100+ datasets found
  1. What is the most common race/ethnicity?

    • hub.arcgis.com
    • gis-for-racialequity.hub.arcgis.com
    Updated Apr 14, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Urban Observatory by Esri (2020). What is the most common race/ethnicity? [Dataset]. https://hub.arcgis.com/maps/2603a03fc55244c19f7f73d04cd53cea
    Explore at:
    Dataset updated
    Apr 14, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    Knowing the racial and ethnic composition of a community is often one of the first steps in understanding, serving, and advocating for various groups. This information can help enforce laws, policies, and regulations against discrimination based on race and ethnicity. These statistics can also help tailor services to accommodate cultural differences.This multi-scale map shows the most common race/ethnicity living within an area. Map opens at tract-level in Los Angeles, CA but has national coverage. Zoom out to see counties and states.This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available. The data on race were derived from answers to the question on race that was asked of individuals in the United States. The Census Bureau collects racial data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically. The categories represent a social-political construct designed for collecting data on the race and ethnicity of broad population groups in this country, and are not anthropologically or scientifically based. Learn more here.

  2. H

    Race/ethnicity swap survey

    • dataverse.harvard.edu
    Updated Jan 18, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Emilce Santana (2025). Race/ethnicity swap survey [Dataset]. http://doi.org/10.7910/DVN/TXF4H2
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 18, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Emilce Santana
    License

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

    Description

    These files are the replication data/dofiles for my working papers "Quantifying the Causal Effect of Ethnoracial Background in Online Dating" and "The Role of Educational Background in Dating between Black and White People". I also include results of pretests I conducted prior to the main phase of the data collection.

  3. u

    American Community Survey

    • gstore.unm.edu
    csv, geojson, gml +5
    Updated Mar 6, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Earth Data Analysis Center (2020). American Community Survey [Dataset]. https://gstore.unm.edu/apps/rgis/datasets/474fef30-414f-4269-b37a-5103c84b141f/metadata/FGDC-STD-001-1998.html
    Explore at:
    json(5), gml(5), shp(5), kml(5), csv(5), xls(5), zip(1), geojson(5)Available download formats
    Dataset updated
    Mar 6, 2020
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    2018
    Area covered
    West Bounding Coordinate -109.05017 East Bounding Coordinate -103.00196 North Bounding Coordinate 37.000293 South Bounding Coordinate 31.33217, New Mexico
    Description

    A broad and generalized selection of 2014-2018 US Census Bureau 2018 5-year American Community Survey race, ethnicity and citizenship data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico counties). The selection, while not comprehensive, provides a first-level characterization of the race and/or ethnicity of populations in New Mexico, along with citizenship status and nativity. The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users. The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. As in the decennial census, strict confidentiality laws protect all information that could be used to identify individuals or households.The ACS combines population or other data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. The primary advantage of using multiyear estimates is the increased statistical reliability of the data for less populated areas and small population subgroups. 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. While each full Data Profile contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by New Mexico county boundaries, based on TIGER/Line Files: shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database.

  4. 2022 Economic Surveys: AB00MYCSA01B | Annual Business Survey: Statistics for...

    • test.data.census.gov
    • data.census.gov
    Updated Dec 19, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ECN (2024). 2022 Economic Surveys: AB00MYCSA01B | Annual Business Survey: Statistics for Employer Firms by Ethnicity for the U.S.: 2022 (ECNSVY Annual Business Survey Company Summary) [Dataset]. https://test.data.census.gov/table/ABSCS2022.AB00MYCSA01B?q=22:+Utilities
    Explore at:
    Dataset updated
    Dec 19, 2024
    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
    2022
    Area covered
    United States
    Description

    Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Ethnicity for the U.S.: 2022.Table ID.ABSCS2022.AB00MYCSA01B.Survey/Program.Economic Surveys.Year.2022.Dataset.ECNSVY Annual Business Survey Company Summary.Release Date.2024-12-19.Release Schedule.The Annual Business Survey (ABS) occurs every year, beginning in reference year 2017.For more information about ABS planned data product releases, see Tentative ABS Schedule..Dataset Universe.The dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Methodology.Data Items and Other Identifying Records.Number of employer firms (firms with paid employees)Sales and receipts of employer firms (reported in $1,000s of dollars)Number of employees (during the March 12 pay period)Annual payroll (reported in $1,000s of dollars)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Ethnicity Hispanic Mexican, Mexican American, Chicano Puerto Rican Cuban Other Hispanic, Latino, or Spanish Equally Hispanic/non-Hispanic Non-Hispanic Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status) Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the ABS are employer companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The data are shown for the U.S. only.For information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00") NAICS code. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Office of Notaries (NAICS 541120)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.The ABS sample includes firms that are selected with certainty if they have known research and development activities, were included in the 2022 BERD sample, or have high receipts, payroll, or employment. Total sample size is 850,000 firms. The universe is stratified by state, industry group, and expected demographic group. Firms selected to the sample receive a questionnaire. For all data on this table, firms not selected into the sample are represented with administrative, 2022 Economic Census, or other economic surveys records.For more information about the sample design, see Annual Business Survey Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0351).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business' data or identity.To comply with data quality standards, data rows with high relative standard errors (RSE) are not presented. Additionally, firm counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the Annual Business Survey Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, and more, see Technical Documentation..Weights.For more information about weighting, see Annual Business Survey Methodology..Table Information.FTP Download.https://www2.census.gov/programs-surveys/abs/data/2022/.API Information.Annual Business Survey (ABS) data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing da...

