36 datasets found
  1. Under Age 65 Disability Diagnoses of Supplemental Security Income (SSI)...

    • catalog.data.gov
    Updated Dec 24, 2022
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    Social Security Administration (2022). Under Age 65 Disability Diagnoses of Supplemental Security Income (SSI) Recipients by Census Area - December 2010 [Dataset]. https://catalog.data.gov/dataset/under-age-65-disability-diagnoses-of-supplemental-security-income-ssi-recipients-by-census
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    Dataset updated
    Dec 24, 2022
    Dataset provided by
    Social Security Administrationhttp://ssa.gov/
    Description

    The Under Age 65 Disability Diagnoses of Supplemental Security Income (SSI) Recipients by Census Area is produced using the data found in Table 38 from the SSI Annual Statistical Report of 2010. This file contains 9 age groups in 4 regions defined by the U.S. Census Bureau by sex and by 23 diagnostic groups.

  2. A

    ‘Under Age 65 Disability Diagnoses of Supplemental Security Income (SSI)...

    • analyst-2.ai
    Updated Dec 15, 2010
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2010). ‘Under Age 65 Disability Diagnoses of Supplemental Security Income (SSI) Recipients by Census Area, December 2010’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-under-age-65-disability-diagnoses-of-supplemental-security-income-ssi-recipients-by-census-area-december-2010-2649/375e7ae9/?iid=003-539&v=presentation
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    Dataset updated
    Dec 15, 2010
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Under Age 65 Disability Diagnoses of Supplemental Security Income (SSI) Recipients by Census Area, December 2010’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/2734f2ee-00fe-4177-941e-da79efd0886b on 26 January 2022.

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

    The Under Age 65 Disability Diagnoses of Supplemental Security Income (SSI) Recipients by Census Area (December 2010) is produced using the data found in Table 38 from the SSI Annual Statistical Report of 2010. This file contains 9 age groups in 4 regions defined by the U.S. Census Bureau by sex and by 23 diagnostic groups.

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

  3. VetPop2023 Urban/Rural by Poverty & Disability FY2023-2025

    • catalog.data.gov
    • datahub.va.gov
    • +1more
    Updated Apr 2, 2025
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    Department of Veterans Affairs (2025). VetPop2023 Urban/Rural by Poverty & Disability FY2023-2025 [Dataset]. https://catalog.data.gov/dataset/vetpop2023-urban-rural-by-poverty-disability-fy2023-2025
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    Dataset updated
    Apr 2, 2025
    Dataset provided by
    United States Department of Veterans Affairshttp://va.gov/
    Description

    The Department of Veterans Affairs provides official estimates and projections of the Veteran population using the Veteran Population Projection Model (VetPop). Based on the latest model VetPop2023 and the most recent national survey estimates from the 2023 American Community Survey 1-Year (ACS) data, the projected number of Veterans living in the 50 states, DC and Puerto Rico for fiscal years, 2023 to 2025, are allocated to Urban and Rural areas. As defined by the Census Bureau, Rural encompasses all population, housing, and territory not included within an Urban area (https://www.census.gov/programs-surveys/geography/guidance/geo-areas/urban-rural.html). This table contains the Veteran estimates by urban/rural, age group, poverty, and disability. The poverty level and disability are determined by ACS based on responses on total income and functional difficulties. Refer to the sections on Poverty and Disability Status in the document, https://www2.census.gov/programs-surveys/acs/tech_docs/subject_definitions/2023_ACSSubjectDefinitions.pdf Note: rounding to the nearest 1,000 is always appropriate for VetPop estimates.

  4. Aug 2007 Current Population Survey: Veterans Supplement

    • catalog.data.gov
    • datasets.ai
    Updated Sep 19, 2023
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    U.S. Census Bureau (2023). Aug 2007 Current Population Survey: Veterans Supplement [Dataset]. https://catalog.data.gov/dataset/aug-2007-current-population-survey-veterans-supplement
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    Dataset updated
    Sep 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    Provides data for veterans of the United States on Vietnam-theater and Persian Gulf-theater status, service-connected income, effect of a service-connected disability on current labor force participation and participation in veterans’ programs.

  5. 4/16 Daily Covid 19 & 2018 5Y ACS County Subset

    • kaggle.com
    Updated Apr 18, 2020
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    James Tourkistas (2020). 4/16 Daily Covid 19 & 2018 5Y ACS County Subset [Dataset]. https://www.kaggle.com/datasets/jtourkis/john-hopkins-416-daily-covid-19-acs-2018-5y/code
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 18, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    James Tourkistas
    Description

    Context

    Dataset aims to further a county by county comparison of potential risk factors that could heighten Covid 19 transmission rates or deaths. It includes a subset of county by county American Community Survey (ACS) estimates of: race/ethnicity demographics, income levels, poverty characteristics, industry information, work transportation, general population over 60 characteristics, and select housing characteristics. It also includes 4/16 Daily Spread Estimates from John Hopkins.

    Content

    The data includes information on:

    1) General and Over 60 county level indicators for race, poverty level, housing size, sources of income, employment status, whether living alone, language barriers, immigration status, and disability status. 2) Modes of Transportation Stats 3) County Level Industry Stats

    Acknowledgements

    Note: ACS five year estimates are selections limited to counties with populations over 20,000. https://www.census.gov/programs-surveys/acs/guidance/estimates.html

    Link to ACS/Census Tables:

    https://data.census.gov/cedsci/table?q=United%20States&tid=ACSDP1Y2018.DP05&hidePreview=true&vintage=2018&layer=VT_2018_040_00_PY_D1&cid=S0103_C01_001E

    Source of John Hopkins Daily Virus Spread Data: https://github.com/CSSEGISandData/COVID-19

    Inspiration

    I hope this data will help bring people closer to figuring out what economic factors correlate to or influence disease spread.

