70 datasets found
  1. F

    Labor Force Participation Rate - 20 Yrs. & over, White Men

    • fred.stlouisfed.org
    json
    Updated Jul 3, 2025
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    (2025). Labor Force Participation Rate - 20 Yrs. & over, White Men [Dataset]. https://fred.stlouisfed.org/series/LNS11300028
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 3, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Labor Force Participation Rate - 20 Yrs. & over, White Men (LNS11300028) from Jan 1954 to Jun 2025 about 20 years +, males, participation, white, labor force, labor, household survey, rate, and USA.

  2. F

    Civilian Labor Force Level - 20 Yrs. & over, White Men

    • fred.stlouisfed.org
    json
    Updated Jul 3, 2025
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    (2025). Civilian Labor Force Level - 20 Yrs. & over, White Men [Dataset]. https://fred.stlouisfed.org/series/LNU01000028
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 3, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Civilian Labor Force Level - 20 Yrs. & over, White Men (LNU01000028) from Jan 1954 to Jun 2025 about 20 years +, males, civilian, white, labor force, labor, household survey, and USA.

  3. T

    United States - Labor Force Participation Rate - 20 Yrs. & over, White Men

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 11, 2018
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    TRADING ECONOMICS (2018). United States - Labor Force Participation Rate - 20 Yrs. & over, White Men [Dataset]. https://tradingeconomics.com/united-states/civilian-labor-force-participation-rate-20-years-and-over-white-men-percent-fed-data.html
    Explore at:
    xml, excel, csv, jsonAvailable download formats
    Dataset updated
    Mar 11, 2018
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    United States - Labor Force Participation Rate - 20 Yrs. & over, White Men was 69.70% in April of 2025, according to the United States Federal Reserve. Historically, United States - Labor Force Participation Rate - 20 Yrs. & over, White Men reached a record high of 88.40 in August of 1954 and a record low of 69.00 in April of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Labor Force Participation Rate - 20 Yrs. & over, White Men - last updated from the United States Federal Reserve on July of 2025.

  4. T

    United States - Civilian Labor Force Level - 20 Yrs. & over, White Men

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 8, 2020
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    TRADING ECONOMICS (2020). United States - Civilian Labor Force Level - 20 Yrs. & over, White Men [Dataset]. https://tradingeconomics.com/united-states/civilian-labor-force-level-20-years-and-over-white-men-thous-of-persons-fed-data.html
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset updated
    Mar 8, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    United States - Civilian Labor Force Level - 20 Yrs. & over, White Men was 66593.00000 Thous. of Persons in May of 2025, according to the United States Federal Reserve. Historically, United States - Civilian Labor Force Level - 20 Yrs. & over, White Men reached a record high of 66794.00000 in January of 2025 and a record low of 37657.00000 in July of 1954. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Civilian Labor Force Level - 20 Yrs. & over, White Men - last updated from the United States Federal Reserve on July of 2025.

  5. N

    White Hall, AR annual income distribution by work experience and gender...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
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    Neilsberg Research (2025). White Hall, AR annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/baced76c-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Arkansas, White Hall
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within White Hall. The dataset can be utilized to gain insights into gender-based income distribution within the White Hall population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within White Hall, among individuals aged 15 years and older with income, there were 1,782 men and 1,763 women in the workforce. Among them, 804 men were engaged in full-time, year-round employment, while 995 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 9.95% fell within the income range of under $24,999, while 9.75% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 23.38% of men in full-time roles earned incomes exceeding $100,000, while 12.66% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    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.

    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 White Hall median household income by race. You can refer the same here

  6. F

    Labor Force Participation Rate - Men

    • fred.stlouisfed.org
    json
    Updated Jul 3, 2025
    + more versions
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    (2025). Labor Force Participation Rate - Men [Dataset]. https://fred.stlouisfed.org/series/LNS11300001
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 3, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Labor Force Participation Rate - Men (LNS11300001) from Jan 1948 to Jun 2025 about males, participation, 16 years +, labor force, labor, household survey, rate, and USA.