  5. N

    states in U.S. Ranked by Non-Hispanic Other Race Population // 2025 Edition

    • neilsberg.com
    csv, json
    Updated Feb 11, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Neilsberg Research (2025). states in U.S. Ranked by Non-Hispanic Other Race Population // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/lists/states-in-united-states-by-non-hispanic-other-race-population/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 11, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    United States
    Variables measured
    Non-Hispanic Other Race Population, Non-Hispanic Other Race Population as Percent of Total Population of states in United States, Non-Hispanic Other Race Population as Percent of Total Non-Hispanic Other Race Population of United States
    Measurement technique
    To measure the rank and respective trends, we initially gathered data from the five most recent American Community Survey (ACS) 5-Year Estimates. We then analyzed and categorized the data for each of the racial categories identified by the U.S. Census Bureau. Based on the required racial category classification, we calculated the rank. For geographies with no population reported for the chosen race, we did not assign a rank and excluded them from the list. It is possible that a small population exists but was not reported or captured due to limitations or variations in Census data collection and reporting. We ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories and do not rely on any ethnicity classification, unless explicitly required.For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    This list ranks the 50 states in the United States by Non-Hispanic Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each states over the past five years.

    Content

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

    • 2019-2023 American Community Survey 5-Year Estimates
    • 2018-2022 American Community Survey 5-Year Estimates
    • 2017-2021 American Community Survey 5-Year Estimates
    • 2016-2020 American Community Survey 5-Year Estimates
    • 2015-2019 American Community Survey 5-Year Estimates

    Variables / Data Columns

    • Rank by Non-Hispanic Other Race Population: This column displays the rank of states in the United States by their Non-Hispanic Some Other Race (SOR) population, using the most recent ACS data available.
    • states: The states for which the rank is shown in the previous column.
    • Non-Hispanic Other Race Population: The Non-Hispanic Other Race population of the states is shown in this column.
    • % of Total states Population: This shows what percentage of the total states population identifies as Non-Hispanic Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
    • % of Total U.S. Non-Hispanic Other Race Population: This tells us how much of the entire United States Non-Hispanic Other Race population lives in that states. Please note that the sum of all percentages may not equal one due to rounding of values.
    • 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

    Good to know

    Margin of Error

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

    Custom data

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

    Inspiration

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

  6. u

    American Community Survey

    • gstore.unm.edu
    csv, geojson, gml +5
    Updated Mar 6, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Earth Data Analysis Center (2020). American Community Survey [Dataset]. https://gstore.unm.edu/apps/rgis/datasets/5991c4f8-db89-49d1-a501-1f18e7371e21/metadata/FGDC-STD-001-1998.html
    Explore at:
    zip(1), csv(5), xls(5), geojson(5), gml(5), json(5), kml(5), shp(5)Available download formats
    Dataset updated
    Mar 6, 2020
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    2017
    Area covered
    New Mexico, West Bounding Coordinate -109.05017 East Bounding Coordinate -103.00196 North Bounding Coordinate 37.000293 South Bounding Coordinate 31.33217
    Description

    A broad and generalized selection of 2013-2017 US Census Bureau 2017 5-year American Community Survey race, ethnicity and citizenship data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico counties). The selection, while not comprehensive, provides a first-level characterization of the race and/or ethnicity of populations in New Mexico, along with citizenship status and nativity. The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users. The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. As in the decennial census, strict confidentiality laws protect all information that could be used to identify individuals or households.The ACS combines population or other data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. The primary advantage of using multiyear estimates is the increased statistical reliability of the data for less populated areas and small population subgroups. 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. While each full Data Profile contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by New Mexico county boundaries, based on TIGER/Line Files: shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database.

  7. 2017 Economic Surveys: AB00MYCSA01B | Annual Business Survey: Statistics for...

