26 datasets found
  1. u

    Evidence for Equality National Survey: a Survey of Ethnic Minorities During...

    • beta.ukdataservice.ac.uk
    Updated 2024
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    N. Finney; J. Nazroo; N. Shlomo; D. Kapadia; L. Becares; B. Byrne (2024). Evidence for Equality National Survey: a Survey of Ethnic Minorities During the COVID-19 Pandemic, 2021 [Dataset]. http://doi.org/10.5255/ukda-sn-9116-1
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    Dataset updated
    2024
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    datacite
    Authors
    N. Finney; J. Nazroo; N. Shlomo; D. Kapadia; L. Becares; B. Byrne
    Description
    The Centre on the Dynamics of Ethnicity (CoDE), led by the University of Manchester with the Universities of St Andrews, Sussex, Glasgow, Edinburgh, LSE, Goldsmiths, King's College London and Manchester Metropolitan University, designed and carried out the Evidence for Equality National Survey (EVENS), with Ipsos as the survey partner. EVENS documents the lives of ethnic and religious minorities in Britain during the coronavirus pandemic and is, to date, the largest and most comprehensive survey to do so.

    EVENS used online and telephone survey modes, multiple languages, and a suite of recruitment strategies to reach the target audience. Words of Colour coordinated the recruitment strategies to direct participants to the survey, and partnerships with 13 voluntary, community and social enterprise (VCSE) organisations[1] helped to recruit participants for the survey.

    The ambition of EVENS was to better represent ethnic and religious minorities compared to existing data sources regarding the range and diversity of represented minority population groups and the topic coverage. Thus, the EVENS survey used an 'open' survey approach, which requires participants to opt-in to the survey instead of probability-based approaches that invite individuals to participate following their identification within a pre-defined sampling frame. This 'open' approach sought to overcome some of the limitations of probability-based methods in order to reach a large number and diverse mix of people from religious and ethnic minorities.

    EVENS included a wide range of research and policy questions, including education, employment and economic well-being, housing, social, cultural and political participation, health, and experiences of racism and discrimination, particularly with respect to the impact of the COVID-19 pandemic. Crucially, EVENS covered a full range of racial, ethnic and religious groups, including those often unrepresented in such work (such as Chinese, Jewish and Traveller groups), resulting in the participation of 14,215 participants, including 9,702 ethnic minority participants and a general population sample of 4,513, composed of White people who classified themselves as English, Welsh, Scottish, Northern Irish, and British. Data collection covered the period between 16 February 2021 and 14 August 2021.

    Further information about the study can be found on the EVENS project website.

    A teaching dataset based on the main EVENS study is available from the UKDS under SN 9249.

    [1] The VCSE organisations included Business in the Community, BEMIS (Scotland), Ethnic Minorities and Youth Support Team (Wales), Friends, Families and Travellers, Institute for Jewish Policy Research, Migrants' Rights Networks, Muslim Council Britain, NHS Race and Health Observatory, Operation Black Vote, Race Equality Foundation, Runnymede Trust, Stuart Hall Foundation, and The Ubele Initiative.
  2. N

    Paris, KY Population Breakdown By Race (Excluding Ethnicity) Dataset:...

    • neilsberg.com
    csv, json
    Updated Jul 7, 2024
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    Neilsberg Research (2024). Paris, KY Population Breakdown By Race (Excluding Ethnicity) Dataset: Population Counts and Percentages for 7 Racial Categories as Identified by the US Census Bureau // 2024 Edition [Dataset]. https://www.neilsberg.com/research/datasets/2e48f03c-230c-11ef-bd92-3860777c1fe6/
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    csv, jsonAvailable download formats
    Dataset updated
    Jul 7, 2024
    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
    Paris, Kentucky
    Variables measured
    Asian Population, Black Population, White Population, Some other race Population, Two or more races Population, American Indian and Alaska Native Population, Asian Population as Percent of Total Population, Black Population as Percent of Total Population, White Population as Percent of Total Population, Native Hawaiian and Other Pacific Islander Population, and 4 more
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the racial categories idetified by the US Census Bureau. It is ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories, and do not rely on any ethnicity classification. 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

    The dataset tabulates the population of Paris by race. It includes the population of Paris across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Paris across relevant racial categories.

    Key observations

    The percent distribution of Paris population by race (across all racial categories recognized by the U.S. Census Bureau): 83.49% are white, 8.19% are Black or African American, 0.79% are American Indian and Alaska Native, 0.05% are Asian, 0.63% are some other race and 6.85% are multiracial.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

    Racial categories include:

    • White
    • Black or African American
    • American Indian and Alaska Native
    • Asian
    • Native Hawaiian and Other Pacific Islander
    • Some other race
    • Two or more races (multiracial)

    Variables / Data Columns

    • Race: This column displays the racial categories (excluding ethnicity) for the Paris
    • Population: The population of the racial category (excluding ethnicity) in the Paris is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each race as a proportion of Paris total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

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

    Custom data

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

    Inspiration

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

    Recommended for further research

    This dataset is a part of the main dataset for Paris Population by Race & Ethnicity. You can refer the same here

  3. e

    British General Election Study, 1997 : Ethnic Minority Survey - Dataset -...