  7. E

    Diversity in Tech Statistics 2024 – By Countries, Companies And Demographic...

    • enterpriseappstoday.com
    Updated Mar 1, 2024
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    EnterpriseAppsToday (2024). Diversity in Tech Statistics 2024 – By Countries, Companies And Demographic (Age, Gender, Race, Education) [Dataset]. https://www.enterpriseappstoday.com/stats/diversity-in-tech-statistics.html
    Explore at:
    Dataset updated
    Mar 1, 2024
    Dataset authored and provided by
    EnterpriseAppsToday
    License

    https://www.enterpriseappstoday.com/privacy-policyhttps://www.enterpriseappstoday.com/privacy-policy

    Time period covered
    2022 - 2032
    Area covered
    Global
    Description

    Diversity in Tech Statistics: In today's tech-driven world, discussions about diversity in the technology sector have gained significant traction. Recent statistics shed light on the disparities and opportunities within this industry. According to data from various sources, including reports from leading tech companies and diversity advocacy groups, the lack of diversity remains a prominent issue. For example, studies reveal that only 25% of computing jobs in the United States are held by women, while Black and Hispanic individuals make up just 9% of the tech workforce combined. Additionally, research indicates that LGBTQ+ individuals are underrepresented in tech, with only 2.3% of tech workers identifying as LGBTQ+. Despite these challenges, there are promising signs of progress. Companies are increasingly recognizing the importance of diversity and inclusion initiatives, with some allocating significant resources to address these issues. For instance, tech giants like Google and Microsoft have committed millions of USD to diversity programs aimed at recruiting and retaining underrepresented talent. As discussions surrounding diversity in tech continue to evolve, understanding the statistical landscape is crucial in fostering meaningful change and creating a more inclusive industry for all. Editor’s Choice In 2021, 7.9% of the US labor force was employed in technology. Women hold only 26.7% of tech employment, while men hold 73.3% of these positions. White Americans hold 62.5% of the positions in the US tech sector. Asian Americans account for 20% of jobs, Latinx Americans 8%, and Black Americans 7%. 83.3% of tech executives in the US are white. Black Americans comprised 14% of the population in 2019 but held only 7% of tech employment. For the same position, at the same business, and with the same experience, women in tech are typically paid 3% less than men. The high-tech sector employs more men (64% against 52%), Asian Americans (14% compared to 5.8%), and white people (68.5% versus 63.5%) compared to other industries. The tech industry is urged to prioritize inclusion when hiring, mentoring, and retaining employees to bridge the digital skills gap. Black professionals only account for 4% of all tech workers despite being 13% of the US workforce. Hispanic professionals hold just 8% of all STEM jobs despite being 17% of the national workforce. Only 22% of workers in tech are ethnic minorities. Gender diversity in tech is low, with just 26% of jobs in computer-related sectors occupied by women. Companies with diverse teams have higher profitability, with those in the top quartile for gender diversity being 25% more likely to have above-average profitability. Every month, the tech industry adds about 9,600 jobs to the U.S. economy. Between May 2009 and May 2015, over 800,000 net STEM jobs were added to the U.S. economy. STEM jobs are expected to grow by another 8.9% between 2015 and 2024. The percentage of black and Hispanic employees at major tech companies is very low, making up just one to three percent of the tech workforce. Tech hiring relies heavily on poaching and incentives, creating an unsustainable ecosystem ripe for disruption. Recruiters have a significant role in disrupting the hiring process to support diversity and inclusion. You May Also Like To Read Outsourcing Statistics Digital Transformation Statistics Internet of Things Statistics Computer Vision Statistics

  8. Diversity among cybersecurity teams in selected countries 2023, by race and...

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Diversity among cybersecurity teams in selected countries 2023, by race and gender [Dataset]. https://www.statista.com/statistics/1423591/diversity-among-cybersecurity-staff-in-selected-countries/
    Explore at:
    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2023 - May 2023
    Area covered
    Canada, United Kingdom, United States
    Description

    According to a 2023 study, around ** percent of cybersecurity professionals aged 60 or older in the United States, Canada, the United Kingdom, and Ireland were white men. The proportion of non-white men in this age group reached ** percent, while the share of white and non-white women aged 60 or older was around ** and two percent, respectively. On the other hand, non-white men constituted ** percent of the cybersecurity workforce under **, and the share of non-white women in this age group reached ** percent.