    • data.census.gov
    Updated May 19, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ECN (2020). 2017 Economic Surveys: AB00MYCSA01B | Annual Business Survey: Statistics for Employer Firms by Ethnicity for the U.S.: 2017 (ECNSVY Annual Business Survey Company Summary) [Dataset]. https://data.census.gov/table/ABSCS2017.AB00MYCSA01B?q=517311
    Explore at:
    Dataset updated
    May 19, 2020
    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
    2017
    Area covered
    United States
    Description

    Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Ethnicity for the U.S.: 2017.Table ID.ABSCS2017.AB00MYCSA01B.Survey/Program.Economic Surveys.Year.2017.Dataset.ECNSVY Annual Business Survey Company Summary.Release Date.2020-05-19.Release Schedule.The Annual Business Survey (ABS) occurs every year, beginning in reference year 2017.For more information about ABS planned data product releases, see Tentative ABS Schedule..Dataset Universe.The dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2017 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Methodology.Data Items and Other Identifying Records.Number of employer firms (firms with paid employees)Sales and receipts of employer firms (reported in $1,000s of dollars)Number of employees (during the March 12 pay period)Annual payroll (reported in $1,000s of dollars)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Ethnicity Hispanic Mexican, Mexican American, Chicano Puerto Rican Cuban Other Hispanic, Latino, or Spanish Equally Hispanic/non-Hispanic Non-Hispanic Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status) Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the ABS are employer companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The data are shown for the U.S. only.For information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00") NAICS code. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.The ABS sample includes firms that are selected with certainty if they have known research and development activities, were included in the 2017 BERD sample, or have high receipts, payroll, or employment. Total sample size is 850,000 firms. The universe is stratified by state, industry group, and expected demographic group. Firms selected to the sample receive a questionnaire. For all data on this table, firms not selected into the sample are represented with administrative, 2017 Economic Census, or other economic surveys records.For more information about the sample design, see Annual Business Survey Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY20-008).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business' data or identity.To comply with data quality standards, data rows with high relative standard errors (RSE) are not presented. Additionally, firm counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the Annual Business Survey Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, and more, see Technical Documentation..Weights.For more information about weighting, see Annual Business Survey Methodology..Table Information.FTP Download.https://www2.census.gov/programs-surveys/abs/data/2017/.API Information.Annual Business Survey (ABS) data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data ...

  8. American Community Survey (ACS) Race and Hispanic Origin Variables –...

    • performance-data-integration-space-fdot.hub.arcgis.com
    Updated Aug 10, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Florida Department of Transportation (2023). American Community Survey (ACS) Race and Hispanic Origin Variables – Boundaries [Dataset]. https://performance-data-integration-space-fdot.hub.arcgis.com/items/4dcfd68df9254b5886d38e992ac93b72
    Explore at:
    Dataset updated
    Aug 10, 2023
    Dataset authored and provided by
    Florida Department of Transportationhttps://www.fdot.gov/
    Area covered
    Earth
    Description

    The Florida Department of Transportation (FDOT or Department) has identified processed, authoritative datasets to support the preliminary spatial analysis of equity considerations. These processed datasets are available at larger geographies, such as the United States Census Bureau tract or county-level; however, additional raw datasets from other sources can be used to identify equity considerations. Most of this raw data is available at the Census block group, parcel, or point-level—but additional processing is required to make suitable for spatial analysis. For more information, contact Dana Reiding with the FDOT Forecasting and Trends Office (FTO).The American Community Survey (ACS) Race and Hispanic Origin Variables – Boundaries layer is identified to support the equity community indicator of race and ethnicity. This layer contains the most current release of data from the ACS about population broken down by race and Hispanic origin. These are 5-year estimates shown by tract, county, and state boundaries. The layer is owned and managed by the ESRI Demographics Team. Data Link: https://www.arcgis.com/home/item.html?id=23ab8028f1784de4b0810104cd5d1c8f Available Geography Levels: State, County, Tract Owner/Managed By: ESRI Demographics FDOT Point of Contact:Dana Reiding, ManagerForecasting and Trends OfficeFlorida Department of TransportationDana.Reiding@dot.state.fl.us605 Suwannee Street, Tallahassee, Florida 32399850-414-4719

  9. Understanding Society: Ethnicity and Health Teaching Dataset Wave 1,...

    • beta.ukdataservice.ac.uk
    Updated 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Institute For Social University Of Essex (2023). Understanding Society: Ethnicity and Health Teaching Dataset Wave 1, 2009-2010 [Dataset]. http://doi.org/10.5255/ukda-sn-8465-2
    Explore at:
    Dataset updated
    2023
    Dataset provided by
    DataCitehttps://www.datacite.org/
    UK Data Servicehttps://ukdataservice.ac.uk/
    Authors
    Institute For Social University Of Essex
    Description

    Understanding Society, (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

    This is a teaching resource for those who are new to data analysis. It is a step-by-step guide starting from exploring a survey, understanding the structure of the survey data and then using the data to do some simple exercises to measure differences in health and wellbeing across ethnic groups. The survey used here is Understanding Society: the UK Household Longitudinal Study which interviews individuals in the sampled households every year. To make it easier to use the teaching dataset accompanying this teaching resource only includes responses given by adults (16+ year olds) during the first interview to questions about ethnicity, health and wellbeing and some key socio-demographic characteristics such as age, sex, education, income, labour market status etc. The statistical software used to construct the dataset is Stata, but it is also available to download in SPSS and tab-delimited text formats.

