56 datasets found
  1. d

    CT DPH COVID -19 Race and Ethnicity Data Summary

    • catalog.data.gov
    • data.ct.gov
    Updated Jul 24, 2023
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    data.ct.gov (2023). CT DPH COVID -19 Race and Ethnicity Data Summary [Dataset]. https://catalog.data.gov/dataset/ct-dph-covid-19-race-and-ethnicity-data-summary
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    Dataset updated
    Jul 24, 2023
    Dataset provided by
    data.ct.gov
    Area covered
    Connecticut
    Description

    This report summarizes data on COVID-19 cases and COVID-19 associated deaths by race/ethnicity for the state of Connecticut and the 10 largest Connecticut towns. Data on race/ethnicity are missing on almost half (47%) of reported COVID-19 cases. CT DPH has urged healthcare providers and laboratories to complete information on race/ethnicity for all COVID-19 cases. All data in this report are preliminary; data will be updated as new COVID-19 case reports are received and data errors are corrected. Data on COVID-19 cases and COVID-19-associated deaths were last updated on April 20, 2020 at 3 PM. Information about race and ethnicity are collected on the Connecticut Department of Public Health (DPH) COVID-19 case report form, which is completed by healthcare providers for laboratory-confirmed COVID-19 cases. Information about the race/ethnicity of COVID-19-associated deaths also are collected by the Connecticut Office of the Chief Medical Examiner and shared with DPH. Race/ethnicity categories used in this report are mutually exclusive. People answering ‘yes’ to more than one race category are counted as ‘other’.

  2. d

    AmeriCorps Members Demographic

    • catalog-dev.data.gov
    • data.americorps.gov
    • +1more
    Updated Mar 20, 2025
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    CNCS (2025). AmeriCorps Members Demographic [Dataset]. https://catalog-dev.data.gov/dataset/americorps-members-demographic-7eccb
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    Dataset updated
    Mar 20, 2025
    Dataset provided by
    CNCS
    Description

    The data is prepared using AmeriCorps members who began service on any day in fiscal year (FY) 2017. The members may have served 1 to 365 days during their term. Members who are in never served, disqualified, pre-service, or deferred statuses were excluded from this analysis. AmeriCorps VISTA and AmeriCorps NCCC race and ethnicity data come from the member application to serve. The code to extract the data between the two programs is the same. The ASN race and ethnicity data comes from the enrollment form. The enrollment form may exist multiple times if the member enrolled in more than one term. It is not uncommon for each enrollment form to have conflicting information about the member’s race and ethnicity. The member may have enrollment form data for terms served outside of the timeframe of the dataset. For example, if we are reporting on members who began service in FY17, then a member who also served in FY16 may have race and ethnicity information in the FY16 enrollment form and no race or ethnicity information or conflicting information in the FY17 enrollment form. In the case of conflicting information, this analysis assumes each instance of race designation is correct. If a member reports themselves as “Asian or Asian American” in one enrollment form and “White” in another enrollment form, then the analysis categorizes this person as someone who identifies with multiple race selections vs. one or the other. In the case of ethnicity, if a member indicates that they are not Hispanic or Latino/a in one form, but that they are in another, this analysis assumes the affirmative—and they will be categorized as Hispanic or Latino/a. Lastly, the totals include the total results from the query plus the difference between the query and the raw count of members who started service in that fiscal year. The members who did not have a record in the invite table and enrollment table were added to the non-response category. Senior Corps Figures come from the Annual Progress Report Supplement as of April 11, 2018. Percentages are calculated from totals of the subcategories, excluding the non-response categories.

  3. 2018 Economic Surveys: AB1800NESD03 | Nonemployer Statistics by Demographics...

    • data.census.gov
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    ECN, 2018 Economic Surveys: AB1800NESD03 | Nonemployer Statistics by Demographics series (NES-D): Legal Form of Organization Statistics for Nonemployer Firms by Sector, Sex, Ethnicity, Race, Veteran Status for the U.S., States, and Metro Areas: 2018 (ECNSVY Nonemployer Statistics by Demographics Company Summary) [Dataset]. https://data.census.gov/cedsci/table?q=ab1800%2A&n=62&tid=ABSNESD2018.AB1800NESD03
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    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

    Release Date: 2021-12-16.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-FY22-032)...Key Table Information:.Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series)...Data Items and Other Identifying Records:.Data include estimates on:.Number of nonemployer firms (firms without paid employees). Sales and receipts of nonemployer firms (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). ...The data are also shown by the following legal form of organization (LFO) categories:. S-Corporations. C-Corporations. Individual proprietorships. Partnerships...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for firms 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 subtotal because a Hispanic firm may be of any race; because a firm could be tabulated in more than one racial group; or because the number of nonemployer firm's data are rounded....Industry and Geography Coverage:.Data are shown for the total for all sectors (00) and the 2-digit NAICS codes levels for the U.S., states, and metro areas. Data are excluded for the following NAICS industries:.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). Management of Companies and Enterprises (NAICS 55). Private Households (NAICS 814). Public Administration (NAICS 92). Industries Not Classified (NAICS 99)...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...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/abs/data/2018/AB1800NESD03.zip...API Information:.Nonemployer Demographic Statistics data are housed in the Census Bureau API. For more information, see https://api.census.gov/data/2018/absnesd.html...Symbols:. D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals. S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.. N - Not available or not comparable. X - Not applicable..The following symbols are used to identify the level of noise applied to the data:. G - Low noise: The cell value was changed by less than 2 percent by the application of noise.. H - Moderate noise: The cell value was changed by 2 percent or more but less than 5 percent by the application of noise.. J - High noise: The cell value was changed by 5 percent or more by the application of noise..For a complete list of all economic programs symbols, see the Symbols Glossary...Source:.U.S. Census Bureau, Nonemployer Statistics by Demographics, Annual Business Survey Program.For more information about the survey, please visit https://www.census.gov/programs-s...

