94 datasets found
  1. Occupational Employment and Wage Statistics (OES)

    • catalog.data.gov
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    Updated May 16, 2022
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    Bureau of Labor Statistics (2022). Occupational Employment and Wage Statistics (OES) [Dataset]. https://catalog.data.gov/dataset/occupational-employment-and-wage-statistics-oes
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    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Description

    The Occupational Employment and Wage Statistics (OES) program conducts a semi-annual survey to produce estimates of employment and wages for specific occupations. The OES program collects data on wage and salary workers in nonfarm establishments in order to produce employment and wage estimates for about 800 occupations. Data from self-employed persons are not collected and are not included in the estimates. The OES program produces these occupational estimates by geographic area and by industry. Estimates based on geographic areas are available at the National, State, Metropolitan, and Nonmetropolitan Area levels. The Bureau of Labor Statistics produces occupational employment and wage estimates for over 450 industry classifications at the national level. The industry classifications correspond to the sector, 3-, 4-, and 5-digit North American Industry Classification System (NAICS) industrial groups. More information and details about the data provided can be found at http://www.bls.gov/oes

  2. u

    Labour force survey estimates (LFS), by National Occupational Classification...

    • data.urbandatacentre.ca
    • beta.data.urbandatacentre.ca
    • +3more
    Updated Oct 1, 2024
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    (2024). Labour force survey estimates (LFS), by National Occupational Classification for Statistics (NOC-S) and sex, annual [Dataset]. https://data.urbandatacentre.ca/dataset/gov-canada-9230a0fa-eb15-42c0-b30f-455413252037
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    Dataset updated
    Oct 1, 2024
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    Number of persons in the labour force (employment and unemployment) and not in the labour force, unemployment rate, participation rate, and employment rate, by National Occupational Classification for Statistics (NOC-S) and sex, last 5 years.

  3. g

    Archival Version

    • datasearch.gesis.org
    Updated Aug 5, 2015
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    National Academy of Sciences. Committee on Occupational Classification and Analysis (2015). Archival Version [Dataset]. http://doi.org/10.3886/ICPSR07845
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    Dataset updated
    Aug 5, 2015
    Dataset provided by
    da|ra (Registration agency for social science and economic data)
    Authors
    National Academy of Sciences. Committee on Occupational Classification and Analysis
    Description

    This data collection contains two separate data files, both of which are the results of the systematic evaluation of job worth performed by the Committee on Occupational Classification and Analysis of the National Academy of Sciences. The Committee acquired a selection of variables from the April 1971 Current Population Survey (CPS) that were gathered from a sample of households which yielded 60,441 workers in the experienced civilian labor force. The CPS survey provided detailed information about the workers and their family backgrounds, education, and employment. Part 1 contains that data augmented with Dictionary of Occupational Titles (DOT) characteristics, e.g., job classification and description, for each worker in the survey. Part 2 of this data collection is a file created by the Committee containing aggregate DOT characteristics (based on the DOT, Fourth Edition) for the 574 expanded occupation categories of the 1970 United States Census. The motivation for aggregating DOT characteristics (which exist as scores for each of 12,099 occupations) into 1970 United States Census codes was to allow researchers to relate the characteristics of occupations from the DOT to the characteristics of the individuals in those occupations gathered from the Census and survey data. The file's data -- the aggregated scores for all the workers in each of the 574 occupational categories -- are based on a variety of criteria, e.g., Specific Vocational Preparation (SVP), aptitudes, interest factors, preferences, physical demands, environmental conditions, and General Educational Development (GED).

  4. H

    Crosswalk of OES Survey Occupations to Other Occupational Classification...