    Nandi, Alita and Wiltshire, Deborah. (2019). "Teaching Resource: Analysing ethnic differences in health using data from Understanding Society".

    For information on the main Understanding Society study, see SN 6614, Understanding Society and Harmonised BHPS.

    Latest edition information
    For the second edition (August 2020), updated data and documentation files were deposited.

  10. 2018 Economic Surveys: AB00MYCSA01B | Annual Business Survey: Statistics for...

    • data.census.gov
    Updated Jan 28, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ECN (2021). 2018 Economic Surveys: AB00MYCSA01B | Annual Business Survey: Statistics for Employer Firms by Ethnicity for the U.S.: 2018 (ECNSVY Annual Business Survey Company Summary) [Dataset]. https://data.census.gov/table/ABSCS2018.AB00MYCSA01B
    Explore at:
    Dataset updated
    Jan 28, 2021
    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
    2018
    Area covered
    United States
    Description

    Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Ethnicity for the U.S.: 2018.Table ID.ABSCS2018.AB00MYCSA01B.Survey/Program.Economic Surveys.Year.2018.Dataset.ECNSVY Annual Business Survey Company Summary.Release Date.2021-01-28.Release Schedule.The Annual Business Survey (ABS) occurs every year, beginning in reference year 2017.For more information about ABS planned data product releases, see Tentative ABS Schedule..Dataset Universe.The dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2017 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Methodology.Data Items and Other Identifying Records.Number of employer firms (firms with paid employees)Sales and receipts of employer firms (reported in $1,000s of dollars)Number of employees (during the March 12 pay period)Annual payroll (reported in $1,000s of dollars)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Ethnicity Hispanic Equally Hispanic/non-Hispanic Non-Hispanic Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status) Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the ABS are employer companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The data are shown for the U.S. only.For information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00") NAICS code. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.The ABS sample includes firms that are selected with certainty if they have known research and development activities, were included in the 2018 BERD sample, or have high receipts, payroll, or employment. Total sample size is 300,000 firms. The universe is stratified by state, industry group, and expected demographic group. Firms selected to the sample receive a questionnaire. For all data on this table, firms not selected into the sample are represented with administrative, 2017 Economic Census, or other economic surveys records.For more information about the sample design, see Annual Business Survey Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY20-424).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business' data or identity.To comply with data quality standards, data rows with high relative standard errors (RSE) are not presented. Additionally, firm counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the Annual Business Survey Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, and more, see Technical Documentation..Weights.For more information about weighting, see Annual Business Survey Methodology..Table Information.FTP Download.https://www2.census.gov/programs-surveys/abs/data/2018/.API Information.Annual Business Survey (ABS) data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsS - Estimate does not meet publication standards becau...

  11. Race/Ethnicity Group with Lowest Median Income in the U.S.

    • hub.arcgis.com
    • coronavirus-resources.esri.com
    • +2more
    Updated Oct 18, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Urban Observatory by Esri (2018). Race/Ethnicity Group with Lowest Median Income in the U.S. [Dataset]. https://hub.arcgis.com/maps/0ed46c1e58034bf583e7afc99fcd6a5c
    Explore at:
    Dataset updated
    Oct 18, 2018
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    This map shows which race/ethnicity group has the lowest median income in the United States by tract, county and state, using the latest available data from the U.S. Census Bureau's American Community Survey (ACS).For each group showing a median income figure, the lowest median income determines the color used on the map. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey. The map's topic is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. To see the full list of attributes available in this map's layers, go to a layer listed under the "Layers" section below and choose the "Data" tab for that layer, and choose "Fields" at the top right on that page.

  12. Presbyterian Panel Survey, February 2017 - Race and Ethnicity, Clergy

    • thearda.com
    • osf.io
    Updated Feb 2017
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    The Association of Religion Data Archives (2017). Presbyterian Panel Survey, February 2017 - Race and Ethnicity, Clergy [Dataset]. http://doi.org/10.17605/OSF.IO/P2U3D
    Explore at:
    Dataset updated
    Feb 2017
    Dataset provided by
    Association of Religion Data Archives
    Dataset funded by
    Congregational Ministries Division, Presbyterian Church (U.S.A.)
    Description

    The Presbyterian Panel began in 1973 and is an ongoing panel study in which mailed and web-based questionnaires are used to survey representative samples of constituency groups of the Presbyterian Church (U.S.A.). These constituency groups include members, elders, pastors serving in a congregation and specialized clergy serving elsewhere. The August 2013 and February 2017 Panel surveys both dealt with race and ethnicity, and the inclusion of a number of identical questions in the two surveys allows for analysis of change over time. This dataset contains data from clergy in the Presbyterian Church (U.S.A.).

