The Office of Personnel Management requires government agencies, at a minimum, to query employees on job satisfaction, organizational assessment and organizational culture. VHA maintains response data for all census surveys such as the Voice of VA as well as the VA Entrance and Exit surveys.

The 2018 APS employee census was administered to all available Australian Public Service (APS) employees. This census approach provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The census' content is designed to establish the views of APS employees on workplace issues such as leadership, learning and development, and job satisfaction. The census ran from 7 May to 8 June 2018. Overall, 103,137 APS employees responded to the employee census, a response rate of 74%.

Please be aware that the very large number of respondents to the employee census means these files are over 200 mb in size. Downloading and opening these files may take some time.

TECHNICAL NOTES

Three files are available for download.

• 2018 APS employee census - Questionnaire: This contains the 2018 APS employee census questionnaire.

• 2018 APS employee census - 5 point dataset.csv: This file contains individual responses to the 2018 APS employee census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document.

• 2018 APS employee census - 5 point dataset.sav: This file contains individual responses to the 2018 APS employee census for use with the SPSS software package.

To protect the privacy and confidentiality of respondents to the 2018 APS employee census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions.

Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author.

A recommended short citation is: 2018 APS employee census data, Australian Public Service Commission.

Any queries can be directed to research@apsc.gov.au.

The 2021 APS Employee Census was administered to all available Australian Public Service (APS) employees, running from 10 May to 11 June 2021.

The Employee Census provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The Census' content is designed to establish the views of APS employees on workplace issues such as leadership, learning and development, and job satisfaction.

Overall, 109,537 APS employees responded to the Employee Census in 2021, a response rate of 77%.

Please be aware that the very large number of respondents to the employee census means these files are over 200MB in size. Downloading and opening these files may take some time.

TECHNICAL NOTES

Three files are available for download.

• 2021 APS Employee Census - Questionnaire: This contains the 2021 APS Employee Census questionnaire.
• 2021 APS Employee Census - 5 point dataset.csv: This file contains individual responses to the 2021 APS Employee Census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document.
• 2021 APS Employee Census - 5 point dataset.sav: This file contains individual responses to the 2021 APS Employee Census for use with the SPSS software package.

To protect the privacy and confidentiality of respondents to the 2021 APS Employee Census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions.

Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author.

A recommended short citation is: 2021 APS Employee Census data, Australian Public Service Commission.

Any queries can be directed to research@apsc.gov.au.

The 2020 APS Employee Census was administered to all available Australian Public Service (APS) employees, running from 12 October to 13 November 2020. This was delayed from the usual May to June timeframe due to the impact of COVID-19.

The Employee Census provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The Census' content is designed to establish the views of APS employees on workplace issues such as leadership, learning and development, and job satisfaction.

Overall, 108,085 APS employees responded to the Employee Census in 2020, a response rate of 78%.

Please be aware that the very large number of respondents to the employee census means these files are over 200MB in size. Downloading and opening these files may take some time.

TECHNICAL NOTES

Three files are available for download.

• 2020 APS Employee Census - Questionnaire: This contains the 2020 APS Employee Census questionnaire.

• 2020 APS Employee Census - 5 point dataset.csv: This file contains individual responses to the 2020 APS Employee Census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document.

• 2020 APS Employee Census - 5 point dataset.sav: This file contains individual responses to the 2020 APS Employee Census for use with the SPSS software package.

To protect the privacy and confidentiality of respondents to the 2020 APS Employee Census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions.

Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author. A recommended short citation is: 2020 APS Employee Census data, Australian Public Service Commission.

Any queries can be directed to research@apsc.gov.au.

Summary

The 2024 APS Employee Census was administered to eligible Australian Public Service (APS) employees between 6 May and 7 June 2024. Overall, 140,396 APS employees responded to the APS Employee Census in 2024, a response rate of 81%.

The APS Employee Census is an annual employee perception survey of the Australian Public Service workforce. The APS Employee Census has been conducted since 2012 and collects APS employee opinions and perspectives on a range of topics, including employee engagement, wellbeing, and leadership.

The APS Employee Census provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error.

Please be aware that the very large number of respondents to the APS Employee Census means these files are over 200MB in size.

Downloading and opening these files may take some time.

Technical notes

Three files are available for download.

• 2024 APS Employee Census - Questionnaire: This contains the 2024 APS Employee Census questionnaire.

• 2024 APS Employee Census - 5 point dataset with data values: This CSV file contains individual responses to the 2024 APS Employee Census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document. Data in this file are presented as data values.

• 2024 APS Employee Census - 5 point dataset with data labels: This CSV file contains individual responses to the 2024 APS Employee Census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document. Data in this file are presented as data labels.

• 2024 APS Employee Census - 5 point dataset.sav: This file contains individual responses to the 2024 APS Employee Census for use with the SPSS software package.