    • dataverse.harvard.edu
    pdf +1
    Updated Jan 28, 2013
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    Harvard Dataverse (2013). Crosswalk of OES Survey Occupations to Other Occupational Classification Systems, 1982 [Dataset]. http://doi.org/10.7910/DVN/TZ7FMR
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    pdf(408496), text/plain; charset=us-ascii(3411180)Available download formats
    Dataset updated
    Jan 28, 2013
    Dataset provided by
    Harvard Dataverse
    Area covered
    United States
    Description

    The 1982 crosswalk consists of all (and only those) Occupational Employment Statistics (OES) survey occupations used during the most recent surveys of all industries covered by the OES survey program. Those OES occupations not surveyed during the referenced cycle are not included on the crosswalk. However, all nine digit fourth edition Dictionary of Occupational Titles (DOT) codes are contained on the tape and have been assigned to either specific OES occupations, OES residual categories, or to an unassigned OES code because the DOT occupation is industry-specific and the industry is not within the scope of the OES survey.

  5. 2019 American Community Survey: S2406 | OCCUPATION BY CLASS OF WORKER FOR...

    • data.census.gov
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    ACS, 2019 American Community Survey: S2406 | OCCUPATION BY CLASS OF WORKER FOR THE CIVILIAN EMPLOYED POPULATION 16 YEARS AND OVER (ACS 5-Year Estimates Subject Tables) [Dataset]. https://data.census.gov/table/ACSST5Y2019.S2406
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2019
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2015-2019 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..Occupation titles and their 4-digit codes are based on the Standard Occupational Classification (SOC). The Census occupation codes for 2018 and later years are based on the 2018 revision of the SOC. To allow for the creation of the multiyear tables, occupation data in the multiyear files (prior to data year 2018) were recoded to the 2018 Census occupation codes. We recommend using caution when comparing data coded using 2018 Census occupation codes with data coded using Census occupation codes prior to data year 2018. For more information on the Census occupation code changes, please visit our website at https://www.census.gov/topics/employment /industry-occupation/guidance/code-lists.html..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed information about the 2019 changes, see the 2016 American Community Survey Content Test Report for Class of Worker located at http://www.census.gov/library/working-papers/2017/acs/2017_Martinez_01.html..The 2015-2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.An "***...

  6. 2021 American Community Survey: S2406 | OCCUPATION BY CLASS OF WORKER FOR...

    • data.census.gov
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    ACS, 2021 American Community Survey: S2406 | OCCUPATION BY CLASS OF WORKER FOR THE CIVILIAN EMPLOYED POPULATION 16 YEARS AND OVER (ACS 5-Year Estimates Subject Tables) [Dataset]. https://data.census.gov/table/ACSST5Y2021.S2406?g=860XX00US39759
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2021
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..Occupation titles and their 4-digit codes are based on the Standard Occupational Classification (SOC). The Census occupation codes for 2018 and later years are based on the 2018 revision of the SOC. To allow for the creation of the multiyear tables, occupation data in the multiyear files (prior to data year 2018) were recoded to the 2018 Census occupation codes. We recommend using caution when comparing data coded using 2018 Census occupation codes with data coded using Census occupation codes prior to data year 2018. For more information on the Census occupation code changes, please visit our website at https://www.census.gov/topics/employment /industry-occupation/guidance/code-lists.html..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed information about the 2019 changes, see the 2016 American Community Survey Content Test Report for Class of Worker located at http://www.census.gov/library/working-papers/2017/acs/2017_Martinez_01.html..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient ...

  7. 2018 American Community Survey: EEOALL1R | EEO 1R. DETAILED CENSUS...

    • data.census.gov
    Updated Nov 16, 2023
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    ACS (2023). 2018 American Community Survey: EEOALL1R | EEO 1R. DETAILED CENSUS OCCUPATION BY SEX AND RACE/ETHNICITY FOR RESIDENCE GEOGRAPHY (ACS 5-Year Estimates Equal Employment Opportunity) [Dataset]. https://data.census.gov/cedsci/table?q=eeo
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    Dataset updated
    Nov 16, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2018
    Description

