13 datasets found
  1. 2016 Economic Surveys: SE1600CSCBO05 | Statistics for Owners of Respondent...

    • data.census.gov
    Updated Aug 16, 2018
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    ECN (2018). 2016 Economic Surveys: SE1600CSCBO05 | Statistics for Owners of Respondent Employer Firms by Whether the Business Provided the Owner's Primary Source of Personal Income by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 (ECNSVY Annual Survey of Entrepreneurs Annual Survey of Entrepreneurs Characteristics of Business Owners) [Dataset]. https://data.census.gov/table/ASECBO2016.SE1600CSCBO05?q=Bickers+Construction+Inc
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    Dataset updated
    Aug 16, 2018
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

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

    Time period covered
    2016
    Description

    Release Date: 2018-08-10.[NOTE: Includes firms with payroll at any time during 2016. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2016 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status for at least one owner and were not publicly held or not classifiable by gender, ethnicity, race, and veteran status. The 2016 Annual Survey of Entrepreneurs asked for information for up to four persons owning the largest percentage(s) of the business. Percentages are for owners of respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for Owners of Respondent Employer Firms by Whether the Business Provided the Owner's Primary Source of Personal Income by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016. ..Release Schedule. . This file was released in August 2018.. ..Key Table Information. . These data are related to all other 2016 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2016 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2016 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. For Characteristics of Business Owners (CBO) data, all estimates are of owners of firms responding to the ASE. That is, estimates are based only on firms providing gender, ethnicity, race, or veteran status; or firms not classifiable by gender, ethnicity, race, and veteran status that returned an ASE online questionnaire with at least one question answered. The ASE online questionnaire provided space for up to four owners to report their characteristics.. CBO data are not representative of all owners of all firms operating in the United States. The data do not represent all business owners in the United States.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for Owners of Respondent Employer Firms by Whether the Business Provided the Owner's Primary Source of Personal Income by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 contains data on:. . Number of owners of respondent firms with paid employees. Percent of number of owners of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of owners of respondent firms. . All owners of respondent firms. Female. Male. Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Nonminority. Veteran. Nonveteran. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 years in business. Firms with 16 or more years in business. . . Whether the busines...

  2. undefined undefined: undefined | undefined (undefined)

    • data.census.gov
    Updated Aug 16, 2018
    + more versions
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    United States Census Bureau (2018). undefined undefined: undefined | undefined (undefined) [Dataset]. https://data.census.gov/table/ASECB2016.SE1600CSCB19?q=Foster+S+A+Lumber+CO
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    Dataset updated
    Aug 16, 2018
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    License

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

    Description

    Release Date: 2018-08-10.[NOTE: Includes firms with payroll at any time during 2016. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2016 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status or that were publicly held or not classifiable by gender, ethnicity, race, or veteran status. Percentages are for respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for U.S. Employer Firms by Language(s) Used for Customer Transactions by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016. ..Release Schedule. . This file was released in August 2018.. ..Key Table Information. . These data are related to all other 2016 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2016 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2016 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. In this file, "respondent firms" refers to all firms that reported gender, ethnicity, race, or veteran status for at least one owner or returned a survey form with at least one item completed and were publicly held or not classifiable by gender, ethnicity, race, and veteran status.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for U.S. Employer Firms by Language(s) Used for Customer Transactions by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 contains data on:. . Number of firms with paid employees. Sales and receipts for firms with paid employees. Number of employees for firms with paid employees. Annual payroll for firms with paid employees. Percent of respondent firms with paid employees. Percent of sales and receipts of respondent firms with paid employees. Percent of number of employees of respondent firms with paid employees. Percent of annual payroll of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of respondent firms. . All firms. Female-owned. Male-owned. Equally male-/female-owned. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Equally minority/nonminority. Nonminority. Veteran-owned. Equally veteran-/nonveteran-owned. Nonveteran-owned. All firms classifiable by gender, ethnicity, race, and veteran status. Publicly held and other firms not classifiable by gender, ethnicity, race, and veteran status. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 years in busin...

  3. 2016 Economic Surveys: SE1600CSCB23 | Statistics for U.S. Employer Firms...

