4 datasets found
  1. m

    Emergency Assistance (EA) Family Shelter Resources and Data

    • mass.gov
    Updated Jul 9, 2025
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    Executive Office of Housing and Livable Communities (2025). Emergency Assistance (EA) Family Shelter Resources and Data [Dataset]. https://www.mass.gov/info-details/emergency-assistance-ea-family-shelter-resources-and-data
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Executive Office of Housing and Livable Communities
    Area covered
    Massachusetts
    Description

    There are several forms, regulations and data associated with the Emergency Assistance (EA) Family Shelter Program for our business partners and constituents.

  2. Rate of homelessness in the U.S. 2023, by state

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Rate of homelessness in the U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/727847/homelessness-rate-in-the-us-by-state/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    When analyzing the ratio of homelessness to state population, New York, Vermont, and Oregon had the highest rates in 2023. However, Washington, D.C. had an estimated ** homeless individuals per 10,000 people, which was significantly higher than any of the 50 states. Homeless people by race The U.S. Department of Housing and Urban Development performs homeless counts at the end of January each year, which includes people in both sheltered and unsheltered locations. The estimated number of homeless people increased to ******* in 2023 – the highest level since 2007. However, the true figure is likely to be much higher, as some individuals prefer to stay with family or friends - making it challenging to count the actual number of homeless people living in the country. In 2023, nearly half of the people experiencing homelessness were white, while the number of Black homeless people exceeded *******. How many veterans are homeless in America? The  number of homeless veterans in the United States has halved since 2010. The state of California, which is currently suffering a homeless crisis, accounted for the highest number of homeless veterans in 2022. There are many causes of homelessness among veterans of the U.S. military, including post-traumatic stress disorder (PTSD), substance abuse problems, and a lack of affordable housing.

  3. Morocco MA: Coverage: Social Safety Net Programs: Poorest Quintile: % of...

    • ceicdata.com
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    CEICdata.com, Morocco MA: Coverage: Social Safety Net Programs: Poorest Quintile: % of Population [Dataset]. https://www.ceicdata.com/en/morocco/social-protection/ma-coverage-social-safety-net-programs-poorest-quintile--of-population
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    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2009
    Area covered
    Morocco
    Variables measured
    Employment
    Description

    Morocco MA: Coverage: Social Safety Net Programs: Poorest Quintile: % of Population data was reported at 50.107 % in 2009. Morocco MA: Coverage: Social Safety Net Programs: Poorest Quintile: % of Population data is updated yearly, averaging 50.107 % from Dec 2009 (Median) to 2009, with 1 observations. Morocco MA: Coverage: Social Safety Net Programs: Poorest Quintile: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank.WDI: Social Protection. Coverage of social safety net programs shows the percentage of population participating in cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.; ; ASPIRE: The Atlas of Social Protection - Indicators of Resilience and Equity, The World Bank. Data are based on national representative household surveys. (datatopics.worldbank.org/aspire/); Simple average;

  4. c

    Causes of Homelessness among Older People in Four Cities in England, and...

    • datacatalogue.cessda.eu
    Updated Nov 28, 2024
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    Watt, H.; Byrne, K.; Crane, M., University of Sheffield; Warnes, A. M. (2024). Causes of Homelessness among Older People in Four Cities in England, and Boston, Massachusetts, 2001-2003 [Dataset]. http://doi.org/10.5255/UKDA-SN-5276-1
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    Dataset updated
    Nov 28, 2024
    Dataset provided by
    Boston Medical Center
    Sheffield Institute for Studies on Ageing
    Committee to End Elder Homelessness
    King
    Authors
    Watt, H.; Byrne, K.; Crane, M., University of Sheffield; Warnes, A. M.
    Time period covered
    Jul 1, 2001 - Aug 1, 2003
    Area covered
    England
    Variables measured
    Individuals, Cross-national, National
    Measurement technique
    Face-to-face interview, Self-completion, the 'key workers' (case managers) completed questionnaires about their assessments of the respondents’ problems and of the events and states that led to homelessness. Further clarifications and checks were made by telephone.
    Description

    Abstract copyright UK Data Service and data collection copyright owner.


    A comparative study of the causes of new episodes of homelessness among people aged 50 or more years was undertaken in Boston, Massachusetts (USA), Melbourne, Australia, and four English cities. The aims were to make a substantial contribution to the predominantly American debate on the causes of homelessness, and to make practice recommendations for the improvement of prevention.

    The study had several objectives. It aimed to collect information about the antecedents, triggers and risk factors for becoming homeless in later life and about the national and local policy and service contexts. Furthermore, the researchers aimed to analyse and interpret the findings with reference to an integrated model of the causes of homelessness that represented structural and policy factors, including housing, health and social service organisation and delivery factors, and personal circumstances, events, problems and dysfunctions. The aim was to do this collaboratively, by drawing on the project partners' experience and knowledge. Finally, it was hoped to develop recommendations for housing, primary health care and social welfare organisations for the prevention of homelessness. This was to be done by identifying the common sequences and interactions of events that precede homelessness and their markers (or 'early warning' indicators) and by holding workshops in England with practitioners and their representative organisations on new ways of working.

    By the study of contrasting welfare and philanthropic regimes in a relatively homogeneous category of homeless incidence (i.e. recent cases among late middle-aged and older people), it was hoped that valuable insights into the relative contributions of the policy, service and personal factors would be obtained. The study focused on older people who had recently become homeless, purposely to gather detailed and reliable information about the prior and contextual circumstances. To have included people who had been homeless for several years would have reduced the quality of the data because of 'recall' problems.

    Users should note that data from the Australian sample for the study are not included in this dataset.
    Main Topics:

    The data file includes information about the English respondents and those from Boston. It was compiled in two stages. The first stage involved each project partner entering the pre-coded responses into the file. All partners then identified themes and created codes for the open-ended responses, and the resulting variables were added. Data quality-control procedures included blind checks of the data coding and keying.

    The first 200 variables pertain to information collected from the respondents. They comprise descriptive variables of the circumstances prior to homelessness, including housing tenure during the three years prior to the survey, previous homelessness, employment history, income, health and addiction problems, and contacts with family, friends and formal services. The respondents were asked to rate whether specific factors were implicated in becoming homeless, and where appropriate, a following open-ended question sought elaboration.

    The remaining variables comprise information collected from the respondents' 'key workers' about their understanding of the events and states that led to their clients becoming homeless.

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Executive Office of Housing and Livable Communities (2025). Emergency Assistance (EA) Family Shelter Resources and Data [Dataset]. https://www.mass.gov/info-details/emergency-assistance-ea-family-shelter-resources-and-data

Emergency Assistance (EA) Family Shelter Resources and Data

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4 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 9, 2025
Dataset authored and provided by
Executive Office of Housing and Livable Communities
Area covered
Massachusetts
Description

There are several forms, regulations and data associated with the Emergency Assistance (EA) Family Shelter Program for our business partners and constituents.

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