  9. Proportion of women and men employed in occupations, annual, inactive

    • www150.statcan.gc.ca
    Updated Jan 6, 2023
    + more versions
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    Government of Canada, Statistics Canada (2023). Proportion of women and men employed in occupations, annual, inactive [Dataset]. http://doi.org/10.25318/1410033501-eng
    Explore at:
    Dataset updated
    Jan 6, 2023
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Proportion of women and men employed in the National Occupational Classification (NOC) broad occupational categories, current year.

  10. N

    Fort White, FL annual income distribution by work experience and gender...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Fort White, FL annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/baa63937-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Fort White, Florida
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Fort White. The dataset can be utilized to gain insights into gender-based income distribution within the Fort White population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Fort White, among individuals aged 15 years and older with income, there were 209 men and 222 women in the workforce. Among them, 113 men were engaged in full-time, year-round employment, while 114 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 7.96% fell within the income range of under $24,999, while none of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 6.19% of men in full-time roles earned incomes exceeding $100,000, while 1.75% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    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.

    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 Fort White median household income by race. You can refer the same here

  11. s

    Data from: Employment by occupation

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Jul 27, 2022
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    Race Disparity Unit (2022). Employment by occupation [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/work-pay-and-benefits/employment/employment-by-occupation/latest
    Explore at:
    csv(309 KB)Available download formats
    Dataset updated
    Jul 27, 2022
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    39.8% of workers from the Indian ethnic group were in 'professional' jobs in 2021 – the highest percentage out of all ethnic groups in this role.

  12. Number of employees worldwide 1991-2025

    • statista.com
    • ai-chatbox.pro
    Updated May 30, 2025
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    Statista (2025). Number of employees worldwide 1991-2025 [Dataset]. https://www.statista.com/statistics/1258612/global-employment-figures/
    Explore at:
    Dataset updated
    May 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

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

  13. Austria Employment: Male: Employees: White Collar Workers

    • ceicdata.com
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    CEICdata.com, Austria Employment: Male: Employees: White Collar Workers [Dataset]. https://www.ceicdata.com/en/austria/labour-force-survey-new-questionnaire-employment/employment-male-employees-white-collar-workers
    Explore at:
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2021 - Dec 1, 2021
    Area covered
    Austria
    Description

    Austria Employment: Male: Employees: White Collar Workers data was reported at 1,022.482 Person th in Dec 2021. This records an increase from the previous number of 1,022.278 Person th for Sep 2021. Austria Employment: Male: Employees: White Collar Workers data is updated quarterly, averaging 1,016.840 Person th from Mar 2021 (Median) to Dec 2021, with 4 observations. The data reached an all-time high of 1,022.482 Person th in Dec 2021 and a record low of 998.223 Person th in Jun 2021. Austria Employment: Male: Employees: White Collar Workers data remains active status in CEIC and is reported by Statistics Austria. The data is categorized under Global Database’s Austria – Table AT.G010: Labour Force Survey: New Questionnaire: Employment.

  14. t

    Data from: Participation Rates

    • townfolio.co
    + more versions
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    Participation Rates [Dataset]. https://townfolio.co/bc/white-rock/labour-force
    Explore at:
    Description

    Overall, the participation rate in White Rock, BC is declining at a rate of 0.31% per year over the past 15 years from 2001 to 2016. In the last two census, its participation rates declined by 5.5%, an average growth rate of -1.1% per year from 2011 to 2016. A decrease in participation rate means the proportion of the working population in White Rock, BC is lower than in the past.

  15. N

    White Earth Township, Minnesota annual median income by work experience and...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). White Earth Township, Minnesota annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/a5403e5e-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Minnesota, White Earth Township
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    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 White Earth township. 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 White Earth township, the median income for all workers aged 15 years and older, regardless of work hours, was $36,250 for males and $25,250 for females.