    • data.census.gov
    Updated Aug 16, 2018
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    ECN (2018). 2016 Economic Surveys: SE1600CSCB23 | Statistics for U.S. Employer Firms That Had E-Commerce Sales by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 (ECNSVY Annual Survey of Entrepreneurs Annual Survey of Entrepreneurs Characteristics of Businesses) [Dataset]. https://data.census.gov/table/ASECB2016.SE1600CSCB23?q=GEORGE%20E%20BURDEN%20PLUMBING%20CO
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    Dataset updated
    Aug 16, 2018
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

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

    Time period covered
    2016
    Area covered
    United States
    Description

    Release Date: 2018-08-10.[NOTE: Includes firms with payroll at any time during 2016. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2016 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status or that were publicly held or not classifiable by gender, ethnicity, race, or veteran status. Percentages are for respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for U.S. Employer Firms That Had E-Commerce Sales by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016. ..Release Schedule. . This file was released in August 2018.. ..Key Table Information. . These data are related to all other 2016 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2016 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2016 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. In this file, "respondent firms" refers to all firms that reported gender, ethnicity, race, or veteran status for at least one owner or returned a survey form with at least one item completed and were publicly held or not classifiable by gender, ethnicity, race, and veteran status.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for U.S. Employer Firms That Had E-Commerce Sales by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 contains data on:. . Number of firms with paid employees. Sales and receipts for firms with paid employees. Number of employees for firms with paid employees. Annual payroll for firms with paid employees. Percent of respondent firms with paid employees. Percent of sales and receipts of respondent firms with paid employees. Percent of number of employees of respondent firms with paid employees. Percent of annual payroll of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of respondent firms. . All firms. Female-owned. Male-owned. Equally male-/female-owned. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Equally minority/nonminority. Nonminority. Veteran-owned. Equally veteran-/nonveteran-owned. Nonveteran-owned. All firms classifiable by gender, ethnicity, race, and veteran status. Publicly held and other firms not classifiable by gender, ethnicity, race, and veteran status. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 years in business. Firms with 16 or more ye...

  4. FiveThirtyEight Hate Crimes Dataset

    • kaggle.com
    zip
    Updated Apr 26, 2019
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    FiveThirtyEight (2019). FiveThirtyEight Hate Crimes Dataset [Dataset]. https://www.kaggle.com/datasets/fivethirtyeight/fivethirtyeight-hate-crimes-dataset/data
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    zip(3407 bytes)Available download formats
    Dataset updated
    Apr 26, 2019
    Dataset authored and provided by
    FiveThirtyEighthttps://abcnews.go.com/538
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Content

    Hate Crimes

    This folder contains data behind the story Higher Rates Of Hate Crimes Are Tied To Income Inequality.

    HeaderDefinition
    stateState name
    median_household_incomeMedian household income, 2016
    share_unemployed_seasonalShare of the population that is unemployed (seasonally adjusted), Sept. 2016
    share_population_in_metro_areasShare of the population that lives in metropolitan areas, 2015
    share_population_with_high_school_degreeShare of adults 25 and older with a high-school degree, 2009
    share_non_citizenShare of the population that are not U.S. citizens, 2015
    share_white_povertyShare of white residents who are living in poverty, 2015
    gini_indexGini Index, 2015
    share_non_whiteShare of the population that is not white, 2015
    share_voters_voted_trumpShare of 2016 U.S. presidential voters who voted for Donald Trump
    hate_crimes_per_100k_splcHate crimes per 100,000 population, Southern Poverty Law Center, Nov. 9-18, 2016
    avg_hatecrimes_per_100k_fbiAverage annual hate crimes per 100,000 population, FBI, 2010-2015

    Sources: Kaiser Family Foundation Kaiser Family Foundation Kaiser Family Foundation Census Bureau Kaiser Family Foundation Kaiser Family Foundation Census Bureau Kaiser Family Foundation United States Elections Project Southern Poverty Law Center FBI

    Correction

    Please see the following commit: https://github.com/fivethirtyeight/data/commit/fbc884a5c8d45a0636e1d6b000021632a0861986

    Context

    This is a dataset from FiveThirtyEight hosted on their GitHub. Explore FiveThirtyEight data using Kaggle and all of the data sources available through the FiveThirtyEight organization page!

    • Update Frequency: This dataset is updated daily.

    Acknowledgements

    This dataset is maintained using GitHub's API and Kaggle's API.

    This dataset is distributed under the Attribution 4.0 International (CC BY 4.0) license.

  5. 2015 Economic Surveys: SE1500CSCB23 | Statistics for U.S. Employer Firms...

