. f) Senate Control: The political party that had control over the Senate during each particular period specified. (Categorical - Democratic, Republican) g) Senate Democrats: The number of Democratic senators serving during that specific funding gap. h) Senate Republicans: The number of Republican senators serving during that particular period specified. i) Senate Independents: The number of Independent senators serving at that time frame. j ) House Control :He political party that had control over House Representatives throughoted specific dataried by each perticularnce k ) House Democrats -

• Analyzing Duration and Furloughs: You can compute various statistics about federal funding gaps using relevant columns such as 'Start Date,' 'End Date,' 'Total days,' 'Employees furloughed,' 'Number of Employees Furloughed. For example:

  • Calculate the average duration of funding gaps during a specific time period.
  • Determine the total number of funding gaps that resulted in employee furloughs.
  • Analyze the average number of employees furloughed during various periods.

• Understanding Party Control: The dataset includes information about political party control over Senate and House Representatives during funding gaps. • Analyzing Senate Control:

  • Determine which party controlled the Senate during each funding gap period.
  • Compare the prevalence of Democratic, Republican, or Independent control over time.
  1. Exploring

Research Ideas

• Analyzing the impact of federal funding gaps on government employees: This dataset can be used to study the number of employees who were furloughed during each funding gap and analyze the duration of their furlough. It can provide insights into the economic effects and hardships faced by government workers during such periods.
• Examining the political dynamics during funding gaps: By analyzing the control of both the House of Representatives and Senate during each funding gap, this dataset can shed light on how political party control affected negotiations and resolutions. It can help identify patterns or trends in bipartisan cooperation or conflict during these periods.
• Comparing different funding gaps over time: With information on start dates, end dates, and total days for each gap, this dataset allows for comparisons across different periods in history. Researchers can assess whether funding gaps have become more frequent or longer-lasting over time and identify any patterns that may exist in relation to economic factors or political developments

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset d...

The files in this deposit were scraped from https://www.opm.gov/data/datasets/ on Feb 12, 2025.The U.S. Office of Personnel Management (OPM) serves as the chief human resources agency and personnel policy manager for the Federal Government.Archive created by Lars Vilhuber, Cornell University. Original data are "a work prepared by an officer or employee of the United States Government as part of that person's official duties". Under section 105 of the Copyright Act of 1976,such works are not entitled to domestic copyright protection under U.S. law and are therefore in the public domain.

This dataset contains Iowa civilian employed population estimate for individuals 16 years or older by by sex and class of worker for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Table B24080.

Sex includes the following: Both, Male, and Female.

Class of Worker includes the following: All Classes; Private-for-Profit Wage and Salary Workers; Private-for-Profit Wage and Salary Workers, Employee; Private-for-Profit Wage and Salary Workers, Self-Employed in Own INC; Private Not-for-Profit Wage and Salary Workers; Local Government Workers; State Government Workers; Federal Government Workers; Self-Employed; and Unpaid Family Workers.

Used to store information on Federal employees in the Senior Executive Service (SES) and appointed employees in the Schedule C System. Every four years, just after the Presidential election, the United States Government Policy and Supporting Positions, commonly known as the Plum Book, is published, alternately, by the Senate and the House. The Plum Book is used to identify presidentially appointed positions within the Federal Government. The data in the Plum Book comes from the ESCS but may be slightly modified by the Government Printing Office before publication based on additional information they have.

Federal personnel engaged in science and technology and its components, by type of science, personnel category, for provinces and territories from 2000 to today.

Initial Claims for UI released by the CT Department of Labor. Initial Claims are applications for Unemployment Benefits. Initial Claims may not result in receiving UI benefits if the individual doesn't qualify.

The initial claims reported in these tables are "processed" claims to the extent that duplicates and "reopened" claims have been eliminated. The claim counts in this dataset may not match claim counts from other sources.

Unemployment claims tabulated in this dataset represent only one component of the unemployed. Claims do not account for those not covered under the Unemployment system (e.g. federal workers, railroad workers or religious workers) or the unemployed self-employed.

Claims filed for a particular week will change as time goes on and the backlog is addressed.

This data set contains information about any US government agency participating in the transit benefits program, funding agreements, individual participating Federal employees and details about commutes, supervisors and supervisory approvals, fare media in use, and transaction histories.