    These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 30% between the median incomes of males and females in White Earth township. With women, regardless of work hours, earning 70 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetownship of White Earth township.

    - Full-time workers, aged 15 years and older: In White Earth township, among full-time, year-round workers aged 15 years and older, males earned a median income of $47,500, while females earned $50,417

    Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.06 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

    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 White Earth township median household income by race. You can refer the same here

  16. N

    White Pine County, NV annual income distribution by work experience and...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). White Pine County, NV annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/bacee005-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    White Pine County, Nevada
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within White Pine County. The dataset can be utilized to gain insights into gender-based income distribution within the White Pine County population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within White Pine County, among individuals aged 15 years and older with income, there were 2,969 men and 2,932 women in the workforce. Among them, 1,534 men were engaged in full-time, year-round employment, while 1,289 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 9.52% fell within the income range of under $24,999, while 10.86% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 15.71% of men in full-time roles earned incomes exceeding $100,000, while 12.26% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    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.

    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 White Pine County median household income by race. You can refer the same here

  17. Average cybersecurity salary in the U.S. 2023, by ethnicity and gender

    • statista.com
    Updated May 10, 2024
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    Statista (2024). Average cybersecurity salary in the U.S. 2023, by ethnicity and gender [Dataset]. https://www.statista.com/statistics/1465480/us-average-cybersecurity-salary-by-ethnicity-and-gender/
    Explore at:
    Dataset updated
    May 10, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2023 - May 2023
    Area covered
    United States
    Description

    According to a 2023 study, the average cybersecurity salary of white men in the United States was around 150 thousand U.S. dollars, approximately five thousand U.S. dollars more than the salary of men of color, and 13 thousand U.S. dollars more than the salary of women of color.

  18. s

    Civil Service workforce

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Oct 11, 2024
    Share
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    Race Disparity Unit (2024). Civil Service workforce [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/workforce-and-business/workforce-diversity/civil-service-workforce/latest
    Explore at:
    csv(13 MB)Available download formats
    Dataset updated
    Oct 11, 2024
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    UK and overseas
    Description

    White people made up 83.4% of civil servants in March 2024 – they made up 80.7% of the working age population (16 to 64 year olds) in the 2021 Census.

  19. F

    Labor Force Participation Rate - 20 Yrs. & over, Black or African American...

    • fred.stlouisfed.org
    json
    Updated Jul 3, 2025
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    (2025). Labor Force Participation Rate - 20 Yrs. & over, Black or African American Men [Dataset]. https://fred.stlouisfed.org/series/LNS11300031
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 3, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Labor Force Participation Rate - 20 Yrs. & over, Black or African American Men (LNS11300031) from Jan 1972 to Jun 2025 about 20 years +, males, participation, African-American, labor force, labor, household survey, rate, and USA.

  20. Global energy sector workforce breakdown by gender and ethnicity 2022

    • statista.com
    Updated Apr 29, 2024
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    Statista (2024). Global energy sector workforce breakdown by gender and ethnicity 2022 [Dataset]. https://www.statista.com/statistics/1311080/worldwide-energy-sector-workforce-by-gender-and-ethnicity/
    Explore at:
    Dataset updated
    Apr 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Worldwide
    Description

    Employment in the worldwide energy sector is unevenly distributed across gender and ethnic groups. In 2022, about two thirds of energy sector jobs were held by men. Broken down by ethnicity, energy sector employment was even more unevenly distributed, with 78 percent of the sector's jobs held by white employees.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
(2025). Labor Force Participation Rate - 20 Yrs. & over, White Men [Dataset]. https://fred.stlouisfed.org/series/LNS11300028

Labor Force Participation Rate - 20 Yrs. & over, White Men

LNS11300028

Explore at:
jsonAvailable download formats
Dataset updated
Jul 3, 2025
License

https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

Description

Graph and download economic data for Labor Force Participation Rate - 20 Yrs. & over, White Men (LNS11300028) from Jan 1954 to Jun 2025 about 20 years +, males, participation, white, labor force, labor, household survey, rate, and USA.

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