  6. A

    Broadband Adoption and Computer Use by year, state, demographic...

    • data.amerigeoss.org
    • datadiscoverystudio.org
    • +1more
    csv, json, rdf, xml
    Updated Jul 27, 2019
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    United States[old] (2019). Broadband Adoption and Computer Use by year, state, demographic characteristics [Dataset]. https://data.amerigeoss.org/zh_CN/dataset/broadband-adoption-and-computer-use-by-year-state-demographic-characteristics
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    xml, json, rdf, csvAvailable download formats
    Dataset updated
    Jul 27, 2019
    Dataset provided by
    United States[old]
    Description

    This dataset is imported from the US Department of Commerce, National Telecommunications and Information Administration (NTIA) and its "Data Explorer" site. The underlying data comes from the US Census

    1. dataset: Specifies the month and year of the survey as a string, in "Mon YYYY" format. The CPS is a monthly survey, and NTIA periodically sponsors Supplements to that survey.

    2. variable: Contains the standardized name of the variable being measured. NTIA identified the availability of similar data across Supplements, and assigned variable names to ease time-series comparisons.

    3. description: Provides a concise description of the variable.

    4. universe: Specifies the variable representing the universe of persons or households included in the variable's statistics. The specified variable is always included in the file. The only variables lacking universes are isPerson and isHouseholder, as they are themselves the broadest universes measured in the CPS.

    5. A large number of *Prop, *PropSE, *Count, and *CountSE columns comprise the remainder of the columns. For each demographic being measured (see below), four statistics are produced, including the estimated proportion of the group for which the variable is true (*Prop), the standard error of that proportion (*PropSE), the estimated number of persons or households in that group for which the variable is true (*Count), and the standard error of that count (*CountSE).

    DEMOGRAPHIC CATEGORIES

    1. us: The usProp, usPropSE, usCount, and usCountSE columns contain statistics about all persons and households in the universe (which represents the population of the fifty states and the District and Columbia). For example, to see how the prevelance of Internet use by Americans has changed over time, look at the usProp column for each survey's internetUser variable.

    2. age: The age category is divided into five ranges: ages 3-14, 15-24, 25-44, 45-64, and 65+. The CPS only includes data on Americans ages 3 and older. Also note that household reference persons must be at least 15 years old, so the age314* columns are blank for household-based variables. Those columns are also blank for person-based variables where the universe is "isAdult" (or a sub-universe of "isAdult"), as the CPS defines adults as persons ages 15 or older. Finally, note that some variables where children are technically in the univese will show zero values for the age314* columns. This occurs in cases where a variable simply cannot be true of a child (e.g. the workInternetUser variable, as the CPS presumes children under 15 are not eligible to work), but the topic of interest is relevant to children (e.g. locations of Internet use).

    3. work: Employment status is divided into "Employed," "Unemployed," and "NILF" (Not in the Labor Force). These three categories reflect the official BLS definitions used in official labor force statistics. Note that employment status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by work status, even if they are otherwise considered part of the universe for the variable of interest.

    4. income: The income category represents annual family income, rather than just an individual person's income. It is divided into five ranges: below $25K, $25K-49,999, $50K-74,999, $75K-99,999, and $100K or more. Statistics by income group are only available in this file for Supplements beginning in 2010; prior to 2010, family income range is available in public use datasets, but is not directly comparable to newer datasets due to the 2010 introduction of the practice of allocating "don't know," "refused," and other responses that result in missing data. Prior to 2010, family income is unkown for approximately 20 percent of persons, while in 2010 the Census Bureau began imputing likely income ranges to replace missing data.

    5. education: Educational attainment is divided into "No Diploma," "High School Grad," "Some College," and "College Grad." High school graduates are considered to include GED completers, and those with some college include community college attendees (and graduates) and those who have attended certain postsecondary vocational or technical schools--in other words, it signifies additional education beyond high school, but short of attaining a bachelor's degree or equivilent. Note that educational attainment is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by education, even if they are otherwise considered part of the universe for the variable of interest.

    6. sex: "Male" and "Female" are the two groups in this category. The CPS does not currently provide response options for intersex individuals.

    7. race: This category includes "White," "Black," "Hispanic," "Asian," "Am Indian," and "Other" groups. The CPS asks about Hispanic origin separately from racial identification; as a result, all persons identifying as Hispanic are in the Hispanic group, regardless of how else they identify. Furthermore, all non-Hispanic persons identifying with two or more races are tallied in the "Other" group (along with other less-prevelant responses). The Am Indian group includes both American Indians and Alaska Natives.

    8. disability: Disability status is divided into "No" and "Yes" groups, indicating whether the person was identified as having a disability. Disabilities screened for in the CPS include hearing impairment, vision impairment (not sufficiently correctable by glasses), cognitive difficulties arising from physical, mental, or emotional conditions, serious difficulty walking or climbing stairs, difficulty dressing or bathing, and difficulties performing errands due to physical, mental, or emotional conditions. The Census Bureau began collecting data on disability status in June 2008; accordingly, this category is unavailable in Supplements prior to that date. Note that disability status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by disability status, even if they are otherwise considered part of the universe for the variable of interest.

    9. metro: Metropolitan status is divided into "No," "Yes," and "Unkown," reflecting information in the dataset about the household's location. A household located within a metropolitan statistical area is assigned to the Yes group, and those outside such areas are assigned to No. However, due to the risk of de-anonymization, the metropolitan area status of certain households is unidentified in public use datasets. In those cases, the Census Bureau has determined that revealing this geographic information poses a disclosure risk. Such households are tallied in the Unknown group.