    The EEO Tabulation is sponsored by four Federal agencies consisting of the Equal Employment Opportunity Commission (EEOC), the Employment Litigation Section of the Civil Rights Division at the Department of Justice (DOJ), the Office of Federal Contract Compliance Programs (OFCCP), and the Office of Personnel Management (OPM), and developed in conjunction with the U.S. Census Bureau..Supporting documentation on code lists and subject definitions can be found on the Equal Employment Opportunity Tabulation website. https://www.census.gov/topics/employment/equal-employment-opportunity-tabulation.html.Source: U.S. Census Bureau, 2014-2018 American Community Survey.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see https://www.census.gov/programs-surveys/acs/technical-documentation.html The effect of nonsampling error is not represented in these tables)..The U.S. Census Bureau collects race data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB). Except for the total, all race and ethnicity categories are mutually exclusive. "Black" refers to Black or African American; "AIAN" refers to American Indian and Alaska Native; and "NHPI" refers to Native Hawaiian and Other Pacific Islander. "Balance of Not Hispanic or Latino" includes the balance of non-Hispanic individuals who reported multiple races or reported Some Other Race alone. For more information on race and Hispanic origin, see the Subject Definitions at https://www.census.gov/programs-surveys/acs/technical-documentation.html..Race and Hispanic origin are separate concepts on the American Community Survey. "White alone Hispanic or Latino" includes respondents who reported Hispanic or Latino origin and reported race as "White" and no other race. "All other Hispanic or Latino" includes respondents who reported Hispanic or Latino origin and reported a race other than "White," either alone or in combination..Occupation titles and their 4-digit codes are based on the 2018 Standard Occupational Classification..The 2014-2018 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Explanation of Symbols:An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "(X)" means that the estimate is not applicable or not available.An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate.An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.

  8. 2020 American Community Survey: S2406 | OCCUPATION BY CLASS OF WORKER FOR...

    • data.census.gov
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    ACS, 2020 American Community Survey: S2406 | OCCUPATION BY CLASS OF WORKER FOR THE CIVILIAN EMPLOYED POPULATION 16 YEARS AND OVER (ACS 5-Year Estimates Subject Tables) [Dataset]. https://data.census.gov/table/ACSST5Y2020.S2406?g=160XX00US3714100
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2020
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..Occupation titles and their 4-digit codes are based on the Standard Occupational Classification (SOC). The Census occupation codes for 2018 and later years are based on the 2018 revision of the SOC. To allow for the creation of the multiyear tables, occupation data in the multiyear files (prior to data year 2018) were recoded to the 2018 Census occupation codes. We recommend using caution when comparing data coded using 2018 Census occupation codes with data coded using Census occupation codes prior to data year 2018. For more information on the Census occupation code changes, please visit our website at https://www.census.gov/topics/employment /industry-occupation/guidance/code-lists.html..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed information about the 2019 changes, see the 2016 American Community Survey Content Test Report for Class of Worker located at http://www.census.gov/library/working-papers/2017/acs/2017_Martinez_01.html..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there w...

  9. u

    Labour force survey estimates (LFS), by National Occupational Classification...

    • beta.data.urbandatacentre.ca
    • datasets.ai
    • +3more
    Updated Sep 13, 2024
    + more versions
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    (2024). Labour force survey estimates (LFS), by National Occupational Classification for Statistics (NOC-S) and sex, unadjusted for seasonality [Dataset]. https://beta.data.urbandatacentre.ca/dataset/gov-canada-82000457-099b-4cf9-9181-107a0c7effb6
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    Dataset updated
    Sep 13, 2024
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    Number of persons in the labour force (employment and unemployment) and not in the labour force, unemployment rate, participation rate, and employment rate, by National Occupational Classification for Statistics (NOC-S) and sex, last 5 months.

  10. Labour force survey estimates (LFS), job tenure by National Occupational...

    • open.canada.ca
    • www150.statcan.gc.ca
    • +1more
    csv, html, xml
    Updated Jan 17, 2023
    + more versions
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    Statistics Canada (2023). Labour force survey estimates (LFS), job tenure by National Occupational Classification for Statistics (NOC-S) and sex, unadjusted for seasonality [Dataset]. https://open.canada.ca/data/en/dataset/e922ac08-b430-4390-b500-bcee3e593a25
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    html, xml, csvAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    Number of employed persons by job tenure, National Occupational Classification for Statistics (NOC-S) and sex, last 5 months.