    • data.census.gov
    Updated Jul 15, 2017
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    ECN (2017). 2015 Economic Surveys: SE1500CSCB23 | Statistics for U.S. Employer Firms That Had E-Commerce Sales by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015 (ECNSVY Annual Survey of Entrepreneurs Annual Survey of Entrepreneurs Characteristics of Businesses) [Dataset]. https://data.census.gov/table/ASECB2015.SE1500CSCB23?q=E%20C%20WOOD%20CO
    Explore at:
    Dataset updated
    Jul 15, 2017
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

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

    Time period covered
    2015
    Area covered
    United States
    Description

    Release Date: 2017-07-13.[NOTE: Includes firms with payroll at any time during 2015. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2015 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status or that were publicly held or not classifiable by gender, ethnicity, race, or veteran status. Percentages are for respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for U.S. Employer Firms That Had E-Commerce Sales by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015. ..Release Schedule. . This file was released in July 2017.. ..Key Table Information. . These data are related to all other 2015 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2015 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2015 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. In this file, "respondent firms" refers to all firms that reported gender, ethnicity, race, or veteran status for at least one owner or returned a survey form with at least one item completed and were publicly held or not classifiable by gender, ethnicity, race, and veteran status.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for U.S. Employer Firms That Had E-Commerce Sales by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015 contains data on:. . Number of firms with paid employees. Sales and receipts for firms with paid employees. Number of employees for firms with paid employees. Annual payroll for firms with paid employees. Percent of respondent firms with paid employees. Percent of sales and receipts of respondent firms with paid employees. Percent of number of employees of respondent firms with paid employees. Percent of annual payroll of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of respondent firms. . All firms. Female-owned. Male-owned. Equally male-/female-owned. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Equally minority/nonminority. Nonminority. Veteran-owned. Equally veteran-/nonveteran-owned. Nonveteran-owned. All firms classifiable by gender, ethnicity, race, and veteran status. Publicly held and other firms not classifiable by gender, ethnicity, race, and veteran status. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 years in business. Firms with 16 or more year...

  6. Average percentage of women and men in management positions, first quarter...

    • www150.statcan.gc.ca
    • open.canada.ca
    • +1more
    Updated Feb 28, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Average percentage of women and men in management positions, first quarter of 2025 [Dataset]. http://doi.org/10.25318/3310094001-eng
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    Dataset updated
    Feb 28, 2025
    Dataset provided by
    Government of Canadahttp://www.gg.ca/
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Average percentage of women and men in management positions, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, first quarter of 2025.

  7. Policy Radar - At Risk Jobs

    • data-insight-tfwm.hub.arcgis.com
    Updated Nov 24, 2021
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    Transport for West Midlands (2021). Policy Radar - At Risk Jobs [Dataset]. https://data-insight-tfwm.hub.arcgis.com/documents/245cd30e9f9148869c80eaa0db3c26be
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    Dataset updated
    Nov 24, 2021
    Dataset authored and provided by
    Transport for West Midlandshttp://www.tfwm.org.uk/
    Description

    Utilising a regression analysis we created a correlation matrix utilising a number of demographic indicators from the Local Insight platform. This application is showing the distribution of the datasets that were found to have the strongest relationships, with the base comparison dataset of proportion of jobs at risk following the outbreak of COVID-19. This app contains the following datasets: proportion of jobs in education, proportion of jobs in accommodation and food services, proportion of jobs in health, proportion of business enterprises with a turnover of £1M to £4.9M, proportion of business enterprises with a turnover of £5M or more, proportion of jobs in manufacturing, proportion of working age adults who are economically active, proportion of adults who are economically inactive, proportion of people who identify their ethnicity as white and proportion of the male population aged 15 to 19.

  8. d

    U.S. Voting by Census Block Groups

    • search.dataone.org
    Updated Oct 29, 2025
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    Bryan, Michael (2025). U.S. Voting by Census Block Groups [Dataset]. http://doi.org/10.7910/DVN/NKNWBX
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    Dataset updated
    Oct 29, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Bryan, Michael
    Area covered
    United States
    Description