    10. scChldHome:

  7. H

    Survey of Income and Program Participation Core and Disability

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Mar 6, 2018
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    Alan Jette (2018). Survey of Income and Program Participation Core and Disability [Dataset]. http://doi.org/10.7910/DVN/5ZBH5B
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 6, 2018
    Dataset provided by
    Harvard Dataverse
    Authors
    Alan Jette
    License

    https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.7910/DVN/5ZBH5Bhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.7910/DVN/5ZBH5B

    Description

    The Survey of Income and Program Participation (SIPP) is a large panel study of civilian non-institutionalized U.S. citizens. Conducted by the U.S. Census Bureau, SIPP provides detailed income and other economic resource distribution information for the U.S. population. Using these data, program analysts, policy makers, or other researchers can then predict assistance program eligibility rates. The survey focuses primarily on improving data on people who are economically at risk: poor or near-poor people and middle-income people who, if they lost a spouse, parent or job, would likely experience economic deprivation and might then require federal assistance. Secondary to this core set of information, SIPP adds question modules about a variety of policy related topics. This user's guide pertains to SIPP's overlapping cross-sectional core data and modules on disability from the 1992 and 1993 panels. The Survey of Income and Program Participation, Core and Disability Modules, 1992-1993 contains data on 98,395 cases across 1,494 variables.

  8. V

    Median Income, Home Value and Residential Property Taxes in NJ Census Tracts...

    • odgavaprod.ogopendata.com
    • data.virginia.gov
    csv
    Updated Feb 13, 2024
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    Datathon 2024 (2024). Median Income, Home Value and Residential Property Taxes in NJ Census Tracts -New Jersey [Dataset]. https://odgavaprod.ogopendata.com/dataset/median-income-home-value-and-residential-property-taxes-in-nj-census-tracts-new-jersey
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    csv(396092)Available download formats
    Dataset updated
    Feb 13, 2024
    Dataset authored and provided by
    Datathon 2024
    Area covered
    New Jersey
    Description

    This layer was developed for public use of the most current median household income, median home value and median owner-occupied residential real estate taxes compiled by the US Census Bureau from the 2017 to 2021 American Community Survey at the Census Tract (neighborhood) level.

    All data are 2020 Census Tract (neighborhood) level five-year estimates from the U.S. Census Bureau American Community Survey from 2017 to 2021. Median household income earned in the past 12 months. Includes wage or salary income; net self-employment income; interest, dividends, or net rental or royalty income or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); public assistance or welfare payments; retirement, survivor, or disability pensions; and all other income. Median home value (an estimate of how much the property would sell for if it were for sale) for properties owned, being bought, vacant for sale, or sold but not occupied at the time of the survey. Data are based on values reported by property owners. Median real estate taxes (due to all taxing jurisdictions) for owner-occupied properties are based on taxes reported by homeowners to the Census Bureau in the American Community Survey from 2017 to 2021.

  9. Data from: Current Population Survey: Veterans Supplement

    • s.cnmilf.com
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • +1more
    Updated Jul 19, 2023
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    U.S. Census Bureau (2023). Current Population Survey: Veterans Supplement [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/current-population-survey-veterans-supplement-a9db2
    Explore at:
    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    Provides data for veterans of the United States on Vietnam-theater and Persian Gulf-theater status, service-connected income, effect of a service-connected disability on current labor force participation and participation in veterans' programs.

  10. Census of Population and Housing, 1990: Summary Tape File 3C

    • archive.ciser.cornell.edu
    Updated Jan 6, 2020
    + more versions
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    Bureau of the Census (2020). Census of Population and Housing, 1990: Summary Tape File 3C [Dataset]. http://doi.org/10.6077/9nnp-b653
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    Dataset updated
    Jan 6, 2020
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    Bureau of the Census
    Variables measured
    HousingUnit, Individual
    Description

    Summary Tape File 3C contains summaries for the entire United States. The collection provides sample data weighted to represent the total population and also contains 100-percent counts and unweighted sample counts for total persons and total housing units. Additional population and housing variables include age, ancestry, disability, citizenship, education, income, marital status, race, sex, travel time to work, rent, tenure, value of housing unit, number of vehicles, and monthly owner costs. The collection provides 178 population tables and 99 housing tables. The geographic hierarchy includes the following levels: United States, region, division, state, county, county subdivision, place with 10,000 or more persons, consolidated city, Alaska Native Regional Corporation, Metropolitan Statistical Area, and Urbanized Area. (Source: downloaded from ICPSR 7/13/10)

    This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR06054.v1. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

  11. CDPHE Composite Socio-Demographic Dataset (County)

    • data.colorado.gov
    • healthdata.gov
    • +1more
    csv, xlsx, xml
    Updated Mar 31, 2017
    + more versions
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    CDPHE - Department of Public Health and Environment; U.S. Census American Community Survey (2017). CDPHE Composite Socio-Demographic Dataset (County) [Dataset]. https://data.colorado.gov/Health/CDPHE-Composite-Socio-Demographic-Dataset-County-/rcsh-y5k8
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    xml, csv, xlsxAvailable download formats
    Dataset updated
    Mar 31, 2017
    Dataset provided by
    Colorado Department of Public Health and Environmenthttps://cdphe.colorado.gov/
    Authors
    CDPHE - Department of Public Health and Environment; U.S. Census American Community Survey
    Description

    This county geography dataset includes selected indicators (2011-2015 5-Year Averages) pertaining to population, age, race/ethnicity, language, housing, poverty/income, education, disability, health insurance, employment, and age*race*gender groups. This dataset is assembled annually from the U.S. Census American Community Survey American Factfinder website and is maintained by the Colorado Department of Public Health and Environment.