  11. Labour Force Survey Employment status by occupation

    • data.wu.ac.at
    html
    Updated Aug 13, 2014
    + more versions
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    Office for National Statistics (2014). Labour Force Survey Employment status by occupation [Dataset]. https://data.wu.ac.at/schema/data_gov_uk/M2M1NTkwMWYtOGYxZi00MDUyLTgwZjktYjM3YzdjMThlYWFj
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    htmlAvailable download formats
    Dataset updated
    Aug 13, 2014
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

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

    Description

    Labour Force Survey (LFS) data relating to employees, self-employed, full-time and part-time workers by occupation group (based on Standard Occupation Classification 2000) by sex.

    Source agency: Office for National Statistics

    Designation: National Statistics

    Language: English

    Alternative title: LFS

  12. i

    Occupational Employment Estimates - Dataset - The Indiana Data Hub

    • hub.mph.in.gov
    Updated Sep 11, 2018
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    (2018). Occupational Employment Estimates - Dataset - The Indiana Data Hub [Dataset]. https://hub.mph.in.gov/dataset/occupational-employment-estimates
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    Dataset updated
    Sep 11, 2018
    License

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

    Description

    The Occupational Employment Statistics (OES) program conducts a semiannual survey designed to produce estimates of employment and wages for specific occupations. The OES program collects data on wage and salary workers in nonfarm establishments in order to produce employment and wage estimates for about 800 occupations. Data from self-employed persons are not collected and are not included in the estimates. The OES program produces these occupational estimates for the nation as a whole, by state, by metropolitan or nonmetropolitan area, and by industry or ownership. The Bureau of Labor Statistics produces occupational employment and wage estimates for approximately 415 industry classifications at the national level. The industry classifications correspond to the sector, 3-, 4-, and selected 5- and 6-digit North American Industry Classification System (NAICS) industrial groups. The OES program surveys approximately 200,000 establishments per panel (every six months), taking three years to fully collect the sample of 1.2 million establishments. To reduce respondent burden, the collection is on a three-year survey cycle that ensures that establishments are surveyed at most once every three years. The estimates for occupations in nonfarm establishments are based on OES data collected for the reference months of May and November. The OES survey is a federal-state cooperative program between the Bureau of Labor Statistics (BLS) and State Workforce Agencies (SWAs). BLS provides the procedures and technical support, draws the sample, and produces the survey materials, while the SWAs collect the data. SWAs from all fifty states, plus the District of Columbia, Puerto Rico, Guam, and the Virgin Islands participate in the survey. Occupational employment and wage rate estimates at the national level are produced by BLS using data from the fifty states and the District of Columbia. Employers who respond to states' requests to participate in the OES survey make these estimates possible.

  13. Current Population Survey, May 2017: Contingent Worker Supplement

    • icpsr.umich.edu
    ascii, delimited, r +3
    Updated Apr 29, 2021
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    Inter-university Consortium for Political and Social Research [distributor] (2021). Current Population Survey, May 2017: Contingent Worker Supplement [Dataset]. http://doi.org/10.3886/ICPSR37191.v2
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    spss, delimited, stata, sas, ascii, rAvailable download formats
    Dataset updated
    Apr 29, 2021
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/37191/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/37191/terms

    Time period covered
    May 2017
    Area covered
    United States
    Description