  4. Census of Population and Housing, 2000: Summary File 1, New York

    • archive.ciser.cornell.edu
    • search.datacite.org
    Updated Jan 6, 2020
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    Bureau of the Census (2020). Census of Population and Housing, 2000: Summary File 1, New York [Dataset]. http://doi.org/10.6077/bk42-1782
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    Dataset updated
    Jan 6, 2020
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    Bureau of the Census
    Area covered
    New York
    Variables measured
    HousingUnit, Individual
    Description

    Summary File 1 contains 100-percent United States decennial Census data, which is the information compiled from the questions asked of all people and about every housing unit. Population items include sex, age, race, Hispanic or Latino origin, household relationship, and group quarters occupancy. Housing items include occupancy status, vacancy status, and tenure (owner occupied or renter occupied). There are a total of 171 population tables ("P") and 56 housing tables ("H") provided down to the block level, and 59 population tables provided down to the census tract level ("PCT") for a total of 286 tables. In addition, 14 population tables and 4 housing tables at the block level and 4 population tables at the census tract level are repeated by major race and Hispanic or Latino groups. The data present population and housing characteristics for the total population, population totals for an extensive list of race (American Indian and Alaska Native tribes, Asian, Native Hawaiian, and Other Pacific Islander) and Hispanic or Latino groups, and population and housing characteristics for a limited list of race and Hispanic or Latino groups. Population and housing items may be crosstabulated. Selected aggregates and medians also are provided. Summary File 1 is released in the form of individual files for each of the 50 states, the District of Columbia, and Puerto Rico. (Source: downloaded from ICPSR 7/13/10)

    Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR03194.v2. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

  5. Census of Population and Housing, 1990: Modified Age/Race, Sex and Hispanic...

    • archive.ciser.cornell.edu
    Updated Jan 1, 2020
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    Bureau of the Census (2020). Census of Population and Housing, 1990: Modified Age/Race, Sex and Hispanic Origin (MARS) File (STF-S-2B) [Dataset]. http://doi.org/10.6077/j5/o8guds
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    Dataset updated
    Jan 1, 2020
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    Bureau of the Census
    Variables measured
    Individual
    Description

    The MARS file contains modified race and age data based on the 1990 Census. Both race and age are tabulated by sex and Hispanic origin for several layers of geography. The race data were modified to make reporting categories comparable to those used by state and local agencies. The 1990 Census included 9,804,847 persons who checked the "other race" category and were therefore not included in one of the 15 racial categories listed on the Census form. "Other race" is usually not an acceptable reporting category for state and local agencies. Therefore, the Census Bureau assigned each "other race" person to the specified race reported by another person geographically close with an identical response to the Hispanic-origin question. Hispanic origin was taken into account because over 95 percent of the "other race" persons were of Hispanic origin. (Hispanic-origin persons may be of any race.) The assignment of race to Hispanic-origin persons did not affect the Hispanic-origin category that they checked (i.e, Mexican, Puerto Rican, Cuban, etc.). Age data were modified because respondents tended to report age as of the date they completed the 1990 questionnaire, instead of age as of the April 1, 1990 Census date. In addition, there may have been a tendency for respondents to round up their age if they were close to having a birthday. Age data for individuals in households were modified by adjusting the reported birth-year data by race and sex for each of the 1990 Census's 449 district offices to correspond with the national level quarterly distribution of births available from the National Center for Health Statistics. The data for persons in group quarters were adjusted similarly, but on a state basis. The age adjustment affects approximately 100 million people. In this file their adjusted age is one year different from that reported in the 1990 Census. STF-S-2B only contains data for 12 states, their counties, and Minor Civil Divisions (MCDs). (Source: ICPSR, retrieved 06/15/2011)

  6. U.S. distribution of race and ethnicity among the military 2019

    • statista.com
    Updated Jan 24, 2025
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    Statista (2025). U.S. distribution of race and ethnicity among the military 2019 [Dataset]. https://www.statista.com/statistics/214869/share-of-active-duty-enlisted-women-and-men-in-the-us-military/
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    Dataset updated
    Jan 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the fiscal year of 2019, 21.39 percent of active-duty enlisted women were of Hispanic origin. The total number of active duty military personnel in 2019 amounted to 1.3 million people.

    Ethnicities in the United States The United States is known around the world for the diversity of its population. The Census recognizes six different racial and ethnic categories: White American, Native American and Alaska Native, Asian American, Black or African American, Native Hawaiian and Other Pacific Islander. People of Hispanic or Latino origin are classified as a racially diverse ethnicity.