  12. Data from: RAND Center for Population Health and Health Disparities (CPHHD)...

    • icpsr.umich.edu
    ascii, delimited, sas +2
    Updated Oct 21, 2011
    + more versions
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    Escarce, Jose J.; Lurie, Nicole; Jewell, Adria (2011). RAND Center for Population Health and Health Disparities (CPHHD) Data Core Series: Decennial Census Abridged, 1990-2010 [United States] [Dataset]. http://doi.org/10.3886/ICPSR27866.v1
    Explore at:
    ascii, stata, delimited, spss, sasAvailable download formats
    Dataset updated
    Oct 21, 2011
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Escarce, Jose J.; Lurie, Nicole; Jewell, Adria
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/27866/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/27866/terms

    Area covered
    Mississippi, Washington, Idaho, New Mexico, Pennsylvania, Minnesota, Puerto Rico, Massachusetts, Missouri, Rhode Island
    Description

    The RAND Center for Population Health and Health Disparities (CPHHD) Data Core Series is composed of a wide selection of analytical measures, encompassing a variety of domains, all derived from a number of disparate data sources. The CPHHD Data Core's central focus is on geographic measures for census tracts, counties, and Metropolitan Statistical Areas (MSAs) from two distinct geo-reference points, 1990 and 2000. The current study, Decennial Census Abridged, has two cross-sectional datasets, one longitudinal (interpolated) dataset, and one longitudinal (extrapolated) dataset containing a large number and variety of population and housing characteristics-related measures. These data are summarized at five different geographic levels: tract, county (FIPS), county (Geographic), MSA (Geographic), and state. The following types of measures constructed from the Census Bureau Population and Housing Characteristics data are included in the data for this collection: housing characteristics (stock, quality, ownership, costs, expenditures, occupancy, etc.), crowding (housing and population density), urbanicity, racial and ethnic composition, language, nationality, and citizenship. Further measures cover family/household structure, transportation, educational attainment, labor force, employment status, disabilities, income, poverty, and demographics (e.g., age, gender, and race).

  13. a

    Median Income, Home Value and Residential Property Taxes in NJ Census Tracts...

    • hub.arcgis.com
    • njogis-newjersey.opendata.arcgis.com
    Updated Mar 2, 2023
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    NJ Department of Community Affairs (2023). Median Income, Home Value and Residential Property Taxes in NJ Census Tracts [Dataset]. https://hub.arcgis.com/datasets/709328735a5849d891ff3478e7559a56
    Explore at:
    Dataset updated
    Mar 2, 2023
    Dataset authored and provided by
    NJ Department of Community Affairs
    Area covered
    Description

    All data are 2020 Census Tract (neighborhood) level five-year estimates from the U.S. Census Bureau American Community Survey from 2017 to 2021. Median household income earned in the past 12 months. Includes wage or salary income; net self-employment income; interest, dividends, or net rental or royalty income or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); public assistance or welfare payments; retirement, survivor, or disability pensions; and all other income. Median home value (an estimate of how much the property would sell for if it were for sale) for properties owned, being bought, vacant for sale, or sold but not occupied at the time of the survey. Data are based on values reported by property owners. Median real estate taxes (due to all taxing jurisdictions) for owner-occupied properties are based on taxes reported by homeowners to the Census Bureau in the American Community Survey from 2017 to 2021.

  14. d

    DSS Benefit and Payment Recipient Demographics - quarterly data

    • data.gov.au
    • researchdata.edu.au
    .xlsx, csv +3
    Updated May 30, 2025
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    Department of Social Services (2025). DSS Benefit and Payment Recipient Demographics - quarterly data [Dataset]. https://data.gov.au/data/dataset/dss-payment-demographic-data
    Explore at:
    xlsx(1096182), csv, xlsx(1620878), excel (.xlsx)(1612709), xlsx(1474650), xlsx(1613556), xlsx, excel (.xlsx)(1035515), excel (.xlsx)(1825047), excel (.xlsx), xlsx(1556969), excel (.xlsx)(544421), excel (.xlsx)(1100863), xlsx(1128550), xlsx(1054524), excel (.xlsx)(2317250), excel (.xlsx)(2322747), xlsx(1615572), excel (.xlsx)(1334077), excel (.xlsx)(2319953), excel (.xlsx)(1593519), xlsx(1328672), xlsx(1572129), xlsx(1556837), xlsx(1534161), xlsx(1057446), excel (xlsx)(1619658), excel (.xlsx)(1549173), excel (.xlsx)(1618018), xlsx(1293409), xlsx(1371015), xlsx(1582550), excel (.xlsx)(1646224), excel (.xlsx)(2337811), .xlsx(1582185), excel (.xlsx)(1383273), excel (.xlsx)(1719096), excel (.xlsx)(1620917), excel (.xlsx)(1566083), excel (.xlsx)(1091961), xlsx(1318808)Available download formats
    Dataset updated
    May 30, 2025
    Dataset authored and provided by
    Department of Social Services
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    The DSS Payment Demographic data set is made up of:

    Selected DSS payment data by

    • Geography: state/territory, electorate, postcode, LGA and SA2 (for 2015 onwards)

    • Demographic: age, sex and Indigenous/non-Indigenous

    • Duration on Payment (Working Age & Pensions)

    • Duration on Income Support (Working Age, Carer payment & Disability Support Pension)

    • Rate (Working Age & Pensions)

    • Earnings (Working Age & Pensions)

    • Age Pension assets data

    • JobSeeker Payment and Youth Allowance (other) Principal Carers

    • Activity Tested Recipients by Partial Capacity to Work (NSA,PPS & YAO)

    • Exits within 3, 6 and 12 months (Newstart Allowance/JobSeeker Payment, Parenting Payment, Sickness Allowance & Youth Allowance)

    • Disability Support Pension by medical condition

    • Care Receiver by medical conditions

    • Commonwealth Rent Assistance by Payment type and Income Unit type have been added from March 2017. For further information about Commonwealth Rent Assistance and Income Units see the Data Descriptions and Glossary included in the dataset.