    • b2find.eudat.eu
    Updated Oct 20, 2023
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    (2023). British General Election Study, 1997 : Ethnic Minority Survey - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/cf0821e8-431c-5981-9d78-107cba3f9de9
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    Dataset updated
    Oct 20, 2023
    Area covered
    United Kingdom
    Description

    Abstract copyright UK Data Service and data collection copyright owner. British General Election Study, 1997 : Ethnic Minority Survey The aims of the Ethnic Minority Survey are: to evaluate the extent to which ethnic minority voters are integrated into the electoral process; to evaluate whether, after taking into account their social background, members of the main ethnic minorities vote differently from each other and from their white counterparts; to examine whether the political attitudes of ethnic minority voters are significantly different from that of white voters; to examine whether members of ethnic minorities are influenced by different considerations than their white counterparts in deciding how to vote and to evaluate in particular, the importance of issues of race and immigration in voting behaviour of ethnic minority and white voters. Main Topics: The file contains data for 705 respondents from: an hour and ten minutes long face-to-face interview; a self-completion questionnaire; geographic information derived from the census; turn-out and electoral registration information derived from a check against the marked-up Electoral Registers. The respondents are partly a subset of the British General Election Study Cross-section Survey and partly an ethnic boost generated by a random screening survey. Standard Measures Self-completion Q3a,b,e,f,g,Q4a make up a standard BGES left-right scale; self-completion Q3c,d,Q4b-e make up a standard BGES libertarian-authoritarian scale. Multi-stage stratified random sample The sample was generated from three main sources: ethnic minority respondents who happened to be generated by the main study (samples A and B); a large-scale screening exercise in areas of high ethnic minority concentration (sample C); next-door screening at some sample points with high ethnic minority concentrations (sample D). Face-to-face interview Self-completion CAPI; Link to census data; check against marked-up electoral registers.

  4. u

    Community Focus Areas 2023 RTP

    • data.wfrc.utah.gov
    Updated Jun 15, 2023
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    Wasatch Front Regional Council (2023). Community Focus Areas 2023 RTP [Dataset]. https://data.wfrc.utah.gov/datasets/community-focus-areas-2023-rtp
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    Dataset updated
    Jun 15, 2023
    Dataset authored and provided by
    Wasatch Front Regional Council
    Area covered
    Description

    WFRC Community Focus Areas (2023)Geographic Representation Units WFRC’s Community Focus Areas (CFAs) are geographic areas for which additional consideration may be given within the planning and programming processes for future transportation, economic development, and other projects administered through WFRC. CFAs are used by WFRC in support of meeting the Council-established goal of promoting “inclusive engagement in transportation planning processes and equitable access to affordable and reliable transportation options.” CFAs are designated from Census block group geographic zones that meet the criteria described below. Census block groups are used as these are the smallest geographic areas for which more detailed household characteristics like employment, income, vehicle ownership, commute trip, and English language proficiency are available. WFRC recognizes the limitations of geography-based analysis, as proper planning work considers together the needs of individuals, groups and sectors, and geographic areas. However, geography-based analyses offer a useful starting point for the consideration and prioritization of projects that will serve specific community needs.2023 Community Focus Area Criteria UpdateFor the 2023 RTP planning cycle, WFRC will use two factors in designating geography-based CFAs: 1) concentration of low-income households and 2) concentration of persons identifying as members of racial and ethnic minority groups. The geography for these factors can be identified from consistent and regularly updated data sources maintained by the U.S. Census Bureau. WFRC will also make data available that conveys, while maintaining individual anonymity, the geographic distribution of additional measures including concentrations of persons with disabilities, households with limited English language proficiency, households that do not own a vehicle, older residents (65+ years of age), and younger residents (0-17 years of age). While the application of these factors within the planning process is less straightforward because of their higher statistical margins of error and comparatively even distribution within the region, these additional factors remain valuable as planning context. Low Income Focus Areas, Methodology for IdentificationThe block group-level data from the 2020 Census American Community Survey (ACS) 5-year dataset (Table C17002: Ratio of Income to Poverty Level), is used to determine the percentage of the population within each block group that are in households that have a ratio of income to federal poverty threshold of equal to or less than 1, i.e., their income is below the poverty level. The federal poverty threshold is set differently for households, considering their household size and age of household members.Census block groups in which more than 20% of the households whose income is less than or equal to the federal poverty threshold are included in the WFRC CFAs and designated as Low-Income focus areas. Racial and Ethnic Minority Focus AreasThe block group-level data from the 2020 ACS 5-year dataset (Table B03002: Hispanic or Latino Origin By Race) is used to determine the percentage of the population that did not self-identify their race and ethnicity as “White alone.” The average census block group area in the Wasatch Front urbanized areas has 24.2% of its population that identifies as Black or African American alone, American Indian, and Alaska Native alone, Asian alone, Native Hawaiian and other Pacific Islander alone, some other race alone, two or more races, or of Hispanic or Latino origin.Census blocks in which more than 40%2 of the population identifies as one or more of the racial or ethnic groups listed above are included in the WFRC CFAs and designated as Racial and Ethnic Minority focus areas.Excluding Predominantly Non-Residential Areas from CFAsSome census block groups that meet one or both of the CFA criteria described above contain large, non-residential areas or low density residential areas. Such census block areas may have small residential neighborhoods surrounded by predominantly commercial or industrial land uses, or large areas of public land or as-yet undeveloped lands. For this reason, WFRC staff may adjust the boundaries of an CFA whose census block group population density is less than 500 persons per square mile, to exclude areas of those block groups that have large, predominantly non-residential land uses.Community Focus Area Update FrequencyThe geography for WFRC CFAs will be updated not less than every four years, preceding the project phasing period of the Regional Transportation Planning update cycle. The update will use the most recent version of the 5 year ACS dataset. The next update is expected in the summer of 2026 (the beginning of the 4th year for the 2027 RTP development process) and is expected to use the 2024 5-year ACS results that average results across 2020-2024.Footnotes:1. The 2019 version of WFRC CFAs used ‘Zero Car Households’ as a third factor. This factor is no longer included because of its geographic and statistical fluctuation over time in data reported by the American Community Survey. Additionally, ‘Zero Car households’ was observed to have a strong relationship with the other two CFA designation factors.2. The percentage threshold specified here is approximately one standard deviation above the regional mean for this indicator. Assuming a statistically normal distribution, approximately 16% of the overall set (i.e. census blocks, in this case) would fall above a one standard deviation threshold.3. Table B03002 includes information from both 'Race' and 'Hispanic or Latino Origin' identification questions asked as part of the Census Bureau's American Community Survey.