    The largest part of the population, about 61.3 percent, is composed of White Americans. The largest minority in the country are Hispanics with a share of 17.8 percent of the population, followed by Black or African Americans with 13.3 percent. Life in the U.S. and ethnicity However, life in the United States seems to be rather different depending on the race or ethnicity that you belong to. For instance: In 2019, native Hawaiians and other Pacific Islanders had the highest birth rate of 58 per 1,000 women, while the birth rae of white alone, non Hispanic women was 49 children per 1,000 women.

    The Black population living in the United States has the highest poverty rate with of all Census races and ethnicities in the United States. About 19.5 percent of the Black population was living with an income lower than the 2020 poverty threshold. The Asian population has the smallest poverty rate in the United States, with about 8.1 percent living in poverty.

    The median annual family income in the United States in 2020 earned by Black families was about 57,476 U.S. dollars, while the average family income earned by the Asian population was about 109,448 U.S. dollars. This is more than 25,000 U.S. dollars higher than the U.S. average family income, which was 84,008 U.S. dollars.

  7. 2019 Economic Surveys: AB1900NESD03 | Nonemployer Statistics by Demographics...

    • data.census.gov
    Updated May 11, 2023
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    ECN (2023). 2019 Economic Surveys: AB1900NESD03 | Nonemployer Statistics by Demographics series (NES-D): Legal Form of Organization Statistics for Nonemployer Firms by Sector, Sex, Ethnicity, Race, Veteran Status for the U.S., States, and Metro Areas: 2019 (ECNSVY Nonemployer Statistics by Demographics Company Summary) [Dataset]. https://data.census.gov/table/ABSNESD2019.AB1900NESD03?q=Construction+Data+Inc
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    Dataset updated
    May 11, 2023
    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
    2019
    Area covered
    United States
    Description

    Release Date: 2023-05-11.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY23-0262)...Key Table Information:.Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series)...Data Items and Other Identifying Records:.Data include estimates on:.Number of nonemployer firms (firms without paid employees). Sales and receipts of nonemployer firms (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). ...The data are also shown by the following legal form of organization (LFO) categories:. S-Corporations. C-Corporations. Individual proprietorships. Partnerships...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for firms 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 subtotal because a Hispanic firm may be of any race; because a firm could be tabulated in more than one racial group; or because the number of nonemployer firm's data are rounded.. For C-corporations, there is no tax form or business registry that clearly and unequivocally identifies all owners of this type of business. For this reason, the Census Bureau is unable to assign demographic characteristics for C-corporations. Data for C-corporations are included in the published tables but are not shown by the demographic characteristics of the firms....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-digit NAICS code for:..United States...Data are excluded for the following NAICS industries:.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). Management of Companies and Enterprises (NAICS 55). Private Households (NAICS 814). Public Administration (NAICS 92). Industries Not Classified (NAICS 99)...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...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/abs/data/2019/AB1900NESD03.zip...API Information:.Nonemployer Demographic Statistics data are housed in the Census Bureau API. For more information, see https://api.census.gov/data/2019/absnesd.html...Symbols:. D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals. S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.. N - Not available or not comparable. X - Not applicable..The following symbols are used to identify the level of noise applied to the data:. G - Low noise: The cell valu...

  8. A

    ‘MD COVID-19 - Probable Deaths by Race and Ethnicity Distribution’ analyzed...

    • analyst-2.ai
    Updated May 9, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘MD COVID-19 - Probable Deaths by Race and Ethnicity Distribution’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-md-covid-19-probable-deaths-by-race-and-ethnicity-distribution-79d7/latest
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    Dataset updated
    May 9, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘MD COVID-19 - Probable Deaths by Race and Ethnicity Distribution’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/a77a9f86-8e6e-4887-bf3b-049d05165911 on 27 January 2022.

    --- Dataset description provided by original source is as follows ---

    Summary The cumulative number of probable COVID-19 deaths among Maryland residents by race and ethnicity: African American; White; Hispanic; Asian; Other; Unknown.

    Description The MD COVID-19 - Probable Deaths by Race and Ethnicity Distribution data layer is a collection of the statewide confirmed and probable COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by categories of race and ethnicity. A death is classified as probable if the person's death certificate notes COVID-19 to be a probable, suspect or presumed cause or condition. Probable deaths are not yet been confirmed by a laboratory test. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Confirmed deaths are available from the MD COVID-19 - Confirmed Deaths by Race and Ethnicity Distribution data layer.

    Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

    --- Original source retains full ownership of the source dataset ---

  9. d

    MD COVID-19 - Confirmed Deaths by Race and Ethnicity Distribution

    • catalog.data.gov
    • opendata.maryland.gov
    • +2more
    Updated Jun 21, 2025
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    opendata.maryland.gov (2025). MD COVID-19 - Confirmed Deaths by Race and Ethnicity Distribution [Dataset]. https://catalog.data.gov/dataset/md-covid-19-confirmed-deaths-by-race-and-ethnicity-distribution
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    Dataset updated
    Jun 21, 2025
    Dataset provided by
    opendata.maryland.gov
    Area covered
    Maryland
    Description

    Note: Starting April 27, 2023 updates change from daily to weekly. Summary The cumulative number of confirmed COVID-19 deaths among Maryland residents by race and ethnicity: African American; White; Hispanic; Asian; Other; Unknown. Description The MD COVID-19 - Confirmed Deaths by Race and Ethnicity Distribution data layer is a collection of the statewide confirmed and probable COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by categories of race and ethnicity. A death is classified as confirmed if the person had a laboratory-confirmed positive COVID-19 test result. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Probable deaths are available from the MD COVID-19 - Probable Deaths by Race and Ethnicity Distribution data layer. Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

  10. Population of the U.S. by race 2000-2023

    • statista.com
    Updated Aug 20, 2024
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    Statista (2024). Population of the U.S. by race 2000-2023 [Dataset]. https://www.statista.com/statistics/183489/population-of-the-us-by-ethnicity-since-2000/
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    Dataset updated
    Aug 20, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 2000 - Jul 2023
    Area covered
    United States
    Description

    This graph shows the population of the U.S. by race and ethnic group from 2000 to 2023. In 2023, there were around 21.39 million people of Asian origin living in the United States. A ranking of the most spoken languages across the world can be accessed here. U.S. populationCurrently, the white population makes up the vast majority of the United States’ population, accounting for some 252.07 million people in 2023. This ethnicity group contributes to the highest share of the population in every region, but is especially noticeable in the Midwestern region. The Black or African American resident population totaled 45.76 million people in the same year. The overall population in the United States is expected to increase annually from 2022, with the 320.92 million people in 2015 expected to rise to 341.69 million people by 2027. Thus, population densities have also increased, totaling 36.3 inhabitants per square kilometer as of 2021. Despite being one of the most populous countries in the world, following China and India, the United States is not even among the top 150 most densely populated countries due to its large land mass. Monaco is the most densely populated country in the world and has a population density of 24,621.5 inhabitants per square kilometer as of 2021. As population numbers in the U.S. continues to grow, the Hispanic population has also seen a similar trend from 35.7 million inhabitants in the country in 2000 to some 62.65 million inhabitants in 2021. This growing population group is a significant source of population growth in the country due to both high immigration and birth rates. The United States is one of the most racially diverse countries in the world.

  11. 2020 Economic Surveys: AB2000NESD04 | Nonemployer Statistics by Demographics...

    • data.census.gov
    Updated Feb 8, 2024
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    ECN (2024). 2020 Economic Surveys: AB2000NESD04 | Nonemployer Statistics by Demographics series (NES-D): Owner Characteristics of Nonemployer Firms by Industry, Sex, Ethnicity, Race, and Veteran Status for the U.S., States, and Metro Areas: 2020 (ECNSVY Nonemployer Statistics by Demographics Characteristics of Business Owners) [Dataset]. https://data.census.gov/table/ABSNESDO2020.AB2000NESD04?q=D+W+SVC+CO
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    Dataset updated
    Feb 8, 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
    2020
    Area covered
    United States
    Description

    Release Date: 2024-02-08.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (2020 NES-D Project No. 7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0051)...Key Table Information:.Includes owner-level data for U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series)...Data Items and Other Identifying Records:.Data include estimates on:.Number of owners of nonemployer firms. Percent of number of owners of nonemployer firms (%)...These data are aggregated at the owner level by the following demographic classifications:.All owners of nonemployer firms. Sex. Female. Male. . . Ethnicity. 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). Nonminority (Firms classified as non-Hispanic and White). . . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Nonveteran. . . ...Data Notes:.. Data are tabulated at the owner level.. An owner can be tabulated in more than one race group.. An owner cannot be tabulated with two mutually exclusive demographic classifications (e.g., both as a veteran and a nonveteran).. An individual can own more than one firm....Owner Characteristics:.Using administrative records, owner characteristics were assigned for the following categories:. Place of Birth (USBORN). Owner was born in the U.S.. Owner was born outside the U.S.. . U.S. Citizenship (USCITIZEN). Owner is a citizen of the U.S.. Owner is not a citizen of the U.S.. . Owner Age (OWNRAGE). Under 25. 25 to 34. 35 to 44. 45 to 54. 55 to 64. 65 or over. . . .Question Description codes for the topics are in parenthesis. ..Industry and Geography Coverage:.The data are shown for the total for all sectors (00) NAICS code level for:..United States. States and the District of Columbia. Metropolitan Statistical Areas...The data are also shown for the 2-, 3-, and 4-digit NAICS code level for the United States only...Data are excluded for the following NAICS industries:.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). Management of Companies and Enterprises (NAICS 55). Private Households (NAICS 814). Public Administration (NAICS 92). Industries Not Classified (NAICS 99)...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...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/abs/data/2020/AB2000NESD04.zip...API Information:.Nonemployer Demographic Statistics data are housed in the Census Bureau API. For more information, see https://api.census.gov/data/2020/absnesdo.html...Symbols:. D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals. S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.. N - Not available or not comparable. X - Not applicable.For a complete list of all economic programs symbols, see the Symbols Glossary...Source:.U.S. Census Bureau, Nonemployer Statistics by Demographics, Annual Business Survey Program.For more information about the survey, please visit https://www.census.gov/programs-surveys/abs.html...Contact Information:.To contact the Annual Business Survey Program staff:.Email general, nonsecure, and unencrypted messages to adep.annual.business.survey@census.gov.. Call 301.763.3316 between 7 a.m. and 5 p.m. (EST), Monday through Friday...