    From December 2022, the "DSS Expanded Benefit and Payment Recipient Demographics – quarterly data" publication has introduced expanded reporting populations for income support recipients. As a result, the reporting population for Jobseeker Payment and Special Benefit has changed to include recipients who are current but on zero rate of payment and those who are suspended from payment. The reporting population for ABSTUDY, Austudy, Parenting Payment and Youth Allowance has changed to include those who are suspended from payment. The expanded report will replace the standard report after June 2023.

    Additional data for DSS Expanded Benefit and Payment Recipient Demographics – quarterly data includes:

    • A new contents page to assist users locate the information within the spreadsheet

    • Additional data for the ‘Suspended’ population in the ‘Payment by Rate’ tab to enable users to calculate the old reporting rules.

    • Additional information on the Employment Earning by ‘Income Free Area’ tab.

    From December 2022, Services Australia have implemented a change in the Centrelink payment system to recognise gender other than the sex assigned at birth or during infancy, or as a gender which is not exclusively male or female. To protect the privacy of individuals and comply with confidentialisation policy, persons identifying as ‘non-binary’ will initially be grouped with ‘females’ in the period immediately following implementation of this change. The Department will monitor the implications of this change and will publish the ‘non-binary’ gender category as soon as privacy and confidentialisation considerations allow.

    Local Government Area has been updated to reflect the Australian Statistical Geography Standard (ASGS) 2022 boundaries from June 2023.

    Commonwealth Electorate Division has been updated to reflect the Australian Statistical Geography Standard (ASGS) 2021 boundaries from June 2023.

    SA2 has been updated to reflect the Australian Statistical Geography Standard (ASGS) 2021 boundaries from June 2023.

    From December 2021, the following are included in the report:

    • selected payments by work capacity, by various demographic breakdowns

    • rental type and homeownership

    • Family Tax Benefit recipients and children by payment type

    • Commonwealth Rent Assistance by proportion eligible for the maximum rate

    • an age breakdown for Age Pension recipients

    For further information, please see the Glossary.

    From June 2021, data on the Paid Parental Leave Scheme is included yearly in June releases. This includes both Parental Leave Pay and Dad and Partner Pay, across multiple breakdowns. Please see Glossary for further information.

    From March 2017 the DSS demographic dataset will include top 25 countries of birth. For further information see the glossary.

    From March 2016 machine readable files containing the three geographic breakdowns have also been published for use in National Map, links to these datasets are below:

    Pre June 2014 Quarter Data contains:

    Selected DSS payment data by

    • Geography: state/territory; electorate; postcode and LGA

    • Demographic: age, sex and Indigenous/non-Indigenous

    Note: JobSeeker Payment replaced Newstart Allowance and other working age payments from 20 March 2020, for further details see: https://www.dss.gov.au/benefits-payments/jobseeker-payment

    For data on DSS payment demographics as at June 2013 or earlier, the department has published data which was produced annually. Data is provided by payment type containing timeseries’, state, gender, age range, and various other demographics. Links to these publications are below:

    Concession card data in the March and June 2020 quarters have been re-stated to address an over-count in reported cardholder numbers.

    28/06/2024 – The March 2024 and December 2023 reports were republished with updated data in the ‘Carer Receivers by Med Condition’ section, updates are exclusive to the ‘Care Receivers of Carer Payment recipients’ table, under ‘Intellectual / Learning’ and ‘Circulatory System’ conditions only.

  15. Priority Neighborhoods (2022 ACS) - OakDOT Geographic Equity Toolbox

    • data.oaklandca.gov
    csv, xlsx, xml
    Updated Oct 29, 2024
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    City of Oakland, United States Census Bureau (2024). Priority Neighborhoods (2022 ACS) - OakDOT Geographic Equity Toolbox [Dataset]. https://data.oaklandca.gov/Equity-Indicators/Priority-Neighborhoods-2022-ACS-OakDOT-Geographic-/p29u-9pdx
    Explore at:
    csv, xlsx, xmlAvailable download formats
    Dataset updated
    Oct 29, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    City of Oakland, United States Census Bureau
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    The Priority Neighborhoods dataset is a part of the City of Oakland Department of Transportation's (OakDOT's) Geographic Equity Toolbox. The Priority Neighborhoods GIS dataset relies upon demographic data from the American Community Survey (ACS). This dataset assigns each census tract in Oakland a numerical priority value and a quantile from lowest and highest, as determined by the following seven weighted demographic factors (with weights in brackets "[XX%]"): • People of Color [25%] • Low-income Households (<50% of Area Median Income for a 4-person household) [25%] • People with Disability [10%] • Seniors 65 Years and Over [10%] • Single Parent Families [10%] • Severely Rent-Burdened Households [10%] • Low Educational Attainment (less than a bachelor's degree) [10%]

    This dataset was last updated in October 2024 with data from the 2022 5-year (i.e., averaged from 2018 through 2022) American Community Survey (ACS). The ACS is managed by the United States Census Bureau; learn more about the ACS at: https://www.census.gov/programs-surveys/acs.

    See the online map and read the methodology at: https://www.oaklandca.gov/resources/oakdot-geographic-equity-toolbox. This dataset is maintained by the OakDOT Race and Equity Team; learn more about the team at: https://www.oaklandca.gov/topics/oakdot-race-and-equity-team.