  5. O

    Litchfield County Court African Americans and Native Americans Collection,...

    • data.ct.gov
    • catalog.data.gov
    application/rdfxml +5
    Updated Jul 3, 2025
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    CT State Library (2025). Litchfield County Court African Americans and Native Americans Collection, 1753 - 1852 [Dataset]. https://data.ct.gov/History/Litchfield-County-Court-African-Americans-and-Nati/qfdg-i76h
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    json, application/rssxml, tsv, csv, application/rdfxml, xmlAvailable download formats
    Dataset updated
    Jul 3, 2025
    Dataset authored and provided by
    CT State Library
    Area covered
    Litchfield County, United States
    Description

    PLEASE NOTE: This is an index of a historical collection that contains words and phrases that may be offensive or harmful to individuals investigating these records. In order to preserve the objectivity and historical accuracy of the index, State Archives staff took what would today be considered archaic and offensive descriptions concerning race, ethnicity, and gender directly from the original court papers. For more information on appropriate description, please consult the Diversity Style Guide and Archives for Black Lives in Philadelphia: Anti-Racist Description Resources.

    The Litchfield County Court African Americans and Native Americans Collection is an artificial collection consisting of photocopies of cases involving persons of African descent and indigenous people from the Files and Papers by Subject series of Litchfield County Court records. This collection was created in order to highlight the lives and experiences of underrepresented groups in early America, and make them more easily accessible to researchers.

    Collection Overview

    The collection consists of records of 188 court cases involving either African Americans or Native Americans. A careful search of the Files for the Litchfield County Court discovered 165 on African Americans and 23 on Native Americans, about one third of the total that was found in Files for the New London County Court for the period up to the American Revolution. A couple of reasons exist for this vast difference in numbers. First, Litchfield County was organized much later than New London, one of Connecticut's four original counties. New London was the home of four of seven recognized tribes, was a trading center, and an area of much greater wealth. Second, minority population in the New London County region has been tracked and tabulated by Barbara Brown and James Rose in Black Roots of Southeastern Connecticut.1 Although this valuable work does not include all of Negro or Indian background, it provides a wonderful starting point and it has proven to be of some assistance in tracking down minorities in Litchfield County. In most instances, however, identification is based upon language in the documents and knowledge of surnames or first names.2 Neither surname nor first name provides an invariably reliable guide so it is possible that some minorities have been missed and some persons included that are erroneous.

    In thirteen of 188 court cases, the person of African or Native American background cannot be identified even by first name. He or she is noted as "my Negro," a slave girl, or an Indian. In twenty-three lawsuits, a person with a first name is identified as a Negro, as an Indian in two other cases, and Mulatto in one. In the remaining 151 cases, a least one African American or Native American is identified by complete name.3 Thirteen surnames recur in three or more cases.4 A total of seventy surnames, some with more than one spelling, are represented in the records.

    The Jacklin surname appears most frequently represented in the records. Seven different Jacklins are found in eighteen cases, two for debt and the remaining sixteen for more serious crimes like assault, breach of peace, keeping a bawdy house, and trespass.5 Ten cases concern Cuff Kingsbury of Canaan between 1808 and 1812, all involving debts against Kingsbury and the attempts of plaintiffs to secure writs of execution against him. Cyrus, Daniel, Ebenezer, Jude, Luke, Martin, Nathaniel, Pomp, Titus, and William Freeman are found in nine cases, some for debt, others for theft, and one concerning a petition to appoint a guardian for aged and incompetent Titus Freeman.6 Six persons with the surname Caesar are found in seven court cases.

    Sixty-one of 188 cases concern debt.7 Litchfield County minorities were plaintiffs in only about ten of these lawsuits, half debt by book and half debt by note. The largest single category of court proceedings concern cases of crimes against person or property. They include assault (32 cases), theft (30), breach of peace (5), and breaking out of jail (1). In cases of assault, the Negro or Indian was the perpetrator in about two thirds of the cases and victim in one third. In State v. Alexander Kelson, the defendant was accused of assaulting Eunice Mawwee.8 Minority defendants in assault cases included Daniel K. Boham, William Cable, Prince Comyns, Adonijah Coxel, Homer Dolphin, Jack Jacklin, Pompey Lepean, John Mawwee, Zack Negro, and Jarvis Phillips. One breach of peace case, State v. Frederic Way, the defendant, "a transient Indian man," was accused of breach of the peace for threatening Jonathan Rossetter and the family of Samuel Wilson of Harwinton.9

    In cases of theft, African Americans appeared as defendants in 27 of 30 cases, the only exceptions being two instances in which Negroes were illegally seized by whites and the case of State v. William Pratt of Salisbury. The State charged Pratt with stealing $35 from the house of George Ceasor.10 More typical, however, are such cases as State v. Prince Cummins for the theft of a dining room table and State v. Nathaniel Freeman for the theft of clothes.11

    Another major category of lawsuits revolves around the subject of slaves as property. The number and percentage of such cases is much lower than that for New London County due to the fact that the county was only organized one generation before the American Revolution and the weaker grip the institution of slavery had in that county. The cases may be characterized as conversion to own use (4), fraudulent contract (3), fraudulent sale (3), runaways (3), illegal enslavement (2), and trespass (2).12 The Litchfield County Court in April 1765 heard George Catling v. Moses Willcocks, a case in which Willcocks was accused of converting a slave girl and household goods to his own use.13 In the 1774 fraudulent contract case of Josiah Willoughby v. Elisha Bigelow, the plaintiff accused Bigelow of lying about York Negro's age and condition. Willoughby stated that York Negro was twenty years older that he was reputed to be, was blind in one eye, and "very intemperate in the use of Speretuous Lickor." He sued to recover the purchase price of £45, the court agreed, and the defendant appealed.14 Cash Africa sued Deborah Marsh of Litchfield in 1777 for illegal enslavement. He claimed that he was unlawfully seized with force and arms and compelled to labor for the defendant for three years.15 In another case, David Buckingham v. Jonathan Prindle, the defendant was accused of persuading Jack Adolphus to run away from his master. The plaintiff claimed that Adolphus was about twenty years old and bound to service until age twenty-five, when he would be freed under terms of Connecticut's gradual emancipation law.16