    NADAC data users should note that this data collection contains data on arts-related occupations. Please read the summary below for details. This data collection is comprised of responses from two sets of survey questionnaires, the basic Current Population Survey (CPS) and a survey on the topic of Contingent Employment in the United States, which was administered as a supplement to the February 2017 CPS. In addition to administering the basic CPS, interviewers asked the supplementary questions in three-fourths of the sample households. The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States, for the week prior to the survey. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self- employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage and salaried employees, and estimates of total unemployment. The Contingent Work Supplement questions were asked of all applicable persons age 16 years and older. The supplement data is comprised of information on contingent or temporary work that a person did without expecting continuing employment from the particular employer they happened to be working for. Also included is information about each worker's expectation of continuing employment, satisfaction with their current employment arrangement, current job history, transition into the current employment arrangement, search for other employment, employee benefits, and earnings. The occupation and industry information variables in this data collection can help the data users identify individuals who worked in arts and culture related fields. The occupations are listed in categories like "Architecture and engineering occupations" and "Arts, Design, Entertainment, Sports, and Media Occupations," which include professions such as artists, architects designers, actors, musicians, and writers. Industries related to the arts and culture are in the "Arts, Entertainment, and Recreation" category. The supplement questions were not asked of unpaid family workers and persons not looking for work (this includes persons not in the labor force and unemployed persons on layoff who are not looking for work). Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income.

  14. Labour force survey estimates (LFS), employment by economic region and...

    • www150.statcan.gc.ca
    Updated Mar 20, 2017
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    Government of Canada, Statistics Canada (2017). Labour force survey estimates (LFS), employment by economic region and National Occupational Classification for Statistics (NOC-S) (x 1,000) [Dataset]. http://doi.org/10.25318/1410015401-eng
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    Dataset updated
    Mar 20, 2017
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    This table contains 2607 series, with data for years 1987 - 2000 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (79 items: Canada; Newfoundland and Labrador; South Coast-Burin Peninsula; Newfoundland and Labrador; Avalon Peninsula; Newfoundland and Labrador ...), National Occupational Classification for Statistics (NOC-S) (33 items: Total employed; all occupations; Management occupations; Senior management occupations; Other management occupations ...).

  15. 2021 American Community Survey: C24060 | OCCUPATION BY CLASS OF WORKER FOR...

    • data.census.gov
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    ACS, 2021 American Community Survey: C24060 | OCCUPATION BY CLASS OF WORKER FOR THE CIVILIAN EMPLOYED POPULATION 16 YEARS AND OVER (ACS 5-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/cedsci/table?q=C24060&g=8600000US77015&table=C24060&tid=ACSDT5Y2021.C24060
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2021
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Occupation titles and their 4-digit codes are based on the Standard Occupational Classification (SOC). The Census occupation codes for 2018 and later years are based on the 2018 revision of the SOC. To allow for the creation of the multiyear tables, occupation data in the multiyear files (prior to data year 2018) were recoded to the 2018 Census occupation codes. We recommend using caution when comparing data coded using 2018 Census occupation codes with data coded using Census occupation codes prior to data year 2018. For more information on the Census occupation code changes, please visit our website at https://www.census.gov/topics/employment /industry-occupation/guidance/code-lists.html..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed information about the 2019 changes, see the 2016 American Community Survey Content Test Report for Class of Worker located at http://www.census.gov/library/working-papers/2017/acs/2017_Martinez_01.html..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  16. Labour force survey estimates (LFS), employment by Aboriginal group,...

    • open.canada.ca
    • ouvert.canada.ca
    • +1more
    csv, html, xml
    Updated Jan 17, 2023
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    Statistics Canada (2023). Labour force survey estimates (LFS), employment by Aboriginal group, National Occupational Classification for Statistics (NOC-S), sex and age group [Dataset]. https://open.canada.ca/data/en/dataset/e355e57b-9c71-44df-a0c7-ff2061d80199
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    xml, csv, htmlAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    This table contains 450 series, with data for years 2007 - 2015 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Aboriginal group (5 items: Total population; Aboriginal population; First Nations; Métis; ...); National Occupational Classification for Statistics (NOC-S) (10 items: Total, all occupations; Management occupations; Business, finance and administrative occupations; Natural and applied sciences and related occupations; ...); Sex (3 items: Both sexes; Males; Females); Age group (3 items: 15 years and over; 25 years and over; 25 to 54 years).

  17. 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
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    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.