    Field Descriptions: • TRACT: Census Tract Number • QUINTILE: Priority Quintile (calculated) • PLAN_AREA: OakDOT Planning Area • POPULATION: Population (average from 2018 through 2022) • PCT_POC: Percent People of Color • PCT_INC: Percent Low Income • PCT_SRB: Percent Severely Rent-Burdened • PCT_PWD: People with a Disability • PCT_SENIOR: Percent Seniors • PCT_SPH: Percent Single Parent Households • PCT_EDU: Percent Low Educational Attainment • RAT_POC: Ratio of People of Color (compared to Citywide average) • RAT_INC: Ratio of Low Income (compared to Citywide average) • RAT_SRB: Ratio of Severely Rent-Burdened (compared to Citywide average) • RAT_PWD: Ratio of People with a Disability (compared to Citywide average) • RAT_SENIOR: Ratio of Seniors (compared to Citywide average) • RAT_SPH: Ratio of Single Parent Households (compared to Citywide average) • RAT_EDU: Ratio of Low Educational Attainment (compared to Citywide average) • RAT_SCORE: Priority Ratio (compared to Citywide average) • ALAND: Land Area in square feet

    City of Oakland, Department of Transportation (OakDOT) 250 Frank H. Ogawa Plaza, Suite 4314 | Oakland, CA 94612

  16. V

    HRTPO Transportation-Vulnerable Communities

    • data.virginia.gov
    • hrgeo.org
    • +1more
    Updated Nov 25, 2024
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    Hampton Roads PDC & Hampton Roads TPO (2024). HRTPO Transportation-Vulnerable Communities [Dataset]. https://data.virginia.gov/dataset/hrtpo-transportation-vulnerable-communities
    Explore at:
    html, geojson, zip, csv, arcgis geoservices rest api, kmlAvailable download formats
    Dataset updated
    Nov 25, 2024
    Dataset provided by
    HRPDC & HRTPO
    Authors
    Hampton Roads PDC & Hampton Roads TPO
    Description

    StoryMap link:https://arcg.is/1OXPW1

    This dataset contains the Hampton Roads Transportation Planning Organization (HRTPO) 9 Environmental Justice (EJ) Indicators (Carless Households, Cash Public Assistance Households, Disabled Population, Elderly Population, Female Head of Household, Food Stamps/SNAP Household, Limited English Proficiency Population, Minority Population, and Low-Income/Poverty Households) at the Census Block Group level. The U.S. Census data source uses the 2017-2021 ACS 5-Year Estimates. The dataset includes Youth Population, which is not an EJ Indicator but is used in the Transportation Challenges and Strategies Long-Range Transportation Plan (LRTP) report. This data will be used for the HRTPO 2050 LRTP, for planning purposes only.

    Title VI - Environmental Justice Framework

    Applied to 2050 Long-Range Transportation Plan

    Introduction
    Providing equitable access to transportation is essential for thriving communities. Below are federal regulations to help foster transportation equity.
    Title VI of the Civil Rights Act prohibits discrimination based on race, color, and national origin in programs and activities receiving federal financial assistance.
    Environmental Justice (EJ) is the fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income with respect to the development, implementation, and enforcement of environmental laws, regulations, and policies. The Environmental Justice Executive Order 12898, signed in 1994, reinforces the requirements of Title VI.
    Transportation-Vulnerability Key Indicators
    The following transportation-vulnerability key indicators were used to identify individuals or households that may experience varying degrees of disadvantage in transportation accessibility and/or the transportation planning process:
    • Minority
    • Low-Income Households
    • Households Receiving Cash Public Assistance
    • Households Receiving Food Stamps
    • Carless Households
    • Disabled Populations
    • Elderly Populations
    • Female Heads of Household
    • Limited English Proficiency Households
    Transportation-Vulnerable Communities
    Using US Census Bureau’s 2017-2021 American Community Survey data, each transportation-vulnerability key indicator was assessed by census block groups, the smallest available geography for the identified key indicators, and compared to regional averages. Any census block group with an average key indicator equal to or higher than the regional average for that indicator is identified as a transportation-vulnerable community.

    The dataset contains the 9 EJ Indicators used for the HRTPO Title VI/EJ Analysis and the 2050 LRTP. The field names/aliases will change based on what platform the user is viewing the data (e.g., ArcMap, ArcPro, ArcGIS Online, Microsoft Excel, etc.). The suggestion is to view 'Field Alias Names'. To help preserve the field names and descriptions and to help the user understand the data, the following list contains the field names, field alias names, and field descriptions: (EXAMPLE: Field Name = Field Alias Name. Field Description.).

    OBJECTID = OBJECTID. Unique integer field used to identify rows in tables in a geodatabase uniquely. ESRI ArcMap/ArcPro automatically defines this field.

    Shape = Shape. The type of shape for the data. In this case, the EJ data are all 2021 Census Block Group (CBG) polygons. ESRI ArcMap/ArcPro automatically defines this field.

    GEOID = Census GEOID. Census numeric codes that uniquely identify all administrative/legal and statistical geographic areas. In this case, the EJ data are all 2021 CBGs.

    GEOID_1 = Census GEOID - Joined. Census numeric codes that uniquely identify all administrative/legal and statistical geographic areas. In this case, the EJ data are all 2021 CBGs.

    Block_Grou = Census Block Group. CBG is a geographical unit used by the U.S. Census Bureau which is between the Census Tract and the Census Block levels.

    TAZ = Transportation Analysis Zones (TAZ). HRTPO Transportation Analysis Zones (TAZs) that spatially join with the CBGs. Each CBG has a TAZ that intersects/overlays with the HRTPO TAZs.

    Locality = Locality. Locality name: the dataset includes 16 localities (Cities of Chesapeake, Franklin, Hampton, Newport News, Norfolk, Poquoson, Portsmouth, Suffolk, Virginia Beach, and Williamsburg, and the Counties of Gloucester, Isle of Wight, James City, Southampton, Surry*, and York). The HRTPO/MPO Boundary does not include Surry County, but the data is included for HRPDC/MPA purposes.

    Total_Popu = Total Population. Census Total Population.

    Total_Hous = Total Households. Census Total Households.

    Carless_To = Carless Total. Total Carless Households. Households with no vehicles available.

    Carless_Re = Carless regional Avg. Carless Households regional average.

    Carless_BG = Carless BG Avg. Carless Households Census Block Group average.

    Carless_AB = Carless Above Avg (Yes/No). Carless Households above the regional average. No = Not an EJ Community, Yes = EJ Community.