• 2024 APS Employee Census - data dictionary: This file contains a list of variables and labels within the APS Employee Census.

To protect the privacy and confidentiality of respondents to the 2024 APS Employee Census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions.

Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author.

A recommended short citation is: 2024 APS Employee Census, Australian Public Service Commission.

Any queries can be directed to research@apsc.gov.au.

The 2013 APS employee census was administered to all available Australian Public Service (APS) employees. This census approach provides a comprehensive view of the APS and ensures no eligible …Show full descriptionThe 2013 APS employee census was administered to all available Australian Public Service (APS) employees. This census approach provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The census ran from 15 May to 14 June 2013. Overall, 102,219 employees responded to the employee census, a response rate of 66%. Please be aware that the very large number of respondents to the employee census means these files are up to 200 mb in size. Downloading and opening these files may take some time. TECHNICAL NOTES Three files are available for download. 2013 APS employee census - Questionnaire: This contains the 2013 APS employee census questionnaire. 2013 APS employee census - 5 point dataset.csv: This file contains individual responses to the 2013 employee census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document. 2013 APS employee census - 5 point dataset.sav: This file contains individual responses to the 2013 employee census for use with the SPSS software package. To protect the privacy and confidentiality of respondents to the 2013 APS employee census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions. Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author. A recommended short citation is: 2013 APS employee census data, Australian Public Service Commission. Any queries can be directed to research@apsc.gov.au.

The 2016 Australian Public Service (APS) employee census was administered to all available APS employees. This census approach provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The census' content is designed to establish the views of APS employees on workplace issues such as leadership, learning and development and job satisfaction. The census ran from 9 May to 10 June 2016. Overall, 96,672 APS employees responded to the employee census, a response rate of 69%.

Please be aware that the very large number of respondents to the employee census means these files are over 200 mb in size. Downloading and opening these files may take some time.

TECHNICAL NOTES

Three files are available for download.

• 2016 APS employee census - Questionnaire: This contains the 2016 APS employee census questionnaire.

• 2016 APS employee census - 5 point dataset.csv: This file contains individual responses to the 2016 APS employee census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document.

• 2016 APS employee census - 5 point dataset.sav: This file contains individual responses to the 2016 APS employee census for use with the SPSS software package.

To protect the privacy and confidentiality of respondents to the 2016 APS employee census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions.

Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author.

A recommended short citation is: 2016 APS employee census data, Australian Public Service Commission.

Any queries can be directed to research@apsc.gov.au.

The 2022 APS Employee Census was administered to all available Australian Public Service (APS) employees, running from 9 May to 10 June 2022. The Employee Census provides a comprehensive view of the …Show full descriptionThe 2022 APS Employee Census was administered to all available Australian Public Service (APS) employees, running from 9 May to 10 June 2022. The Employee Census provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The Census' content is designed to establish the views of APS employees on workplace issues such as leadership, employee wellbeing, and job satisfaction. Overall, 120,662 APS employees responded to the Employee Census in 2022, a response rate of 83%. Please be aware that the very large number of respondents to the employee census means these files are over 200MB in size. Downloading and opening these files may take some time. TECHNICAL NOTES Three files are available for download. 2022 APS Employee Census - Questionnaire: This contains the 2022 APS Employee Census questionnaire. 2022 APS Employee Census - 5 point dataset.csv: This file contains individual responses to the 2022 APS Employee Census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document. 2022 APS Employee Census - 5 point dataset.sav: This file contains individual responses to the 2022 APS Employee Census for use with the SPSS software package. To protect the privacy and confidentiality of respondents to the 2022 APS Employee Census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions. Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author. A recommended short citation is: 2022 APS Employee Census data, Australian Public Service Commission. Any queries can be directed to research@apsc.gov.au.

The Quarterly Census of Employment and Wages (QCEW) program serves as a near census of employment and wage information. 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. Data on the number of establishments, employment, and wages are reported by industry for Connecticut and for the counties, towns and Labor Market Areas (LMAs) and Workforce Investment Areas (WIAs).

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.

Summary The 2024 APS Employee Census was administered to eligible Australian Public Service (APS) employees between 6 May and 7 June 2024. Overall, 140,396 APS employees responded to the APS …Show full description##Summary The 2024 APS Employee Census was administered to eligible Australian Public Service (APS) employees between 6 May and 7 June 2024. Overall, 140,396 APS employees responded to the APS Employee Census in 2024, a response rate of 81%. The APS Employee Census is an annual employee perception survey of the Australian Public Service workforce. The APS Employee Census has been conducted since 2012 and collects APS employee opinions and perspectives on a range of topics, including employee engagement, wellbeing, and leadership. The APS Employee Census provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. Please be aware that the very large number of respondents to the APS Employee Census means these files are over 200MB in size. Downloading and opening these files may take some time. ##Technical notes Three files are available for download. • 2024 APS Employee Census - Questionnaire: This contains the 2024 APS Employee Census questionnaire. • 2024 APS Employee Census - 5 point dataset with data values: This CSV file contains individual responses to the 2024 APS Employee Census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document. Data in this file are presented as data values. • 2024 APS Employee Census - 5 point dataset with data labels: This CSV file contains individual responses to the 2024 APS Employee Census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document. Data in this file are presented as data labels. • 2024 APS Employee Census - 5 point dataset.sav: This file contains individual responses to the 2024 APS Employee Census for use with the SPSS software package. • 2024 APS Employee Census - data dictionary: This file contains a list of variables and labels within the APS Employee Census. To protect the privacy and confidentiality of respondents to the 2024 APS Employee Census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions. Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author. A recommended short citation is: 2024 APS Employee Census, Australian Public Service Commission. Any queries can be directed to research@apsc.gov.au.