    Other subjects found in Litchfield County Minorities include defamation, gambling, keeping a bawdy house, and lascivious carriage. The defamation cases all included the charge of sexual intercourse with an Indian or Negro. In one such case, Henry S. Atwood v. Norman Atwood, both of Watertown, the defendant defamed and slandered the plaintiff by charging that he was "guilty of the crime of fornication or adultery with [a] Black or Negro woman," the wife of Peter Deming.17 Three cases, two from 1814 and one from 1821, accuse several Negroes accuse Harry Fitch, Polly Gorley, Violet Jacklin, Betsy Mead, and Jack Peck alias Jacklin, of running houses of ill repute.18

    The records on African Americans and Native Americans from Litchfield County are relatively sparse, but they do provide some indication of the difficulties encountered by minorities in white society. They also provide some useful genealogical data on a handful of families in northwestern Connecticut.

    1. Barbara W. Brown and James M. Rose, joint authors, Black Roots in Southeastern Connecticut, 1650-1900 (Detroit: Gale Research Co., 1980).
    2. The court cases often identify minorities by the words Negro, mulatto, colored, or Indian.
    3. Two or more African Americans or Native Americans are found in 27 lawsuits, but a maximum of two people are included in the Litchfield County Minorities database.
    4. Surnames with spelling variations: Boston (3), Botsford (4), Caesar (7), Coxel (3), Freedom (3), Freeman (9), Gauson (5), Jacklin (17), Kingsbury (10), Leopen (4), Mawwee (5), Quomenor (4), and Smith (3).
    5. George, Harvey, Isaac, Jack, Philip, Violet, and William Jacklin. Also included is Jack Peck, alias Jack Jacklin.
    6. For the last case, see Conservators and Guardians, Box 2, folder 42.
    7. Fifty-seven suits for debt, the vast majority of which a minority was plaintiff or defendant, and four concerning writs of execution to recover debt owed.
    8. Dec. 1836, Box 3, folder 16.
    9. Sep. 1796, Box 3, folder 6.
    10. David King v. Stephen Walton, Mar. 1791, Box 1, folder 17;Simon Mitchel v. Edward Hinman, Dec. 1793, Box 1, folder 18; State v. William Pratt, Oct. 1848, Box 2, folder 37.
    11. Apr. 1828, Box 2, folder 23; Oct. 1837, Box 2, folder 29.
    12. Three additional conversion cases concern livestock and hay.
    13. Apr. 1765, Box 1, folder 5.
    14. Dec. 1774, Box 1, folder 9.
    15. Sep. 1777, Box 1, folder 9.
    16. Dec. 1813, Box 1, folder 49.
    17. Dec. 1814, Box 2, folder 2.
    18. Sep. 1814, Box 2, folder 3, Sep. 1814, Box 2, folder 4; Sep. 1821, Box 2, folder 15.

    If a record of interest is found, and a reproduction of the original record is desired, you may submit a request via <a

  6. undefined undefined: undefined | undefined (undefined)

    • data.census.gov
    Updated Dec 16, 2021
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    United States Census Bureau (2021). undefined undefined: undefined | undefined (undefined) [Dataset]. https://data.census.gov/table/ABSNESD2018.AB00MYNESD01C?q=Santa+Cruz+County,+California+Business+and+Economy&g=050XX00US06065,06087_040XX00US06&y=2018
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    Dataset updated
    Dec 16, 2021
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    License

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

    Description

    Key Table Information.Table Title.Nonemployer Statistics by Demographics series (NES-D): Statistics for Employer and Nonemployer Firms by Industry and Race for the U.S., States, and Metro Areas: 2018.Table ID.ABSNESD2018.AB00MYNESD01C.Survey/Program.Economic Surveys.Year.2018.Dataset.ECNSVY Nonemployer Statistics by Demographics Company Summary.Source.U.S. Census Bureau, 2018 Economic Surveys, Nonemployer Statistics by Demographics.Release Date.2021-12-16.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.Data in this table combines estimates from the Annual Business Survey (employer firms) and the Nonemployer Statistics by Demographics (nonemployer firms).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).Includes U.S. employer firms estimates of business ownership by sex, ethnicity, race, and veteran status from the 2019 Annual Business Survey (ABS) collection. The employer business 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.Data are also obtained from administrative records and other economic surveys. Note: For employer data only, 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 2019 ABS collection year produces statistics for the 2018 reference year. The "Year" column in the table is the reference year..Methodology.Data Items and Other Identifying Records.Total number of employer and nonemployer firmsTotal sales, value of shipments, or revenue of employer and nonemployer firms ($1,000)Number of nonemployer firmsSales, value of shipments, or revenue of nonemployer firms ($1,000)Number of employer firmsSales, value of shipments, or revenue of employer firms ($1,000)Number of employeesAnnual payroll ($1,000)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) 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) 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 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.Data are shown for the total for all sectors (00) and the 2-digit NAICS levels for the U.S., states and District of Columbia, and metro areas.For 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)Management of Companies and Enterprises (NAICS 55)Private Households (NAICS 814)Public Administration (NAICS 92)Industries Not Classified (NAICS 99)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 da...

  7. G

    Percent visible minority by municipality

    • ouvert.canada.ca
    • open.canada.ca
    html
    Updated Jul 24, 2024
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    Government of Alberta (2024). Percent visible minority by municipality [Dataset]. https://ouvert.canada.ca/data/dataset/da64f6c4-d669-4d5c-8758-cab00de949fa
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    htmlAvailable download formats
    Dataset updated
    Jul 24, 2024
    Dataset provided by
    Government of Alberta
    License

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

    Time period covered
    Jan 1, 1987 - Dec 31, 2021
    Description

    Lists visible minorities as a percentage of the total population, by census year and municipality and municipal district. Visible minorities, as defined in the federal Employment Equity Act, are "persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in colour".