  12. Justice40 in Context: Percent Black or African American (alone or in...

    • atlas-connecteddmv.hub.arcgis.com
    Updated Jun 10, 2022
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    Esri (2022). Justice40 in Context: Percent Black or African American (alone or in combination) - Census 2020 [Dataset]. https://atlas-connecteddmv.hub.arcgis.com/maps/d955d4ee792a4380b5e90efdf6a76754
    Explore at:
    Dataset updated
    Jun 10, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This map shows the percentage of Black or African American population, alone or in combination with any other race and independent of ethnicity, throughout the US according to the 2020 decennial Census. The people represented in this map chose "Black or African American" alone or in combination with another race in the survey (see the Census form here).For more information about the racial categories included on the 2020 Census, visit this resource from the U.S. Census Bureau. The pattern is shown by states, counties, tracts, block groups, and blocks. Zoom or search for anywhere in the US to see a local pattern. Click on an area to learn more. Filter to your area and save a new version of the map to use for your own mapping purposes.The data is from the decennial 2020 Census, and is sourced by the U.S. Census Bureau for all states plus D.C. and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables. For full metadata including data processing notes, visit this group of ArcGIS Living Atlas layers.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteAdditional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

  13. s

    Data from: Employment by occupation

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

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

    Area covered
    United Kingdom
    Description

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

  14. d

    Correlates of Health Behaviors and Outcomes among U.S. Latinx Adults

    • search.dataone.org
    • dataverse.harvard.edu
    • +1more
    Updated Nov 22, 2023
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    Budd, Elizabeth (2023). Correlates of Health Behaviors and Outcomes among U.S. Latinx Adults [Dataset]. http://doi.org/10.7910/DVN/NABLZX
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    Dataset updated
    Nov 22, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Budd, Elizabeth
    Description

    In January 2018, 798 Hispanic/Latino adults living in the United States were recruited through Qualtrics Panels to complete a survey in English or Spanish. Respondents were diverse in their nativity (e.g., 52% Mexican or Mexican American; 17% Puerto Rican; 8.5% Cuban). The survey included the following measures: -Demographic and Health Information – Demographic and Health Data Questionnaire (DHDQ). This researcher-constructed questionnaire is designed to obtain participant information such as: (a) race/ethnicity, (b) age, (c) gender, (d) sexual orientation, (e) relationship status, (f) household income, (g) generational status, (h) education level, (i) presence of chronic health conditions, (j) self-reported height and weight, (k) overall health status, (l) native language and proficient language(s), (m) number of health care visits in the past year, and (n) perceived weight. -Media and Technology Usage and Attitudes Scale (MTUAS). The Media and Technology Usage and Attitudes Scale is a 60-item scale used to measure the frequency of use from specific forms of media and attitudes toward technology (Rosen, Whaling, Carrier, Cheever, & Rokkum, 2013). The scale consists of eleven media usage subscales and four attitude subscales. For the purposes of this study, only the smartphone usage subscale will be included (9 items). Prompts assessing the frequency of technology use stated: “Please indicate how often you do each of the following…” and asked about smartphone usage habits on a scale from 1(Never) to 10 (All the time). Higher scores are indicative of more technology use. The MTUAS was found to show sufficient proof of reliability for smartphone usage subscale (α = .93). Validity has also been shown through comparisons with measures of daily media usage hours, technology-related anxiety, and the Internet Addiction Test (Rosen et al., 2013). -The Sedentary Behavior Questionnaire (SBQ). The Sedentary Behavior Questionnaire is an 18-item scale designed to assess nine different sedentary behaviors including the use of technological devices, hobbies, and sitting due to transportation and work (Rosenberg et al., 2010). The measure is designed to assess sedentary behaviors over weekdays as well as the weekend and then are multiplied to estimate the sum amounts of sedentary hours during a week/weekend. The scale consisted of nine items with answer choices ranging from 1 (None) to 9 (6 hours or more). The current study will slightly alter the SBQ as some of the items may be dated in regards to the technology. An example is “sitting listening to music on the radio, tapes, or CDs.” The examples used in the items will be reflective of sedentary forms of technology used nowadays. The SBQ has been found to be a reliable measure for sedentary behaviors as intraclass correlation coefficients found that the items were sufficient for both weekday (.64-.90) and weekends (.51-.93). Validity of the measure was also sufficient as partial correlations were used to compare the self-reported ratings of the SBQ to accelerometer measures of activity. The study also found that in comparison to the International Physical Activity Questionnaire and body mass index, there were significant correlations with both male and female samples (Rosenberg et al., 2010). -PHQ-9- English: The Patient Health Questionnaire (PHQ-9). The PHQ-9 is a 9-item instrument that measures depressive symptoms (Kroenke, Spitzer, & Williams, 2001). Instructions on the PHQ-9 are as follows: “Over the last 2 weeks, how often have you been bothered by any of the following problems?” The assessment uses a 4-point Likert-type scale with responses ranging from 0 (not at all) to 3 (nearly every day). Scores for PHQ-9 scale are determined by assigning a score to each response ranging from 0 to 3 and then summing the responses. The PHQ-9 score can range from 0 to 27. Higher scores on the measure indicate higher levels of depressive symptoms. -Health Promoting Behaviors – Health Promoting Lifestyle Profile II (HPLP-II). The HPLP-II is a 52-item inventory designed to measure engagement in behaviors that characterize a health-promoting lifestyle (Walker, Sechrist, Pender, 1995). The HPLPII is comprised of a scale and six subscales, which include Spiritual Growth, Interpersonal Relations, Nutrition, Physical Activity, Health Responsibility, and Stress Management. Only the Nutrition (9 items) and Physical Activity (8 items) subscales will be used for the current study. Instructions on the HPLP-II are to indicate level of engagement in each listed behavior using a Likert-type scale, with responses ranging from 1 (never) to 4 (routinely). Scores for the HPLP-II scale and subscale are determined by calculating means for each. Higher scores on the scale and subscales indicate higher levels of engagement in the assessed health promoti... Visit https://dataone.org/datasets/sha256%3A947312a2e719300f2006c0c8f48294d38a5b6a63ad0f31869ed48ea690048cde for complete metadata about this dataset.