The Quarterly Census of Employment and Wages (QCEW) program publishes a quarterly count of employment and wages reported by employers covering 98 percent of U.S. jobs, available at the county, MSA, state and national levels by industry. More information and details about the data provided can be found at http://www.bls.gov/cew

GCCSA based data for Industry of Employment by Owner Managers By Number of Employees, in Working Population Profile (WPP), 2016 Census. Count of owner managers of enterprises. Records the number of employees (in ranges) employed by owner managers (excluding the owner managers themselves). W10 is broken up into 2 sections (W10a - W10b), this section contains 'Unincorporated enterprises Inadequately described Not stated Owner managers of enterprises with Nil employees' - 'Unincorporated enterprises Total Total'. The data is by GCCSA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

Employment Rate and Labor Force Participation. From ACS Table B23025. 5yr ACS 2007-11, By Tract, State of Michigan. Table joined to 2010 TiGER census tracts.

These data contain selected census tract level demographic indicators (estimates) from the 2015-2019 American Community Survey representing the percent of the civilian labor force population (Age 16+) that is unemployed.

GCCSA based data for Occupation of Owner Managers by Number of Employees, in Working Population Profile (WPP), 2016 Census. Count of owner managers of enterprises. The data is by GCCSA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

VITAL SIGNS INDICATOR Commute Time (T4)

FULL MEASURE NAME Commute time by employment location

LAST UPDATED April 2020

DESCRIPTION Commute time refers to the average number of minutes a commuter spends traveling to work on a typical day. The dataset includes metropolitan area, county, city, and census tract tables by place of residence.

DATA SOURCE U.S. Census Bureau: Decennial Census (1980-2000) - via MTC/ABAG Bay Area Census http://www.bayareacensus.ca.gov/transportation.htm

U.S. Census Bureau: American Community Survey Table B08536 (2018 only; by place of employment) Table B08601 (2018 only; by place of employment) www.api.census.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) For the decennial Census datasets, breakdown of commute times was unavailable by mode; only overall data could be provided on a historical basis.

For the American Community Survey datasets, 1-year rolling average data was used for all metros, region, and county geographic levels, while 5-year rolling average data was used for cities and tracts. This is due to the fact that more localized data is not included in the 1-year dataset across all Bay Area cities. Similarly, modal data is not available for every Bay Area city or census tract, even when the 5-year data is used for those localized geographies.

Regional commute times were calculated by summing aggregate county travel times and dividing by the relevant population; similarly, modal commute time were calculated using aggregate times and dividing by the number of communities choosing that mode for the given geography. Census tract data is not available for tracts with insufficient numbers of residents.

The metropolitan area comparison was performed for the nine-county San Francisco Bay Area in addition to the primary MSAs for the nine other major metropolitan areas.

LGA based data for Industry of Employment by Owner Managers By Number of Employees, in Working Population Profile (WPP), 2016 Census. Count of owner managers of enterprises. Records the number of employees (in ranges) employed by owner managers (excluding the owner managers themselves). W10 is broken up into 2 sections (W10a - W10b), this section contains 'Unincorporated enterprises Inadequately described Not stated Owner managers of enterprises with Nil employees' - 'Unincorporated enterprises Total Total'. The data is by LGA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Scandia. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Scandia, the median income for all workers aged 15 years and older, regardless of work hours, was $63,068 for males and $39,972 for females.

These income figures highlight a substantial gender-based income gap in Scandia. Women, regardless of work hours, earn 63 cents for each dollar earned by men. This significant gender pay gap, approximately 37%, underscores concerning gender-based income inequality in the city of Scandia.

- Full-time workers, aged 15 years and older: In Scandia, among full-time, year-round workers aged 15 years and older, males earned a median income of $90,750, while females earned $52,500, leading to a 42% gender pay gap among full-time workers. This illustrates that women earn 58 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Scandia, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Scandia median household income by race. You can refer the same here

Canadian Business Counts, location counts with employees, by employment size ranges and North American Industry Classification System (NAICS), census metropolitan areas and census subdivisions, December 2024.