  18. WISCO...

    • data.europa.eu
    • data.niaid.nih.gov
    • +1more
    unknown
    Updated Jul 3, 2025
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    Zenodo (2025). WISCO occupations_ISCO08_5dgt_55languages_4000titles_with_mapping_surveycodings_20230425 [Dataset]. https://data.europa.eu/data/datasets/oai-zenodo-org-8262593?locale=da
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    unknown(8273529)Available download formats
    Dataset updated
    Jul 3, 2025
    Dataset authored and provided by
    Zenodohttp://zenodo.org/
    License

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

    Description

    Occupation is a key variable in socio-economic research, used in a wide variety of studies, but its measurement is a major challenge. The national stocks of job titles are large with 10,000’s of job titles, they are unstructured with vague boundaries between job titles, and the stock has no fixed list but instead many entries and exits over time. Measuring occupations in a multi-country survey is even a larger challenge, because occupations with the same tasks have to be coded similarly across countries. Most surveys use an open-ended survey question to measure occupations. The challenge relates to time-consuming and expensive office-coding. Alternatively, web surveys and CAPI surveys allow using a look-up database with occupational titles. The Surveycodings team and WageIndicator Foundation provide a multilingual database of coded and translated occupational titles that allow for urvey respondents' self-identification of their occupational titles, thereby tackling the challenge for multi-country surveys to classify job titles into ISCO-08 classification of occupations and to do so consistently across countries. The database is gradually extended with more occupational titles and more languages. The current version, as of 20230202, holds 55 languages for at most 4,000 titles, though some languages have only half of the titles translated, among others because the occupations do not exist in the country at stake or because no translations were aavailable. Details about this and related databases as well as related publications can be found at https://www.surveycodings.org/articles/codings/occupation.

  19. Labour force characteristics by occupation, annual

    • www150.statcan.gc.ca
    • open.canada.ca
    • +1more
    Updated Jan 24, 2025
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    Government of Canada, Statistics Canada (2025). Labour force characteristics by occupation, annual [Dataset]. http://doi.org/10.25318/1410041601-eng
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    Dataset updated
    Jan 24, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Number of persons in the labour force (employment and unemployment), unemployment rate and employment rate, by National Occupational Classification (NOC) and gender.

  20. Labour force survey estimates (LFS), employment by National Occupational...

    • open.canada.ca
    csv, html, xml
    Updated Jan 17, 2023
    + more versions
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    Statistics Canada (2023). Labour force survey estimates (LFS), employment by National Occupational Classification for Statistics (NOC-S), seasonally adjusted [Dataset]. https://open.canada.ca/data/en/dataset/d94340d6-e1e0-4378-8958-753601d7f3f7
    Explore at:
    xml, csv, htmlAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    Labour force survey estimates (LFS), employment by National Occupational Classification for Statistics (NOC-S), seasonally adjusted

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Bureau of Labor Statistics (2022). Occupational Employment and Wage Statistics (OES) [Dataset]. https://catalog.data.gov/dataset/occupational-employment-and-wage-statistics-oes
Organization logo

Occupational Employment and Wage Statistics (OES)

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14 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
May 16, 2022
Dataset provided by
Bureau of Labor Statisticshttp://www.bls.gov/
Description

The Occupational Employment and Wage Statistics (OES) program conducts a semi-annual survey to produce estimates of employment and wages for specific occupations. The OES program collects data on wage and salary workers in nonfarm establishments in order to produce employment and wage estimates for about 800 occupations. Data from self-employed persons are not collected and are not included in the estimates. The OES program produces these occupational estimates by geographic area and by industry. Estimates based on geographic areas are available at the National, State, Metropolitan, and Nonmetropolitan Area levels. The Bureau of Labor Statistics produces occupational employment and wage estimates for over 450 industry classifications at the national level. The industry classifications correspond to the sector, 3-, 4-, and 5-digit North American Industry Classification System (NAICS) industrial groups. More information and details about the data provided can be found at http://www.bls.gov/oes

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