  15. S

    2023 Census population change by ethnic group and territorial authority...

    • datafinder.stats.govt.nz
    csv, dwg, geodatabase +6
    + more versions
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    Stats NZ, 2023 Census population change by ethnic group and territorial authority local board [Dataset]. https://datafinder.stats.govt.nz/layer/117653-2023-census-population-change-by-ethnic-group-and-territorial-authority-local-board/
    Explore at:
    shapefile, kml, mapinfo tab, dwg, mapinfo mif, csv, geodatabase, geopackage / sqlite, pdfAvailable download formats
    Dataset provided by
    Statistics New Zealandhttp://www.stats.govt.nz/
    Authors
    Stats NZ
    License

    https://datafinder.stats.govt.nz/license/attribution-4-0-international/https://datafinder.stats.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    Dataset contains ethnic group census usually resident population counts from the 2013, 2018, and 2023 Censuses, as well as the percentage change in the ethnic group population count between the 2013 and 2018 Censuses, and between the 2018 and 2023 Censuses. Data is available by territorial authority and Auckland local board.

    The ethnic groups are:

    • European
    • Māori
    • Pacific peoples
    • Asian
    • Middle Eastern/Latin American/African
    • Other ethnicity.

    Map shows percentage change in the census usually resident population count for ethnic groups between the 2018 and 2023 Censuses.

    Download lookup file from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

    Footnotes

    Geographical boundaries

    Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

    Subnational census usually resident population

    The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.

    Caution using time series

    Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

    About the 2023 Census dataset

    For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

    Data quality

    The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

    Quality rating of a variable

    The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.

    Ethnicity concept quality rating

    Ethnicity is rated as high quality.

    Ethnicity – 2023 Census: Information by concept has more information, for example, definitions and data quality.

    Using data for good

    Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

    Confidentiality

    The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

    Symbol

    -998 Not applicable

    Percentages

    To calculate percentages, divide the figure for the category of interest by the figure for ‘Total stated’ where this applies.

  16. List of Opinion Pieces on Joacine Katar Moreira - 2nd half of 2019

    • figshare.com
    txt
    Updated Dec 12, 2022
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    Daniel Cardoso; Sónia Lamy (2022). List of Opinion Pieces on Joacine Katar Moreira - 2nd half of 2019 [Dataset]. http://doi.org/10.6084/m9.figshare.20481489.v1
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    txtAvailable download formats
    Dataset updated
    Dec 12, 2022
    Dataset provided by
    figshare
    Authors
    Daniel Cardoso; Sónia Lamy
    License

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

    Description

    A list of the files and names of opinion pieces in the written portuguese press in the second half of 2019 that mention Joacine Katar Moreira by name, along with metadata about the authorship of those opinion pieces.

    For more details please see: https://jkm-project.ulusofona.pt/

  17. Office for Civil Rights School District File, 1970 [United States]: School...

    • icpsr.umich.edu
    ascii, sas, spss
    Updated Dec 9, 2002
    + more versions
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    United States Department of Education. Office for Civil Rights (2002). Office for Civil Rights School District File, 1970 [United States]: School Desegregation Database [Dataset]. http://doi.org/10.3886/ICPSR03530.v1
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    spss, sas, asciiAvailable download formats
    Dataset updated
    Dec 9, 2002
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States Department of Education. Office for Civil Rights
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/3530/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/3530/terms

    Time period covered
    1970 - 1971
    Area covered
    United States
    Description

    This file, part of a data collection effort carried out annually from 1968-1974 to look at issues of school desegregation, contains selected school district-level racial and ethnic data about students and staff for the academic year 1970-1971. The data were collected using OCR Form OS/CR 101. Each district record for each separate year of the series is identical, containing fields for all district data elements surveyed in every year. Where a particular item was not surveyed for a specific year, its corresponding field is zero (for numeric fields) or blank (for alphanumeric fields). Counts of students in various racial and ethnic groups are provided and then further categorized across additional dimensions, including whether resident or non-resident, emotionally disturbed, physically or learning disabled, or requiring special education. Other categories include school-age children in public and non-public schools or not in school, dropouts, and those expelled or suspended. Racial and ethnic counts of full-time classroom teachers and full-time instructional staff are also supplied. Other variables focus on the number of schools in the district that used ability grouping, whether a district had single-sex schools, whether students of different sexes were required to take different courses, the number of students whose language was not English, whether bilingual instruction was used, the number of schools being newly built or modified to increase capacity, the racial composition of new schools, and whether there was litigation.