  8. 2022 Economic Surveys: AB00MYCSA01C | Annual Business Survey: Statistics for...

    • data.census.gov
    • test.data.census.gov
    Updated Dec 19, 2024
    + more versions
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    ECN (2024). 2022 Economic Surveys: AB00MYCSA01C | Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2022 (ECNSVY Annual Business Survey Company Summary) [Dataset]. https://data.census.gov/table/ABSCS2022.AB00MYCSA01C?n=713910
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    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 Race for the U.S.: 2022.Table ID.ABSCS2022.AB00MYCSA01C.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) Race White Black or African American American Indian and Alaska Native Asian Asian Indian Chinese Filipino Japanese Korean Vietnamese Other Asian Native Hawaiian and Other Pacific Islander Native Hawaiian Guamanian or Chamorro Samoan 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) 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 An...

  9. f

    Data_Sheet_2_Racial and Ethnic Inequities in Mortality During...

    • figshare.com
    • frontiersin.figshare.com
    pdf
    Updated Jun 16, 2023
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    Emma A. Richie; Joseph G. Nugent; Ahmed M. Raslan (2023). Data_Sheet_2_Racial and Ethnic Inequities in Mortality During Hospitalization for Traumatic Brain Injury: A Call to Action.pdf [Dataset]. http://doi.org/10.3389/fsurg.2021.690971.s002
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    pdfAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    Frontiers
    Authors
    Emma A. Richie; Joseph G. Nugent; Ahmed M. Raslan
    License

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

    Description

    The health disparities which drive inequities in health outcomes have long plagued our already worn healthcare system and are often dismissed as being a result of social determinants of health. Herein, we explore the nature of these inequities by comparing outcomes for racial and ethnic minorities patients suffering from traumatic brain injury (TBI). We retrospectively reviewed all patients enrolled in the Trauma One Database at the Oregon Health & Science University Hospital from 2006 to October 2017 with an abbreviated injury scale (AIS) for the head or neck >2. Racial and ethnic minority patients were defined as non-White or Hispanic. A total of 6,352 patients were included in our analysis with 1,504 in the racial and ethnic minority cohort vs. 4,848 in the non-minority cohort. A propensity score (PS) model was generated to account for differences in baseline characteristics between these cohorts to generate 1,500 matched pairs. The adjusted hazard ratio for in-hospital mortality for minority patients was 2.21 [95% Confidence Interval (CI) 1.43–3.41, p < 0.001] using injury type, probability of survival, and operative status as covariates. Overall, this study is the first to specifically look at racial and ethnic disparities in the field of neurosurgical trauma. This research has demonstrated significant inequities in the mortality of TBI patients based on race and ethnicity and indicates a substantive need to reshape the current healthcare system and advocate for safer and more supportive pre-hospital social systems to prevent these life-threatening sequelae.

  10. f

    Data_Sheet_1_Ethnicity, minority status, and inter-group bias: A systematic...

    • frontiersin.figshare.com
    docx
    Updated Jun 21, 2023
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    Aino Saarinen; Liisa Keltikangas-Järvinen; Niklas Ravaja (2023). Data_Sheet_1_Ethnicity, minority status, and inter-group bias: A systematic meta-analysis on fMRI studies.DOCX [Dataset]. http://doi.org/10.3389/fnhum.2022.1072345.s001
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    docxAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    Frontiers
    Authors
    Aino Saarinen; Liisa Keltikangas-Järvinen; Niklas Ravaja
    License

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

    Description

    IntroductionThis meta-analysis investigated (1) whether ethnic minority and majority members have a neural inter-group bias toward each other, and (2) whether various ethnic groups (i.e., White, Black, and Asian) are processed in the brain differently by the other respective ethnicities.MethodsA systematic coordinate-based meta-analysis of functional magnetic resonance imaging (fMRI) studies was conducted using Web of Science, PubMed, and PsycINFO (altogether 50 datasets, n = 1211, 50.1% female).ResultsWe found that ethnic minority members did not show any signs of neural inter-group bias (e.g., no majority-group derogation). Ethnic majority members, in turn, expressed biased responses toward minority (vs. majority) members in frontal, parietal, temporal, and occipital regions that are known to be involved in e.g., facial processing, attention, and perspective-taking. We also found differences in neural response patterns toward different ethnic groups (White, Black, and Asian); broadest biases in neural response patterns were evident toward Black individuals (in non-Black individuals). Heterogeneity was mostly minor or low.Discussion:Overall, the findings increase understanding of neural processes involved in ethnicity perception and cognition as well as ethnic prejudices and discrimination. This meta-analysis provides explanations for previous behavioral reports on ethnic discrimination toward minority groups.

  11. England and Wales Census 2021 - Ethnic group by highest level qualification

    • statistics.ukdataservice.ac.uk
    xlsx
    Updated Mar 15, 2023
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    Office for National Statistics; National Records of Scotland; Northern Ireland Statistics and Research Agency; UK Data Service. (2023). England and Wales Census 2021 - Ethnic group by highest level qualification [Dataset]. https://statistics.ukdataservice.ac.uk/dataset/england-and-wales-census-2021-ethnic-group-by-highest-level-qualification
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    xlsxAvailable download formats
    Dataset updated
    Mar 15, 2023
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    Northern Ireland Statistics and Research Agency
    UK Data Servicehttps://ukdataservice.ac.uk/
    Authors
    Office for National Statistics; National Records of Scotland; Northern Ireland Statistics and Research Agency; UK Data Service.
    License

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

    Area covered
    Wales, England
    Description

    This dataset represents ethnic group (19 tick-box level) by highest level qualification, for England and Wales combined. The data are also broken down by age and by sex.

    The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.

    Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

    "Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.