    PROBLEM AND OPPORTUNITY In the United States, voting is largely a private matter. A registered voter is given a randomized ballot form or machine to prevent linkage between their voting choices and their identity. This disconnect supports confidence in the election process, but it provides obstacles to an election's analysis. A common solution is to field exit polls, interviewing voters immediately after leaving their polling location. This method is rife with bias, however, and functionally limited in direct demographics data collected. For the 2020 general election, though, most states published their election results for each voting location. These publications were additionally supported by the geographical areas assigned to each location, the voting precincts. As a result, geographic processing can now be applied to project precinct election results onto Census block groups. While precinct have few demographic traits directly, their geographies have characteristics that make them projectable onto U.S. Census geographies. Both state voting precincts and U.S. Census block groups: are exclusive, and do not overlap are adjacent, fully covering their corresponding state and potentially county have roughly the same size in area, population and voter presence Analytically, a projection of local demographics does not allow conclusions about voters themselves. However, the dataset does allow statements related to the geographies that yield voting behavior. One could say, for example, that an area dominated by a particular voting pattern would have mean traits of age, race, income or household structure. The dataset that results from this programming provides voting results allocated by Census block groups. The block group identifier can be joined to Census Decennial and American Community Survey demographic estimates. DATA SOURCES The state election results and geographies have been compiled by Voting and Election Science team on Harvard's dataverse. State voting precincts lie within state and county boundaries. The Census Bureau, on the other hand, publishes its estimates across a variety of geographic definitions including a hierarchy of states, counties, census tracts and block groups. Their definitions can be found here. The geometric shapefiles for each block group are available here. The lowest level of this geography changes often and can obsolesce before the next census survey (Decennial or American Community Survey programs). The second to lowest census level, block groups, have the benefit of both granularity and stability however. The 2020 Decennial survey details US demographics into 217,740 block groups with between a few hundred and a few thousand people. Dataset Structure The dataset's columns include: Column Definition BLOCKGROUP_GEOID 12 digit primary key. Census GEOID of the block group row. This code concatenates: 2 digit state 3 digit county within state 6 digit Census Tract identifier 1 digit Census Block Group identifier within tract STATE State abbreviation, redundent with 2 digit state FIPS code above REP Votes for Republican party candidate for president DEM Votes for Democratic party candidate for president LIB Votes for Libertarian party candidate for president OTH Votes for presidential candidates other than Republican, Democratic or Libertarian AREA square kilometers of area associated with this block group GAP total area of the block group, net of area attributed to voting precincts PRECINCTS Number of voting precincts that intersect this block group ASSUMPTIONS, NOTES AND CONCERNS: Votes are attributed based upon the proportion of the precinct's area that intersects the corresponding block group. Alternative methods are left to the analyst's initiative. 50 states and the District of Columbia are in scope as those U.S. possessions voting in the general election for the U.S. Presidency. Three states did not report their results at the precinct level: South Dakota, Kentucky and West Virginia. A dummy block group is added for each of these states to maintain national totals. These states represent 2.1% of all votes cast. Counties are commonly coded using FIPS codes. However, each election result file may have the county field named differently. Also, three states do not share county definitions - Delaware, Massachusetts, Alaska and the District of Columbia. Block groups may be used to capture geographies that do not have population like bodies of water. As a result, block groups without intersection voting precincts are not uncommon. In the U.S., elections are administered at a state level with the Federal Elections Commission compiling state totals against the Electoral College weights. The states have liberty, though, to define and change their own voting precincts https://en.wikipedia.org/wiki/Electoral_precinct. The Census Bureau... Visit https://dataone.org/datasets/sha256%3A05707c1dc04a814129f751937a6ea56b08413546b18b351a85bc96da16a7f8b5 for complete metadata about this dataset.

  9. undefined undefined: undefined | undefined (undefined)

    • data.census.gov
    Updated Jul 15, 2017
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    United States Census Bureau (2017). undefined undefined: undefined | undefined (undefined) [Dataset]. https://data.census.gov/table/ASECB2015.SE1500CSCB18?q=COMMON%20WEALTH%20BUILD%20OUT%20CO
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    Dataset updated
    Jul 15, 2017
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    License

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

    Description

    Release Date: 2017-07-13.[NOTE: Includes firms with payroll at any time during 2015. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2015 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status or that were publicly held or not classifiable by gender, ethnicity, race, or veteran status. Percentages are for respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for U.S. Employer Firms That Outsourced or Transferred a Function/Service Outside the United States by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015. ..Release Schedule. . This file was released in July 2017.. ..Key Table Information. . These data are related to all other 2015 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2015 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2015 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. In this file, "respondent firms" refers to all firms that reported gender, ethnicity, race, or veteran status for at least one owner or returned a survey form with at least one item completed and were publicly held or not classifiable by gender, ethnicity, race, and veteran status.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for U.S. Employer Firms That Outsourced or Transferred a Function/Service Outside the United States by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015 contains data on:. . Number of firms with paid employees. Sales and receipts for firms with paid employees. Number of employees for firms with paid employees. Annual payroll for firms with paid employees. Percent of respondent firms with paid employees. Percent of sales and receipts of respondent firms with paid employees. Percent of number of employees of respondent firms with paid employees. Percent of annual payroll of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of respondent firms. . All firms. Female-owned. Male-owned. Equally male-/female-owned. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Equally minority/nonminority. Nonminority. Veteran-owned. Equally veteran-/nonveteran-owned. Nonveteran-owned. All firms classifiable by gender, ethnicity, race, and veteran status. Publicly held and other firms not classifiable by gender, ethnicity, race, and veteran status. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years ...