  18. c

    Community Life Survey, 2013-2014: Special Licence Access

    • datacatalogue.cessda.eu
    • beta.ukdataservice.ac.uk
    Updated Nov 28, 2024
    + more versions
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    Cabinet Office (2024). Community Life Survey, 2013-2014: Special Licence Access [Dataset]. http://doi.org/10.5255/UKDA-SN-7561-2
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    Dataset updated
    Nov 28, 2024
    Authors
    Cabinet Office
    Time period covered
    Apr 30, 2013 - Mar 31, 2014
    Area covered
    England
    Variables measured
    Individuals, Families/households, National
    Measurement technique
    Face-to-face interview
    Description

    Abstract copyright UK Data Service and data collection copyright owner.

    The Community Life Survey was first commissioned by the Cabinet Office in 2012-2013. It is a household survey conducted in England, tracking the latest trends and developments across areas key to encouraging social action and empowering communities, including:
    • volunteering and charitable giving;
    • views about the local area;
    • community cohesion and belonging;
    • community empowerment and participation;
    • influencing local decisions and affairs; and
    • subjective well-being
    Up to 2015-16, the survey used a face-to-face methodology. Following thorough testing, the CLS moved to an online and paper mixed-method approach from 2016-17 onwards (a paper self-completion questionnaire being available as an alternative to the online survey), with an end to previous current face-to-face method. The objectives of the survey are to: The objectives of the survey are to:
    • provide robust, nationally representative data on behaviours and attitudes within communities to inform and direct policy and action in these areas;
    • to provide data of value to all users, including public bodies, external stakeholders and the public; and
    • underpin further research and debate on building stronger communities
    The Community Life Survey incorporates a small number of priority measures from the Citizenship Survey, which ran from 2001-2011, conducted by the Department for Communities and Local Government. These measures were incorporated in the Community Life Survey so that trends in these issues could continue to be tracked over time. (The full Citizenship Survey series is held at the UK Data Archive under GNs 33347 and 33474.)

    Further information may be found on the gov.uk Community Life Survey website.


    The 2013-2014 survey covers May 2013 to April 2014 and forms 'Official Statistics', meaning that it meets the high standards of quality set out by the Code of Practice for Official Statistics.

    End User Licence and Special Licence data
    Users should note that there are two versions of each Community Life Survey dataset. One is available under the standard End User Licence (EUL) agreement, and the other is a Special Licence (SL) version. The SL version contains more detailed variables relating to: social class; ethnicity; religion; sexual identity and lower level geographical classifications (see Main Topics section for details).

    The SL data have more restrictive access conditions than those made available under the standard EUL. Prospective users of the SL version will need to complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables in order to get permission to use that version. Therefore, users are strongly advised to order the standard version of the data.

    The standard EUL version of the Community Life Survey, 2012-2013 dataset is held under SN 7560.

    For the second edition (December 2014) a new version of the data file was deposited, with variables PSU and stratum included, to allow users to calculate standard errors.

    Main Topics:

    The main topics include: identity and social networks, local community, civic engagement, volunteering, social action, subjective well-being and basic demographics.
    The Community Life Survey, 2013-2014: Special Licence Access data file includes the following extra variables:
    • SOC2010 (SOC2010)
    • SOC2010 Sub-Major Group (SOC10smg)
    • Ethnic group: 6 categories (Ethnic6)
    • Ethnic group: 11 categories (Ethnic11a)
    • Respondents Ethnic origin and age (excludes Mixed/Other) (Rethage9a)
    • Sex within Ethnicity: 11 categories (E11sex1)
    • Sex within Ethnicity: 10 categories (E5sex1)
    • Whether practising for each religion (Actrel)
    • Respondent religion: 7 categories (Jewish included in other)(Relig7)
    • Practice status for each religion (Relstat)
    • Ethno-Religious groups: 11 categories (E11Relig1)
    • Respondent sexual identity: 3 categories (Sid2)
    • ONS Ward Classification : Subgroup (2001 Wards) (Wrdsubgpg)
    • ONS District Level Classification: Subgroup (2003) (Ladsubgpg)
    • Output Area Classification : Subgroup (52 categories) (Oasubgrp)
    • Rural and Urban Area Classification 2004 (Rural)
    • PSU Code (PSU)
    • Sample stratum (FinalStratum)

  19. s

    Further education participation

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Jun 12, 2025
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    Race Disparity Unit (2025). Further education participation [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/education-skills-and-training/a-levels-apprenticeships-further-education/further-education-participation/latest
    Explore at:
    csv(39 KB)Available download formats
    Dataset updated
    Jun 12, 2025
    Dataset authored and provided by
    Race Disparity Unit
    License

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

    Area covered
    England
    Description

    In the 10 years to July 2024, the percentage of further education students who were from Asian, Black, Mixed and Other ethnic backgrounds went up from 19.7% to 27.9%.