    This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021. This dataset shows population counts for usual residents aged 16+ Some people aged 16 years old will not have completed key stage 4 yet on census day, and so did not have the opportunity to record any qualifications on the census.

    These estimates are not comparable to Department of Education figures on highest level of attainment because they include qualifications obtained outside England and Wales.

    For quality information in general, please read more from here.

    Ethnic Group (19 tick-box level)

    These are the 19 ethnic group used in this dataset:

    • Asian, Asian British or Asian Welsh
      • Bangladeshi
      • Chinese
      • Indian
      • Pakistani
      • Other Asian
    • Black, Black British, Black Welsh, Caribbean or African
      • African
      • Caribbean
      • Other Black
    • Mixed or Multiple ethnic groups
      • White and Asian
      • White and Black African
      • White and Black Caribbean
      • Other Mixed or Multiple ethnic groups
    • White
      • English, Welsh, Scottish, Northern Irish or British
      • Gypsy or Irish Traveller
      • Irish
      • Roma
      • Other White
    • Other ethnic group
      • Arab
      • Any other ethnic group

    No qualifications

    No qualifications

    Level 1

    Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential Skills

    Level 2

    5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA Diploma

    Apprenticeship

    Apprenticeship

    Level 3

    2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced Diploma

    Level 4 +

    Degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)

    Other

    Vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)

  12. U

    Replication data for: Impartial Judges? Race, Institutional Context, and...

    • dataverse.unc.edu
    • dataverse-staging.rdmc.unc.edu
    Updated Nov 19, 2015
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    UNC Dataverse (2015). Replication data for: Impartial Judges? Race, Institutional Context, and U.S. State Supreme Courts [Dataset]. http://doi.org/10.15139/S3/12123
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    tsv(32053436), text/plain; charset=us-ascii(9722)Available download formats
    Dataset updated
    Nov 19, 2015
    Dataset provided by
    UNC Dataverse
    Area covered
    United States
    Description

    We address a fundamental question in judicial politics: other things being equal, do African American judges behave differently than white judges? Many presume that white judges differ from their minority counterparts in terms of sentencing, deliberation, and propensity to overturn decisions. However, to date, there is little empirical evidence on whether there are systematic differences in behavior between these judges. Here, we utilize the newly created judge-level U.S. State Supreme Court Database to assess whether judicial decisionmaking is affected by the race of the judge. Looking at all criminal cases decided by U.S. state supreme court judges from 1995-1998, we find evidence of differences between white and non-white judges, but only in states where there is no intermediate appellate court. This suggests the effects of race on judicial decisionmaking are conditioned by the institutional structure of the court system.

  13. Colorado Census Tract Retail Alcohol Outlet Density

    • data-cdphe.opendata.arcgis.com
    • hub.arcgis.com
    Updated Jan 28, 2022
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    Colorado Department of Public Health and Environment (2022). Colorado Census Tract Retail Alcohol Outlet Density [Dataset]. https://data-cdphe.opendata.arcgis.com/datasets/colorado-census-tract-retail-alcohol-outlet-density-2020
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    Dataset updated
    Jan 28, 2022
    Dataset authored and provided by
    Colorado Department of Public Health and Environmenthttps://cdphe.colorado.gov/
    Area covered
    Description

    Feature class representing retail alcohol outlet density at the census tract level developed directly from address information from liquor licensee lists that were obtained from the Colorado Department of Revenue-Liquor Enforcement Division (DOR-LED). This file was developed for use in activities and exercises within the Colorado Department of Public Health and Environment (CDPHE), including the Alcohol Outlet Density StoryMap. CDPHE nor DOR-LED are responsible for data products made using this publicly available data. It should be stated that neither agency is acting as an active data steward of this map service/geospatial data layer at this point in time. This dataset is representative of Colorado licensing data gathered in January 2024. The data file contains the following attributes:FIPSTract Name Tract FIPS StateCountyLand Area Square Miles (Area of Land in Square Miles)Water Area SquareMiles (Area of Water in Square Miles)Population Total (Total Population as estimated in ACS 2018-2022)Percent Race White (Percent of population identifying as White as estimated in ACS 2018-2022) Percent Race African American Percent (Percent of population identifying as African American as estimated in ACS 2018-2022)Race American Indian Alaskan Native (Percent of population identifying as American Indian or Alaskan Native as estimated in ACS 2018-2022)Percent Race Asian (Percent of population identifying as Asian as estimated in ACS 2018-2022)Percent Race NHawaiian OPI (Percent of population identifying as Native Hawaiian or Pacific Islander as estimated in 2018-2022)Percent Race Other (Percent of population identifying as another race as estimated in 2018-2022)Percent Ethnicity Hispanic Latino (Percent of population identifying as Hispanic or Latino as estimated in 2018-2022)Percent Ethnicity Not Hispanic or Latino (Percent of population identifying as not Hispanic or Latino as estimated in 2018-2022)Percent Race Minority Race or Hispanic Latino (Percent of population made up of a Race and/or Ethnicity other than White, Non-Hispanic)Percent Population over 24 Years No HS Diploma (Percent of population over 24 years old without a High School Diploma as estimated in 2018-2022)Frequency All Retail Outlets 2024 (All retail alcohol outlets from January 2024)Average Distance Between Outlets in Meters (Average distance in Meters between an alcohol outlet and its nearest neighboring outlet)Frequency Off Premises Outlets 2024 (All Off-premises retail alcohol outlets from January 2024)Frequency On Premises Outlets 2024 (All On-premises retail alcohol outlets from January 2024)Rate Total Outlets per Square Mile (Rate of all retail alcohol outlets per square mile)Rate Total Outlets per 1,000 Residents (Rate of all retail alcohol outlets per 1,000 residents)Rate On Premises Outlets per Square Mile (Rate of On-premises retail alcohol outlets per square mile)Rate Off Premises Outlets per Square Mile (Rate of On-premises retail alcohol outlets per square mile)Rate On Premises Outlets per 1,000 Residents (Rate of on-premises retail alcohol outlets per 1,000 residents)Rate Off Premises Outlets per 1,000 Residents (Rate of off-premises retail alcohol outlets per 1,000 residents)Average Distance Between Outlets in Miles (Average distance in Miles between an alcohol outlet and its nearest neighboring outlet)

  14. p

    Trends in Two or More Races Student Percentage (2011-2023): Maize School...