  10. f

    Impact of Treatment Type on Attendance for Different Subgroups.

    • figshare.com
    • plos.figshare.com
    xls
    Updated Jun 2, 2023
    + more versions
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    Faizan Diwan; Grace Makana; David McKenzie; Silvia Paruzzolo (2023). Impact of Treatment Type on Attendance for Different Subgroups. [Dataset]. http://doi.org/10.1371/journal.pone.0109873.t005
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Faizan Diwan; Grace Makana; David McKenzie; Silvia Paruzzolo
    License

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

    Description

    Notes: Huber-White Standard error in Parentheses. *, **, and *** indicate significance at the 10, 5 and 1 percent levels respectively.Coefficients are from OLS regressions after controlling for marketplace dummies.P-values are for test of equality of treatment effect across subgroups.Impact of Treatment Type on Attendance for Different Subgroups.

  11. Instagram users in the United Kingdom 2019-2028

    • statista.com
    Updated Nov 22, 2024
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    Statista Research Department (2024). Instagram users in the United Kingdom 2019-2028 [Dataset]. https://www.statista.com/topics/3236/social-media-usage-in-the-uk/
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    Dataset updated
    Nov 22, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United Kingdom
    Description

    The number of Instagram users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 2.1 million users (+7.02 percent). After the ninth consecutive increasing year, the Instagram user base is estimated to reach 32 million users and therefore a new peak in 2028. Notably, the number of Instagram users of was continuously increasing over the past years.User figures, shown here with regards to the platform instagram, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

  12. Employment by industry, annual

    • www150.statcan.gc.ca
    • open.canada.ca
    • +1more
    Updated Mar 27, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Employment by industry, annual [Dataset]. http://doi.org/10.25318/1410020201-eng
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    Dataset updated
    Mar 27, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Number of employees by North American Industry Classification System (NAICS) and type of employee, last 5 years.

  13. FiveThirtyEight Primary Candidates 2018 Dataset

    • kaggle.com
    zip
    Updated Apr 26, 2019
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    FiveThirtyEight (2019). FiveThirtyEight Primary Candidates 2018 Dataset [Dataset]. https://www.kaggle.com/fivethirtyeight/fivethirtyeight-primary-candidates-2018-dataset
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    zip(39517 bytes)Available download formats
    Dataset updated
    Apr 26, 2019
    Dataset authored and provided by
    FiveThirtyEighthttps://abcnews.go.com/538
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Content

    Primary Candidates 2018

    This folder contains the data behind the stories:

    This project looks at patterns in open Democratic and Republican primary elections for the U.S. Senate, U.S. House and governor in 2018.

    dem_candidates.csv contains information about the 811 candidates who have appeared on the ballot this year in Democratic primaries for Senate, House and governor, not counting races featuring a Democratic incumbent, as of August 7, 2018.

    rep_candidates.csv contains information about the 774 candidates who have appeared on the ballot this year in Republican primaries for Senate, House and governor, not counting races featuring a Republican incumbent, through September 13, 2018.

    Here is a description and source for each column in the accompanying datasets.

    dem_candidates.csv and rep_candidates.csv include:

    ColumnDescription
    CandidateAll candidates who received votes in 2018’s Democratic primary elections for U.S. Senate, U.S. House and governor in which no incumbent ran. Supplied by Ballotpedia.
    StateThe state in which the candidate ran. Supplied by Ballotpedia.
    DistrictThe office and, if applicable, congressional district number for which the candidate ran. Supplied by Ballotpedia.
    Office TypeThe office for which the candidate ran. Supplied by Ballotpedia.
    Race TypeWhether it was a “regular” or “special” election. Supplied by Ballotpedia.
    Race Primary Election DateThe date on which the primary was held. Supplied by Ballotpedia.
    Primary StatusWhether the candidate lost (“Lost”) the primary or won/advanced to a runoff (“Advanced”). Supplied by Ballotpedia.
    Primary Runoff Status“None” if there was no runoff; “On the Ballot” if the candidate advanced to a runoff but it hasn’t been held yet; “Advanced” if the candidate won the runoff; “Lost” if the candidate lost the runoff. Supplied by Ballotpedia.
    General Status“On the Ballot” if the candidate won the primary or runoff and has advanced to November; otherwise, “None.” Supplied by Ballotpedia.
    Primary %The percentage of the vote received by the candidate in his or her primary. In states that hold runoff elections, we looked only at the first round (the regular primary). In states that hold all-party primaries (e.g., California), a candidate’s primary percentage is the percentage of the total Democratic vote they received. Unopposed candidates and candidates nominated by convention (not primary) are given a primary percentage of 100 but were excluded from our analysis involving vote share. Numbers come from official results posted by the secretary of state or local elections authority; if those were unavailable, we used unofficial election results from the New York Times.
    Won Primary“Yes” if the candidate won his or her primary and has advanced to November; “No” if he or she lost.