Federal Funding Gaps in the US

Overview of US Federal Funding Gaps (1976-2018)

By Throwback Thursday [source]

About this dataset

The dataset includes columns such as Start Date, End Date, Total days, Employees furloughed, Number of Employees Furloughed, Senate Control, Senate Democrats, Senate Republicans ,Senate Independents ,House Control ,House Democrats ,House Republicans and House Independents.

Start Date indicates the date when each federal funding gap began. On the other hand End date shows when these funding gaps came to an end. By examining this information for each gap individually along with calculations from other columns like Total days one can gain insights into how long each funding gap lasted.

Numerical values such as number of employees affected by furloughs are provided within columns like Employees furloughed and Number of Employees Furloughed. The latter column represents a total count for all affected employees throughout a particular funding gap period.

This dataset delves even deeper into political dynamics by revealing which political party was in control during each federal funding gap period through columns like Senate Control and House Control. Specifically defining whether Democrats or Republicans were leading is very crucial to understand any potential ramifications associated with those particular party affiliations being at power during a given time period.

Moreover,the numerical data found under columns named Senate Democrats,Senate Republicans,Senate Independents indicate how many members from respective parties were active participants within United States Senate for each individual government fund shutdown event.As we continue through other sections more details about representation will be present .

Similarly,namesake parties committed to House representatives then find representation factors being unearthed and can be seen through President's Government House Control metric here . Columns like House Democrats, House Republicans and House Independents serve as additional measures to provide a census of who controlled the power dynamic during these respective campaign titanic struggles.Thus , for each federal funding gap period one can ascertain which political party held sway over the decisions made within America's lower parliamentary body.

In total,this comprehensive dataset offers profound insights into how the United States government experienced financial funding gaps throughout several decades of its history. The information provided in this dataset is crucial for anyone looking to study, analyze, or understand the dynamics, duration, impacts, and control factors associated

How to use the dataset

• Understand the Columns:

  • Start Date: The date when a federal funding gap started.
  • End Date: The date when a federal funding gap ended.
  • Total days: The duration of each federal funding gap in days.
  • Employees furloughed: A brief description of the employees affected by each funding gap, providing an insight into different government sectors impacted.
  • Number of Employees Furloughed: The total number of employees who were furloughed during each funding gap.
  • Senate Control and House Control: Political party in control of both chambers during each funding gap (Democrats or Republicans).

• Gain Insight into Duration and Employee Impact: Explore which federal funding gaps had longer durations and higher numbers of furloughed employees. Sort or filter based on Total days or Number of Employees Furloughed columns, respectively, to identify significant instances.

• Analyze Political Party Control: Observe which political party was in control during different periods. Analyze if there is any correlation between party control and decision-making leading to a governmental shutdown.

• Compare Senate and House Representation: Compare Republican, Democrat, Independent representation within both chambers during each period using respective columns like Senate Republicans, House Democrats, etc., providing insights into potential political dynamics affecting these gaps.

• Highlight Interesting Findings: Communicate your data-driven discoveries by visualizing interesting trends with graphs or summarizing them through storytelling techniques.

• Respect Data Privacy Please note that while analyzing the dataset, it is essential to respect any data privacy guidelines and not draw conclusions about individual employees or reveal any sensitive information.

Best of luck with your analysis!

Research Ideas

• Analyzing the impact of federal funding gaps: This datas...

Under the Public Service Compensation Disclosure Policy, compensation, including salary, benefit, and severance amounts for government employees with base salaries or severance payments of equal to or greater than the identified annual threshold, are available in the linked dataset.

Info Source: Sources of Government and Employee Information provides information about the functions, programs, activities and related information holdings of government institutions subject to the Access to Information Act and the Privacy Act. It provides individuals and employees of the government (current and former) with relevant information to access personal information about themselves held by government institutions subject to the Privacy Act and to exercise their rights under the Privacy Act. The Introduction to Info Source: Sources of Government and Employee Information and an index of institutions subject to the Access to Information Act and the Privacy Act are available centrally. The Access to Information Act and the Privacy Act assign overall responsibility to the President of Treasury Board (as the designated Minister) for the government-wide administration of the legislation.