  13. Annual Housing Survey, 1982 [United States]: SMSA Files

    • icpsr.umich.edu
    ascii, sas, spss +1
    Updated Sep 3, 2008
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    United States. Bureau of the Census (2008). Annual Housing Survey, 1982 [United States]: SMSA Files [Dataset]. http://doi.org/10.3886/ICPSR08310.v1
    Explore at:
    stata, ascii, sas, spssAvailable download formats
    Dataset updated
    Sep 3, 2008
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States. Bureau of the Census
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/8310/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/8310/terms

    Time period covered
    1982
    Area covered
    Clifton, Newport News, Georgia, Passaic, San Bernardino, Paterson, Madison, Philadelphia, New Jersey, United States
    Description

    This data collection provides information on the characteristics of the housing inventory in 12 Standard Metropolitan Statistical Areas (SMSAs). Data include year the structure was built, type and number of living quarters, occupancy status, presence of commercial establishments on the property, presence of a garage, and property value. Additional data focus on kitchen and plumbing facilities, type of heating fuel used, source of water, sewage disposal, and heating and air conditioning equipment. Information about housing expenses includes mortgage or rent payments, utility costs, garbage collection fees, property insurance, and real estate taxes as well as repairs, additions, or alterations to the property. Similar data are provided for housing units previously occupied by respondents who had recently moved. Indicators of housing and neighborhood quality are also supplied. Housing quality variables include privacy of bedrooms, condition of kitchen facilities, basement or roof leakage, presence of cracks or holes in walls, ceilings, or floor, reliability of plumbing and heating equipment, and concealed electrical wiring. The presence of storm doors and windows and insulation was also noted. Neighborhood quality variables indicate presence of and objection to street noise, odors, crime, litter, and rundown and abandoned structures, as well as the adequacy of street lighting, public transportation, public parks, schools, shopping facilities, and police and fire protection. Extensive information on the ability of handicapped persons to move around their homes is also provided. Respondents were asked if they needed special equipment, or the help of another person to move around. They were also asked about the presence or need for housing features to aid their movement, such as ramps, braille lettering, elevators, and extra wide doors. In addition to housing characteristics, demographic data for household members are provided, including sex, age, race, income, marital status, and household relationship. Additional data are available for the household head, including Hispanic origin, length of residence, and travel-to-work information.

  14. a

    Justice40 Disadvantaged or Partially Disadvantaged Tracts by Race/Ethnicity...

    • atlas-connecteddmv.hub.arcgis.com
    • regionaldatahub-brag.hub.arcgis.com
    Updated Jun 10, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ArcGIS Living Atlas Team (2022). Justice40 Disadvantaged or Partially Disadvantaged Tracts by Race/Ethnicity (Archive) [Dataset]. https://atlas-connecteddmv.hub.arcgis.com/maps/945b3f2e39a64569ab2d0700a527361b
    Explore at:
    Dataset updated
    Jun 10, 2022
    Dataset authored and provided by
    ArcGIS Living Atlas Team
    Area covered
    Description