    dem_candidates.csv includes:

    ColumnDescription
    Gender“Male” or “Female.” Supplied by Ballotpedia.
    Partisan LeanThe FiveThirtyEight partisan lean of the district or state in which the election was held. Partisan leans are calculated by finding the average difference between how a state or district voted in the past two presidential elections and how the country voted overall, with 2016 results weighted 75 percent and 2012 results weighted 25 percent.
    Race“White” if we identified the candidate as non-Hispanic white; “Nonwhite” if we identified the candidate as Hispanic and/or any nonwhite race; blank if we could not identify the candidate’s race or ethnicity. To determine race and ethnicity, we checked each candidate’s website to see if he or she identified as a certain race. If not, we spent no more than two minutes searching online news reports for references to the candidate’s race.
    Veteran?If the candidate’s website says that he or she served in the armed forces, we put “Yes.” If the website is silent on the subject (or explicitly says he or she didn’t serve), we put “No.” If the field was left blank, no website was available.
    LGBTQ?If the candidate’s website says that he or she is LGBTQ (including indirect references like to a same-sex partner), we put “Yes.” If the website is silent on the subject (or explicitly says he or she is straight), we put “No.” If the field was...
  14. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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ECN (2018). 2016 Economic Surveys: SE1600CSCBO05 | Statistics for Owners of Respondent Employer Firms by Whether the Business Provided the Owner's Primary Source of Personal Income by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 (ECNSVY Annual Survey of Entrepreneurs Annual Survey of Entrepreneurs Characteristics of Business Owners) [Dataset]. https://data.census.gov/table/ASECBO2016.SE1600CSCBO05?q=Bickers+Construction+Inc
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2016 Economic Surveys: SE1600CSCBO05 | Statistics for Owners of Respondent Employer Firms by Whether the Business Provided the Owner's Primary Source of Personal Income by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 (ECNSVY Annual Survey of Entrepreneurs Annual Survey of Entrepreneurs Characteristics of Business Owners)

2016: ECNSVY Annual Survey of Entrepreneurs Annual Survey of Entrepreneurs Characteristics of Business Owners

Explore at:
Dataset updated
Aug 16, 2018
Dataset provided by
United States Census Bureauhttp://census.gov/
Authors
ECN
License

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

Time period covered
2016
Description

Release Date: 2018-08-10.[NOTE: Includes firms with payroll at any time during 2016. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2016 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status for at least one owner and were not publicly held or not classifiable by gender, ethnicity, race, and veteran status. The 2016 Annual Survey of Entrepreneurs asked for information for up to four persons owning the largest percentage(s) of the business. Percentages are for owners of respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for Owners of Respondent Employer Firms by Whether the Business Provided the Owner's Primary Source of Personal Income by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016. ..Release Schedule. . This file was released in August 2018.. ..Key Table Information. . These data are related to all other 2016 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2016 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2016 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. For Characteristics of Business Owners (CBO) data, all estimates are of owners of firms responding to the ASE. That is, estimates are based only on firms providing gender, ethnicity, race, or veteran status; or firms not classifiable by gender, ethnicity, race, and veteran status that returned an ASE online questionnaire with at least one question answered. The ASE online questionnaire provided space for up to four owners to report their characteristics.. CBO data are not representative of all owners of all firms operating in the United States. The data do not represent all business owners in the United States.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for Owners of Respondent Employer Firms by Whether the Business Provided the Owner's Primary Source of Personal Income by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 contains data on:. . Number of owners of respondent firms with paid employees. Percent of number of owners of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of owners of respondent firms. . All owners of respondent firms. Female. Male. Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Nonminority. Veteran. Nonveteran. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 years in business. Firms with 16 or more years in business. . . Whether the busines...

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