    Carless_Nu = Carless Numeric Value (0/1). Carless Households numerical value. 0 = Not an EJ Community, 1 = EJ Community.

    Cash_Assis = Cash Public Assistance Total. Total Households Receiving Cash Public Assistance (CPA). household that received either cash assistance or in-kind benefits.

    Cash_Ass_1 = Cash Public Assistance Regional Avg. CPA Households regional average.

    Cash_Ass_2 = Cash Public Assistance BG Avg. CPA Households Census Block Group average.

    Cash_Ass_3 = Cash Assistance Above Avg (Yes/No). CPA Households above the regional average. No = Not an EJ Community, Yes = EJ Community.

    CPA_Num = Cash Public Assistance Numeric Value (0/1). CPA Households numerical value. 0 = Not an EJ Community, 1 = EJ Community.

    Disability = Disability Total. Total Disabled Populations. non-institutionalized persons identified as having a disability of the following basic areas of functioning - hearing, vision, cognition, and ambulation.

    Disabili_1 = Disability Regional Avg. Disabled Populations regional average.

    Disabili_2 = Disability BG Average. Disabled Populations Census Block Group average.

    Disabili_3 = Disability Above Avg (Yes/No). Disabled Populations above the regional average. No = Not an EJ Community, Yes = EJ Community.

    Disabili_4 = Disability Numeric Value (0/1). Disabled Populations numerical value. 0 = Not an EJ Community, 1 = EJ Community.

    Elderly_To = Elderly Total. Total Elderly Populations. People who are aged 65 and older.

    Elderly_Re = Elderly Region Avg. Elderly Population regional average.

    Elderly_BG = Elderly BG Avg. Elderly Population Census Block Group avg.

    Elderly_Ab = Elderly Above Avg (Yes/No). Elderly Population above the regional average. No = Not an EJ Community, Yes = EJ Community.

    Elderly_Num = Elderly Numeric Value (0/1). Elderly Population numerical value. 0 = Not an EJ Community, 1 = EJ Community.

    Female_HoH = Female Head of Households Total. Total Female Head of Households. Households where females are the head of households with children present and no husband present.

    Female_H_1 = Female Head of Households Regional Avg. Female Head of Households regional average.

    Female_H_2 = Female Head of Households BG Avg. Female Head of Households Census Block Group average.

    Female_H_3 = Female Head of Households Above Avg (Yes/No). Female Head of Households above the regional average. No = Not an EJ Community, Yes = EJ Community.

    FemaleHoH_ = Female Head of Households Numeric Value (0/1). Female Head of Households numerical value. 0 = Not an EJ Community, 1 = EJ Community.

    Food_Stamp = Food Stamps Total. Total Households receiving Food Stamps. Households that received Supplemental Nutrition Assistance Program (SNAP) or Food Stamps.

    Food_Sta_1 = Food Stamps Region Avg. Food Stamps Households regional average.

    Food_Sta_2 = Food Stamps BG Avg. Food Stamps Households Census Block Group average.

    Food_Sta_3 = Food Stamps Above Avg (Yes/No). Food Stamps Households above the regional average. No = Not an EJ Community, Yes = EJ Community.

    FoodStamps = Food Stamps Numeric Value (0/1). Food Stamps Households numerical value. 0 = Not an EJ Community, 1 = EJ Community.

    Limited_En = Limited English Proficiency Total. Total Limited English

  17. g

    Census of Population and Housing, 2000 [United States]: Summary File 4,...

    • search.gesis.org
    Updated Feb 26, 2021
    + more versions
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    United States Department of Commerce. Bureau of the Census (2021). Census of Population and Housing, 2000 [United States]: Summary File 4, District of Columbia - Version 1 [Dataset]. http://doi.org/10.3886/ICPSR13520.v1
    Explore at:
    Dataset updated
    Feb 26, 2021
    Dataset provided by
    ICPSR - Interuniversity Consortium for Political and Social Research
    GESIS search
    Authors
    United States Department of Commerce. Bureau of the Census
    License

    https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de457436https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de457436

    Area covered
    Washington, United States
    Description

    Abstract (en): Summary File 4 (SF 4) from the United States 2000 Census contains the sample data, which is the information compiled from the questions asked of a sample of all people and housing units. Population items include basic population totals: urban and rural, households and families, marital status, grandparents as caregivers, language and ability to speak English, ancestry, place of birth, citizenship status, year of entry, migration, place of work, journey to work (commuting), school enrollment and educational attainment, veteran status, disability, employment status, industry, occupation, class of worker, income, and poverty status. Housing items include basic housing totals: urban and rural, number of rooms, number of bedrooms, year moved into unit, household size and occupants per room, units in structure, year structure built, heating fuel, telephone service, plumbing and kitchen facilities, vehicles available, value of home, monthly rent, and shelter costs. In Summary File 4, the sample data are presented in 213 population tables (matrices) and 110 housing tables, identified with "PCT" and "HCT" respectively. Each table is iterated for 336 population groups: the total population, 132 race groups, 78 American Indian and Alaska Native tribe categories (reflecting 39 individual tribes), 39 Hispanic or Latino groups, and 86 ancestry groups. The presentation of SF4 tables for any of the 336 population groups is subject to a population threshold. That is, if there are fewer than 100 people (100-percent count) in a specific population group in a specific geographic area, and there are fewer than 50 unweighted cases, their population and housing characteristics data are not available for that geographic area in SF4. For the ancestry iterations, only the 50 unweighted cases test can be performed. See Appendix H: Characteristic Iterations, for a complete list of characteristic iterations. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.. All persons in housing units in the District of Columbia in 2000. 2013-05-25 Multiple Census data file segments were repackaged for distribution into a single zip archive per dataset. No changes were made to the data or documentation.2006-01-12 All files were removed from dataset 342 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 341 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 340 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 339 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 338 and flagged as study-level files, so that they will accompany all downloads. Because of the number of files per state in Summary File 4, ICPSR has given each state its own ICPSR study number in the range ICPSR 13512-13563. The study number for the national file is 13570. Data for each state are being released as they become available.The data are provided in 38 segments (files) per iteration. These segments are PCT1-PCT4, PCT5-PCT16, PCT17-PCT34, PCT35-PCT37, PCT38-PCT45, PCT46-PCT49, PCT50-PCT61, PCT62-PCT67, PCT68-PCT71, PCT72-PCT76, PCT77-PCT78, PCT79-PCT81, PCT82-PCT84, PCT85-PCT86 (partial), PCT86 (partial), PCT87-PCT103, PCT104-PCT120, PCT121-PCT131, PCT132-PCT137, PCT138-PCT143, PCT144, PCT145-PCT150, PCT151-PCT156, PCT157-PCT162, PCT163-PCT208, PCT209-PCT213, HCT1-HCT9, HCT10-HCT18, HCT19-HCT22, HCT23-HCT25, HCT26-HCT29, HCT30-HCT39, HCT40-HCT55, HCT56-HCT61, HCT62-HCT70, HCT71-HCT81, HCT82-HCT86, and HCT87-HCT110. The iterations are Parts 1-336, the Geographic Header File is Part 337. The Geographic Header File is in fixed-format ASCII and the table files are in comma-delimited ASCII format. A merged iteration will have 7,963 variables.For Parts 251-336, the part names contain numbers within parentheses that refer to the Ancestry Code List (page G1 of the codebook).