    This map uses an archive of Version 1.0 of the CEJST data as a fully functional GIS layer. See an archive of the latest version of the CEJST tool using Version 2.0 of the data released in December 2024 here.This map shows Census tracts throughout the US based on if they are considered disadvantaged or partially disadvantaged according to Justice40 Initiative criteria. This is overlaid with the most recent American Community Survey (ACS) figures from the U.S. Census Bureau to communicate the predominant race that lives within these disadvantaged or partially disadvantaged tracts. Predominance helps us understand the group of population which has the largest count within an area. Colors are more transparent if the predominant race has a similar count to another race/ethnicity group. The colors on the map help us better understand the predominant race or ethnicity:Hispanic or LatinoWhite Alone, not HispanicBlack or African American Alone, not HispanicAsian Alone, not HispanicAmerican Indian and Alaska Native Alone, not HispanicTwo or more races, not HispanicNative Hawaiian and Other Pacific Islander, not HispanicSome other race, not HispanicSearch for any region, city, or neighborhood throughout the US, DC, and Puerto Rico to learn more about the population in the disadvantaged tracts. Click on any tract to learn more. Zoom to your area, filter to your county or state, and save this web map focused on your area to share the pattern with others. You can also use this web map within an ArcGIS app such as a dashboard, instant app, or story. This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.Note: Justice40 tracts use 2010-based boundaries, while the most recent ACS figures are offered on 2020-based boundaries. When you click on an area, there will be multiple pop-ups returned due to the differences in these boundaries. From Justice40 data source:"Census tract geographical boundaries are determined by the U.S. Census Bureau once every ten years. This tool utilizes the census tract boundaries from 2010 because they match the datasets used in the tool. The U.S. Census Bureau will update these tract boundaries in 2020.Under the current formula, a census tract will be identified as disadvantaged in one or more categories of criteria:IF the tract is above the threshold for one or more environmental or climate indicators AND the tract is above the threshold for the socioeconomic indicatorsCommunities are identified as disadvantaged by the current version of the tool for the purposes of the Justice40 Initiative if they are located in census tracts that are at or above the combined thresholds in one or more of eight categories of criteria.The goal of the Justice40 Initiative is to provide 40 percent of the overall benefits of certain Federal investments in [eight] key areas to disadvantaged communities. These [eight] key areas are: climate change, clean energy and energy efficiency, clean transit, affordable and sustainable housing, training and workforce development, the remediation and reduction of legacy pollution, [health burdens] and the development of critical clean water infrastructure." Source: Climate and Economic Justice Screening toolPurpose"Sec. 219. Policy. To secure an equitable economic future, the United States must ensure that environmental and economic justice are key considerations in how we govern. That means investing and building a clean energy economy that creates well‑paying union jobs, turning disadvantaged communities — historically marginalized and overburdened — into healthy, thriving communities, and undertaking robust actions to mitigate climate change while preparing for the impacts of climate change across rural, urban, and Tribal areas. Agencies shall make achieving environmental justice part of their missions by developing programs, policies, and activities to address the disproportionately high and adverse human health, environmental, climate-related and other cumulative impacts on disadvantaged communities, as well as the accompanying economic challenges of such impacts. It is therefore the policy of my Administration to secure environmental justice and spur economic opportunity for disadvantaged communities that have been historically marginalized and overburdened by pollution and underinvestment in housing, transportation, water and wastewater infrastructure, and health care." Source: Executive Order on Tackling the Climate Crisis at Home and AbroadUse of this Data"The pilot identifies 21 priority programs to immediately begin enhancing benefits for disadvantaged communities. These priority programs will provide a blueprint for other agencies to help inform their work to implement the Justice40 Initiative across government." Source: The Path to Achieving Justice 40

  15. f

    Participant demographics (weighted %).

    • figshare.com
    • plos.figshare.com
    xls
    Updated May 7, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Grant Jones (2025). Participant demographics (weighted %). [Dataset]. http://doi.org/10.1371/journal.pone.0321461.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 7, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Grant Jones
    License

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

    Description

    Background:Opioid use disorder (OUD) is a debilitating health condition that is associated with significant morbidity and mortality in the U.S. While preliminary studies have demonstrated that psilocybin is associated with lowered odds of OUD, current research in this domain suffers from a lack of investigation into the impact of race/ethnicity on this association.Objective:To assess the impact of race and ethnicity on the association between psilocybin use and lowered odds of OUD using data from the National Survey on Drug Use and Health (2002–2019) (N = 706,891).Method:I used survey-weighted multivariable logistic regression to test whether race/ethnicity moderates the association between psilocybin use and lowered odds of OUD. Subsequently, I stratified my sample by race and ethnicity and assessed the associations between psilocybin and OUD for individual racial and ethnic groups (White, Black, Indigenous, Asian, Multiracial, Hispanic). My analysis plan was pre-registered.Results:Race and ethnicity significantly moderated the association between psilocybin and OUD. Furthermore, when I stratified my sample by race and ethnicity, only White participants and Hispanic participants demonstrated a link between psilocybin and lowered odds of OUD (White aOR: 0.84; Hispanic aOR: 0.68). For Black, Asian, Indigenous, and Multiracial participants, psilocybin did not share a significant association with OUD.Conclusion:Race and ethnicity moderate the associations between psilocybin and OUD. Future longitudinal, experimental, and qualitative research is needed to better understand the pattern of associations I observed in this study.

  16. a

    2019-2023 American Community Survey (ACS) 5-year Race by Tenure by County

    • hub.arcgis.com
    • rlisdiscovery.oregonmetro.gov
    Updated Jan 23, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Metro (2025). 2019-2023 American Community Survey (ACS) 5-year Race by Tenure by County [Dataset]. https://hub.arcgis.com/maps/drcMetro::2019-2023-american-community-survey-acs-5-year-race-by-tenure-by-county
    Explore at:
    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Metro
    Area covered
    Description

    County-level race and ethnicity estimates for householders, cross-tabulated with tenure estimates for householders in rented housing units. Race and ethnicity estimates include the following categories: White alone, Black or African American alone, American Indian or Alaska Native alone, Native Hawaiian or Other Pacific Islander alone, Some Other Race alone, Two or More Races, White alone and Not Hispanic or Latino, Hispanic or Latino, and people of color. Estimates are accompanied by margins of error, coefficients of variation, and percentages. Geometry source: 2020 Census. Attribute source: 2019-2023 American Community Survey 5-year estimates, tables B25003, B25003A, B25003B, B25003C, B25003D, B25003E, B25003F, B25003G, B25003H, and B25003I. Date of last data update: 2024-01-11 This is official RLIS data. Contact Person: Joe Gordon joe.gordon@oregonmetro.gov 503-797-1587 RLIS Metadata Viewer: https://gis.oregonmetro.gov/rlis-metadata/#/details/3847 RLIS Terms of Use: https://rlisdiscovery.oregonmetro.gov/pages/terms-of-use

  17. 2020 Economic Surveys: AB2000CSA01 | Annual Business Survey: Statistics for...