    • publicschoolreview.com
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    Public School Review, Trends in Two or More Races Student Percentage (2011-2023): Maize School District vs. Kansas [Dataset]. https://www.publicschoolreview.com/kansas/maize-school-district/2009140-school-district
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    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    Maize Unified School District 266
    Description

    This dataset tracks annual two or more races student percentage from 2011 to 2023 for Maize School District vs. Kansas

  15. 2021 Economic Surveys: AB00MYCSA01C | Annual Business Survey: Statistics for...

    • data.census.gov
    Updated Oct 26, 2023
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    ECN (2023). 2021 Economic Surveys: AB00MYCSA01C | Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2021 (ECNSVY Annual Business Survey Company Summary) [Dataset]. https://data.census.gov/table/ABSCS2021.AB00MYCSA01C?q=111920:+Cotton+Farming&y=2021&n=722
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    Dataset updated
    Oct 26, 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
    2021
    Area covered
    United States
    Description

    Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2021.Table ID.ABSCS2021.AB00MYCSA01C.Survey/Program.Economic Surveys.Year.2021.Dataset.ECNSVY Annual Business Survey Company Summary.Release Date.2023-10-26.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) 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) 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 2021 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-FY23-0479).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/2021/.API Information.Annual Business Survey (ABS) data...

  16. 2017 Economic Surveys: AB00MYCSA01C | Annual Business Survey: Statistics for...

    • data.census.gov
    Updated May 19, 2020
    + more versions
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    ECN (2020). 2017 Economic Surveys: AB00MYCSA01C | Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2017 (ECNSVY Annual Business Survey Company Summary) [Dataset]. https://data.census.gov/table/ABSCS2017.AB00MYCSA01C?g=&n=444130
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    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 Race for the U.S.: 2017.Table ID.ABSCS2017.AB00MYCSA01C.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) Race White Black or African American American Indian and Alaska Native Asian Asian Indian Chinese Filipino Japanese Korean Vietnamese Other Asian Native Hawaiian and Other Pacific Islander Native Hawaiian Guamanian or Chamorro Samoan 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) 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.....

  17. a

    Low Income Cutoffs after tax Visible Minority over 65 years total sex

    • zero-hunger-fredericton.hub.arcgis.com
    • community-prosperity-hub-fredericton.hub.arcgis.com
    • +4more
    Updated Jul 30, 2020
    + more versions
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    City of Fredericton - Ville de Fredericton (2020). Low Income Cutoffs after tax Visible Minority over 65 years total sex [Dataset]. https://zero-hunger-fredericton.hub.arcgis.com/datasets/low-income-cutoffs-after-tax-visible-minority-over-65-years-total-sex
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    Dataset updated
    Jul 30, 2020
    Dataset authored and provided by
    City of Fredericton - Ville de Fredericton
    Description

    Low-income cut-offs, after tax (LICO-AT) - The Low-income cut-offs, after tax refers to an income threshold, defined using 1992 expenditure data, below which economic families or persons not in economic families would likely have devoted a larger share of their after-tax income than average to the necessities of food, shelter and clothing. More specifically, the thresholds represented income levels at which these families or persons were expected to spend 20 percentage points or more of their after-tax income than average on food, shelter and clothing. These thresholds have been adjusted to current dollars using the all-items Consumer Price Index (CPI).The LICO-AT has 35 cut-offs varying by seven family sizes and five different sizes of area of residence to account for economies of scale and potential differences in cost of living in communities of different sizes. These thresholds are presented in Table 4.3 Low-income cut-offs, after tax (LICO-AT - 1992 base) for economic families and persons not in economic families, 2015, Dictionary, Census of Population, 2016.When the after-tax income of an economic family member or a person not in an economic family falls below the threshold applicable to the person, the person is considered to be in low income according to LICO-AT. Since the LICO-AT threshold and family income are unique within each economic family, low-income status based on LICO-AT can also be reported for economic families.Return to footnote1referrerFootnote 2For more information on generation status variables, including information on their classifications, the questions from which they are derived, data quality and their comparability with other sources of data, please refer to the Place of Birth, Generation Status, Citizenship and Immigration Reference Guide, Census of Population, 2016.Return to footnote2referrerFootnote 3Low-income status - The income situation of the statistical unit in relation to a specific low-income line in a reference year. Statistical units with income that is below the low-income line are considered to be in low income.For the 2016 Census, the reference period is the calendar year 2015 for all income variables.Return to footnote3referrerFootnote 4The low-income concepts are not applied in the territories and in certain areas based on census subdivision type (such as Indian reserves). The existence of substantial in-kind transfers (such as subsidized housing and First Nations band housing) and sizeable barter economies or consumption from own production (such as product from hunting, farming or fishing) could make the interpretation of low-income statistics more difficult in these situations.Return to footnote4referrerFootnote 5Prevalence of low income - The proportion or percentage of units whose income falls below a specified low-income line.Return to footnote5referrerFootnote 6For more information on the Visible minority variable, including information on its classification, the questions from which it is derived, data quality and its comparability with other sources of data, please refer to the Visible Minority and Population Group Reference Guide, Census of Population, 2016.Return to footnote6referrerFootnote 7The Employment Equity Act defines visible minorities as 'persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in colour.'Return to footnote7referrerFootnote 8For example, 'East Indian,' 'Pakistani,' 'Sri Lankan,' etc.Return to footnote8referrerFootnote 9For example, 'Vietnamese,' 'Cambodian,' 'Laotian,' 'Thai,' etc.Return to footnote9referrerFootnote 10For example, 'Afghan,' 'Iranian,' etc.Return to footnote10referrerFootnote 11The abbreviation 'n.i.e.' means 'not included elsewhere.' Includes persons with a write-in response such as 'Guyanese,' 'West Indian,' 'Tibetan,' 'Polynesian,' 'Pacific Islander,' etc.Return to footnote11referrerFootnote 12Includes persons who gave more than one visible minority group by checking two or more mark-in responses, e.g., 'Black' and 'South Asian.'Return to footnote12referrerFootnote 13Includes persons who reported 'Yes' to the Aboriginal group question (Question 18), as well as persons who were not considered to be members of a visible minority group.