  20. 2022 Economic Surveys: AB2200NESD03 | Nonemployer Statistics by Demographics...

    • data.census.gov
    Updated May 8, 2025
    + more versions
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    ECN (2025). 2022 Economic Surveys: AB2200NESD03 | Nonemployer Statistics by Demographics series (NES-D): Legal Form of Organization Statistics for Nonemployer Firms by Industry, Sex, Ethnicity, Race, and Veteran Status for the U.S., States, Metro Areas, and Counties: 2022 (ECNSVY Nonemployer Statistics by Demographics Company Summary) [Dataset]. https://data.census.gov/table/ABSNESD2022.AB2200NESD03?q=Baker+Gary+D
    Explore at:
    Dataset updated
    May 8, 2025
    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.Nonemployer Statistics by Demographics series (NES-D): Legal Form of Organization Statistics for Nonemployer Firms by Industry, Sex, Ethnicity, Race, and Veteran Status for the U.S., States, Metro Areas, and Counties: 2022.Table ID.ABSNESD2022.AB2200NESD03.Survey/Program.Economic Surveys.Year.2022.Dataset.ECNSVY Nonemployer Statistics by Demographics Company Summary.Source.U.S. Census Bureau, 2022 Economic Surveys, Nonemployer Statistics by Demographics.Release Date.2025-05-08.Release Schedule.The Nonemployer Statistics by Demographics (NES-D) is released yearly, beginning in 2017..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Table Universe.Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series).Data are also obtained from administrative records, the 2022 Economic Census, and other economic surveys..Methodology.Data Items and Other Identifying Records.Number of nonemployer firmsSales, value of shipments, or revenue of nonemployer firms ($1,000)These data are aggregated by sex, ethnicity, race, and veteran status when classifiable.The data are also shown by the following legal form of organization (LFO) categories: S-Corporations C-Corporations Individual proprietorships Partnerships 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 NES-D and the ABS are 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 2022 data are shown for the total of all sectors (00) and the 2-digit NAICS code levels for:United StatesStates and the District of ColumbiaIn addition, the total of all sectors (00) NAICS is shown for:Metropolitan Statistical AreasMicropolitan Statistical AreasCountiesFor information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00"), and at the 2-digit NAICS code levels depending on geography. 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.NES-D nonemployer data are not conducted through sampling. Nonemployer Statistics (NES) data originate from statistical information obtained through business income tax records that the Internal Revenue Service (IRS) provides to the Census Bureau. The NES-D adds demographic characteristics to the NES data and produces the total firm counts and the total receipts by those demographic characteristics. The NES-D utilizes various administrative records (AR) and the Census Bureau data sources that include the Business Register (BR), Internal Revenue Service (IRS) tax Form 1040 data, tax Schedule K-1 data, Decennial Census and American Community Survey (ACS) data, Social Security Administration's database (Numident), and AR from the Department of Veterans Affairs (VA).For more information, see Nonemployer Statistics by Demographics 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-FY25-0195).This dataset contains both nonemployer and employer data.For the nonemployer data, the NES-D uses noise infusion as the primary method of disclosure avoidance for receipts, and In certain circumstances, some individual cells may be suppressed for additional disclosure avoidance. More information on nonemployer firm disclosure avoidance is available in the Nonemployer Statistics by Demographics Methodology.For the employer data, 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 employer firm disclosure avoidance is available in the Annual Business Survey Methodology..Te...

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data.ct.gov (2023). CT DPH COVID -19 Race and Ethnicity Data Summary [Dataset]. https://catalog.data.gov/dataset/ct-dph-covid-19-race-and-ethnicity-data-summary

CT DPH COVID -19 Race and Ethnicity Data Summary

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Dataset updated
Jul 24, 2023
Dataset provided by
data.ct.gov
Area covered
Connecticut
Description

This report summarizes data on COVID-19 cases and COVID-19 associated deaths by race/ethnicity for the state of Connecticut and the 10 largest Connecticut towns. Data on race/ethnicity are missing on almost half (47%) of reported COVID-19 cases. CT DPH has urged healthcare providers and laboratories to complete information on race/ethnicity for all COVID-19 cases. All data in this report are preliminary; data will be updated as new COVID-19 case reports are received and data errors are corrected. Data on COVID-19 cases and COVID-19-associated deaths were last updated on April 20, 2020 at 3 PM. Information about race and ethnicity are collected on the Connecticut Department of Public Health (DPH) COVID-19 case report form, which is completed by healthcare providers for laboratory-confirmed COVID-19 cases. Information about the race/ethnicity of COVID-19-associated deaths also are collected by the Connecticut Office of the Chief Medical Examiner and shared with DPH. Race/ethnicity categories used in this report are mutually exclusive. People answering ‘yes’ to more than one race category are counted as ‘other’.

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