    • data.census.gov
    Updated Nov 10, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ECN (2022). 2020 Economic Surveys: AB2000CSA01 | Annual Business Survey: Statistics for Employer Firms by Industry, Sex, Ethnicity, Race, and Veteran Status for the U.S., States, and Metro Areas: 2020 (ECNSVY Annual Business Survey Company Summary) [Dataset]. https://data.census.gov/table/ABSCS2020.AB2000CSA01?n=00
    Explore at:
    Dataset updated
    Nov 10, 2022
    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
    2020
    Area covered
    United States
    Description

    Release Date: 2022-11-10.The Census Bureau has reviewed this data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applied (Approval ID: CBDRB-FY22-308)...Release Schedule:.Data in this file come from estimates of business ownership by sex, ethnicity, race, and veteran status from the 2021 Annual Business Survey (ABS) collection. Data are also obtained from administrative records, the 2017 Economic Census, and other economic surveys...Note: The collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2021 ABS collection year produces statistics for the 2020 reference year. The "Year" column in the table is the reference year...For more information about ABS planned data product releases, see Tentative ABS Schedule...Key Table Information:.The data include U.S. firms with paid employees operating during the reference year 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. Employer 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. Employment reflects the number of paid employees during the pay period in the reference year that included March 12...Data Items and Other Identifying Records:.Data include estimates on:.Number of employer firms (firms with paid employees). Sales and receipts of employer firms (reported in $1,000s of dollars). Number of employees (during the March 12 pay period). Annual payroll (reported in $1,000s of dollars)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female. . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority. Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran. Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for businesses owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans. Firms not classifiable by sex, ethnicity, race, and veteran status are counted and tabulated separately.. The detail may not add to the total or subgroup total because a Hispanic or Latino firm may be of any race, and because a firm could be tabulated in more than one racial group. For example, if a firm responded as both Chinese and Black majority owned, the firm would be included in the detailed Asian and Black estimates but would only be counted once toward the higher level all firms' estimates.. References such as "Hispanic- or Latino-owned" businesses refer only to businesses operating in the 50 states and the District of Columbia that self-identified 51 percent or more of their ownership in 2020 to be by individuals of Mexican, Puerto Rican, Cuban or other Hispanic or Latino origin. The ABS does not distinguish between U.S. residents and nonresidents. Companies owned by foreign governments or owned by other companies, foreign or domestic, are included in the category "Unclassifiable."...Industry and Geography Coverage:..The data are shown for the total for all sectors (00) and 2-digit NAICS code levels for:..United States. States and the District of Columbia. Metropolitan Statistical Areas...Data are also shown for the 3- and 4-digit NAICS code for:..United States. States and the District of Columbia...For more information about NAICS, see NAICS Codes & Understanding Industry Classification Systems. For information about geographies used by economic programs at the Census Bureau, see Economic Census: Economic Geographies...Footnotes:.Footnote 660 - Agriculture, forestry, fishing and hunting (Sector 11): Crop and Animal Production (NAICS 111 and 112) are out of scope..Footnote 661 - Transportation and warehousing...

  18. a

    Ethnicity Plurality Ages 0-17 by Zipcode

    • hub.arcgis.com
    • data-sccphd.opendata.arcgis.com
    Updated Feb 8, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Santa Clara County Public Health (2018). Ethnicity Plurality Ages 0-17 by Zipcode [Dataset]. https://hub.arcgis.com/maps/sccphd::ethnicity-plurality-ages-0-17-by-zipcode/about
    Explore at:
    Dataset updated
    Feb 8, 2018
    Dataset authored and provided by
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Racial/ethnic plurality among children ages 0-17, Santa Clara County, 2009-2013. U.S. Census Bureau; American Community Survey, 2009-13 American Community Survey 5-Years Estimates, Table B17024; http://factfinder2.census.gov; 19 October 2015.

  19. 2017 Economic Surveys: AB1700CSA01 | Annual Business Survey: Statistics for...