  18. Census of Population and Housing, 2000: Summary File 3, Alabama

    • archive.ciser.cornell.edu
    Updated Jun 1, 2024
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    Bureau of the Census (2024). Census of Population and Housing, 2000: Summary File 3, Alabama [Dataset]. http://doi.org/10.6077/rfnf-p929
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    Dataset updated
    Jun 1, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    Bureau of the Census
    Variables measured
    HousingUnit, Individual
    Description

    Summary File 3 contains sample data, which is the information compiled from the questions asked of a sample of all people and housing units in the United States. Population items include basic population totals as well as counts for the following characteristics: urban and rural, households and families, marital status, grandparents as caregivers, language and ability to speak English, ancestry, place of birth, citizenship status, year of entry, migration, place of work, journey to work (commuting), school enrollment and educational attainment, veteran status, disability, employment status, industry, occupation, class of worker, income, and poverty status. Housing items include basic housing totals and counts for urban and rural, number of rooms, number of bedrooms, year moved into unit, household size and occupants per room, units in structure, year structure built, heating fuel, telephone service, plumbing and kitchen facilities, vehicles available, value of home, and monthly rent and shelter costs. The Summary File 3 population tables are identified with a "P" prefix and the housing tables are identified with an "H," followed by a sequential number. The "P" and "H" tables are shown for the block group and higher level geography, while the "PCT" and "HCT" tables are shown for the census tract and higher level geography. There are 16 "P" tables, 15 "PCT" tables, and 20 "HCT" tables that bear an alphabetic suffix on the table number, indicating that they are repeated for nine major race and Hispanic or Latino groups. There are 484 population tables and 329 housing tables for a total of 813 unique tables. (Source: downloaded from ICPSR 7/13/10)

    Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR13342.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

  19. Income of individuals by disability status, age group, sex and income source...

    • www150.statcan.gc.ca
    • canwin-datahub.ad.umanitoba.ca
    • +2more
    Updated May 1, 2025
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    Government of Canada, Statistics Canada (2025). Income of individuals by disability status, age group, sex and income source [Dataset]. http://doi.org/10.25318/1110008801-eng
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    Dataset updated
    May 1, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Income of individuals by disability status, age group, sex and income source, Canada, annual.

  20. Decennial Census: State Legislative District Demographic Profile (Sample)

    • catalog.data.gov
    Updated Jul 19, 2023
    + more versions
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    U.S. Census Bureau (2023). Decennial Census: State Legislative District Demographic Profile (Sample) [Dataset]. https://catalog.data.gov/dataset/decennial-census-state-legislative-district-demographic-profile-sample
    Explore at:
    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The State Legislative District Summary File (Sample) (SLDSAMPLE) contains the sample data, which is the information compiled from the questions asked of a sample of all people and housing units. Population items include basic population totals; urban and rural; households and families; marital status; grandparents as caregivers; language and ability to speak English; ancestry; place of birth, citizenship status, and year of entry; migration; place of work; journey to work (commuting); school enrollment and educational attainment; veteran status; disability; employment status; industry, occupation, and class of worker; income; and poverty status. Housing items include basic housing totals; urban and rural; number of rooms; number of bedrooms; year moved into unit; household size and occupants per room; units in structure; year structure built; heating fuel; telephone service; plumbing and kitchen facilities; vehicles available; value of home; monthly rent; and shelter costs. The file contains subject content identical to that shown in Summary File 3 (SF 3).

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Social Security Administration (2022). Under Age 65 Disability Diagnoses of Supplemental Security Income (SSI) Recipients by Census Area - December 2010 [Dataset]. https://catalog.data.gov/dataset/under-age-65-disability-diagnoses-of-supplemental-security-income-ssi-recipients-by-census
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Under Age 65 Disability Diagnoses of Supplemental Security Income (SSI) Recipients by Census Area - December 2010

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Dataset updated
Dec 24, 2022
Dataset provided by
Social Security Administrationhttp://ssa.gov/
Description

The Under Age 65 Disability Diagnoses of Supplemental Security Income (SSI) Recipients by Census Area is produced using the data found in Table 38 from the SSI Annual Statistical Report of 2010. This file contains 9 age groups in 4 regions defined by the U.S. Census Bureau by sex and by 23 diagnostic groups.

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