  18. 2018 Economic Surveys: AB00MYCSA01C | Annual Business Survey: Statistics for...

    • data.census.gov
    Updated Jan 28, 2021
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    ECN (2021). 2018 Economic Surveys: AB00MYCSA01C | Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2018 (ECNSVY Annual Business Survey Company Summary) [Dataset]. https://data.census.gov/table/ABSCS2018.AB00MYCSA01C?q=Business+and+Owner+Characteristics&g=050XX00US49027_040XX00US49&y=2018
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    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 Race for the U.S.: 2018.Table ID.ABSCS2018.AB00MYCSA01C.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) 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) 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 ...

  19. 2019 Economic Surveys: AB00MYCSA01C | Annual Business Survey: Statistics for...

    • data.census.gov
    Updated Oct 28, 2021
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    ECN (2021). 2019 Economic Surveys: AB00MYCSA01C | Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2019 (ECNSVY Annual Business Survey Company Summary) [Dataset]. https://data.census.gov/table/ABSCS2019.AB00MYCSA01C?y=2019&codeset=naics~484
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    Dataset updated
    Oct 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
    2019
    Description

    Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2019.Table ID.ABSCS2019.AB00MYCSA01C.Survey/Program.Economic Surveys.Year.2019.Dataset.ECNSVY Annual Business Survey Company Summary.Release Date.2021-10-28.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) 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) 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 2019 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-FY21-289).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/2019/.API Information.Annual Business Survey (ABS) data ...

  20. 2020 Economic Surveys: AB00MYCSA01C | Annual Business Survey: Statistics for...

    • data.census.gov
    Updated Nov 10, 2022
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    ECN (2022). 2020 Economic Surveys: AB00MYCSA01C | Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2020 (ECNSVY Annual Business Survey Company Summary) [Dataset]. https://data.census.gov/table/ABSCS2020.AB00MYCSA01C?tid=ABSCS2020.AB00MYCSA01C
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    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

    Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2020.Table ID.ABSCS2020.AB00MYCSA01C.Survey/Program.Economic Surveys.Year.2020.Dataset.ECNSVY Annual Business Survey Company Summary.Release Date.2022-11-10.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) 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) 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 2020 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-FY22-308).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/2020/.API Information.Annual Business Survey (ABS) data ...

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N. Finney; J. Nazroo; N. Shlomo; D. Kapadia; L. Becares; B. Byrne (2024). Evidence for Equality National Survey: a Survey of Ethnic Minorities During the COVID-19 Pandemic, 2021 [Dataset]. http://doi.org/10.5255/ukda-sn-9116-1

Evidence for Equality National Survey: a Survey of Ethnic Minorities During the COVID-19 Pandemic, 2021

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497 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
2024
Dataset provided by
UK Data Servicehttps://ukdataservice.ac.uk/
datacite
Authors
N. Finney; J. Nazroo; N. Shlomo; D. Kapadia; L. Becares; B. Byrne
Description
The Centre on the Dynamics of Ethnicity (CoDE), led by the University of Manchester with the Universities of St Andrews, Sussex, Glasgow, Edinburgh, LSE, Goldsmiths, King's College London and Manchester Metropolitan University, designed and carried out the Evidence for Equality National Survey (EVENS), with Ipsos as the survey partner. EVENS documents the lives of ethnic and religious minorities in Britain during the coronavirus pandemic and is, to date, the largest and most comprehensive survey to do so.

EVENS used online and telephone survey modes, multiple languages, and a suite of recruitment strategies to reach the target audience. Words of Colour coordinated the recruitment strategies to direct participants to the survey, and partnerships with 13 voluntary, community and social enterprise (VCSE) organisations[1] helped to recruit participants for the survey.

The ambition of EVENS was to better represent ethnic and religious minorities compared to existing data sources regarding the range and diversity of represented minority population groups and the topic coverage. Thus, the EVENS survey used an 'open' survey approach, which requires participants to opt-in to the survey instead of probability-based approaches that invite individuals to participate following their identification within a pre-defined sampling frame. This 'open' approach sought to overcome some of the limitations of probability-based methods in order to reach a large number and diverse mix of people from religious and ethnic minorities.

EVENS included a wide range of research and policy questions, including education, employment and economic well-being, housing, social, cultural and political participation, health, and experiences of racism and discrimination, particularly with respect to the impact of the COVID-19 pandemic. Crucially, EVENS covered a full range of racial, ethnic and religious groups, including those often unrepresented in such work (such as Chinese, Jewish and Traveller groups), resulting in the participation of 14,215 participants, including 9,702 ethnic minority participants and a general population sample of 4,513, composed of White people who classified themselves as English, Welsh, Scottish, Northern Irish, and British. Data collection covered the period between 16 February 2021 and 14 August 2021.

Further information about the study can be found on the EVENS project website.

A teaching dataset based on the main EVENS study is available from the UKDS under SN 9249.

[1] The VCSE organisations included Business in the Community, BEMIS (Scotland), Ethnic Minorities and Youth Support Team (Wales), Friends, Families and Travellers, Institute for Jewish Policy Research, Migrants' Rights Networks, Muslim Council Britain, NHS Race and Health Observatory, Operation Black Vote, Race Equality Foundation, Runnymede Trust, Stuart Hall Foundation, and The Ubele Initiative.
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