    • data.census.gov
    Updated May 19, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ECN (2020). 2017 Economic Surveys: AB1700CSA01 | Annual Business Survey: Statistics for Employer Firms by Industry, Sex, Ethnicity, Race, and Veteran Status for the U.S., States, Metro Areas, Counties, and Places: 2017 (ECNSVY Annual Business Survey Company Summary) [Dataset]. https://data.census.gov/table/ABSCS2017.AB1700CSA01?q=avoca
    Explore at:
    Dataset updated
    May 19, 2020
    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
    2017
    Area covered
    United States
    Description

    Release Date: 2020-05-19.The Census Bureau has reviewed this data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applied (Approval ID: CBDRB-FY20-008)...Release Schedule:.Data in this file come from estimates of business ownership by sex, ethnicity, race, and veteran status from the 2018 Annual Business Survey (ABS) collection. Data are also obtained from administrative records, the 2017 Economic Census and other economic surveys...Note: The collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2018 ABS collection year produces statistics for the 2017 reference year. The "Year" column in the table is the reference year. The ABS has a larger sample size during the benchmark year of 2017. Due to the larger size, more detailed data are shown for reference year 2017...For more information about ABS planned data product releases, see Tentative ABS Schedule...Key Table Information:.Includes U.S. firms with paid employees, operating during the reference year 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. Employer 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. Employment reflects the number of paid employees during the pay period in the reference year that included March 12...Data Items and Other Identifying Records:.Data include estimates on:.Number of employer firms (firms with paid employees). Sales and receipts of employer firms (reported in $1,000s of dollars). Number of employees (during the March 12 pay period). Annual payroll (reported in $1,000s of dollars)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female. . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority. Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran. Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...Moreover, the 2017 reference year statistics include detailed race and ethnicity data tabulated for:.Hispanic subgroups. Mexican, Mexican American, Chicano. Puerto Rican. Cuban. Other Hispanic, Latino, or Spanish. . Asian subgroups. Asian Indian. Chinese. Filipino. Japanese. Korean. Vietnamese. Other Asian. . Native Hawaiian and Other Pacific Islander subgroups. Native Hawaiian. Guamanian or Chamorro. Samoan. Other Pacific Islander. ...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for businesses owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans. Firms not classifiable by sex, ethnicity, race, and veteran status are counted and tabulated separately.. The detail may not add to the total or subgroup total because a Hispanic or Latino firm may be of any race, and because a firm could be tabulated in more than one racial group. For example, if a firm responded as both Chinese and Black majority owned, the firm would be included in the detailed Asian and Black estimates but would only be counted once toward the higher level all firms' estimates.. References such as "Mexican-owned," "Puerto Rican-owned," "Cuban-owned" or "other Hispanic- or Latino-owned" businesses refer only to businesses operating in the 50 states and the District of Columbia that self-identified 51 percent or more of their ownership in 2017 to be by individuals of Mexican, Puerto Rican, Cuban or other Hispanic or Latino origin. The ABS does not distinguish between U.S. residents and nonresidents. Companies owned by foreign governments or owned by other companies, foreign or domestic, are included in the category "Unclassifiable."...Industry and Geogr...

  20. e

    ACS Race and Hispanic Origin Variables - Centroids

    • coronavirus-resources.esri.com
    • mapdirect-fdep.opendata.arcgis.com
    • +3more
    Updated Oct 22, 2018
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Esri (2018). ACS Race and Hispanic Origin Variables - Centroids [Dataset]. https://coronavirus-resources.esri.com/maps/e6d218a8ba764a939c2add5c081beef9
    Explore at:
    Dataset updated
    Oct 22, 2018
    Dataset authored and provided by
    Esri
    Area covered
    Description

    This layer shows population broken down by race and Hispanic origin. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the predominant race living within an area, and the total population in that area. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B03002Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census: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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations: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.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.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Urban Observatory by Esri (2020). What is the most common race/ethnicity? [Dataset]. https://hub.arcgis.com/maps/2603a03fc55244c19f7f73d04cd53cea
Organization logo

What is the most common race/ethnicity?

Explore at:
Dataset updated
Apr 14, 2020
Dataset provided by
Esrihttp://esri.com/
Authors
Urban Observatory by Esri
Area covered
Description

Knowing the racial and ethnic composition of a community is often one of the first steps in understanding, serving, and advocating for various groups. This information can help enforce laws, policies, and regulations against discrimination based on race and ethnicity. These statistics can also help tailor services to accommodate cultural differences.This multi-scale map shows the most common race/ethnicity living within an area. Map opens at tract-level in Los Angeles, CA but has national coverage. Zoom out to see counties and states.This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available. The data on race were derived from answers to the question on race that was asked of individuals in the United States. The Census Bureau collects racial data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically. The categories represent a social-political construct designed for collecting data on the race and ethnicity of broad population groups in this country, and are not anthropologically or scientifically based. Learn more here.

Search
Clear search
Close search
Google apps
Main menu