5 datasets found
  1. Housing Cost Burden

    • data.ca.gov
    • data.chhs.ca.gov
    • +4more
    pdf, xlsx, zip
    Updated Aug 28, 2024
    + more versions
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    California Department of Public Health (2024). Housing Cost Burden [Dataset]. https://data.ca.gov/dataset/housing-cost-burden
    Explore at:
    xlsx, pdf, zipAvailable download formats
    Dataset updated
    Aug 28, 2024
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    License

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

    Description

    This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

  2. Data from: Community Reporting Thresholds: Sharing Information with...

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Mar 12, 2025
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    National Institute of Justice (2025). Community Reporting Thresholds: Sharing Information with Authorities Concerning Terrorism and Targeted Violence, California and Illinois, 2021 [Dataset]. https://catalog.data.gov/dataset/community-reporting-thresholds-sharing-information-with-authorities-concerning-terrorism-a-04ac4
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justicehttp://nij.ojp.gov/
    Description

    Parents, siblings, partners, and friends are often the first people to suspect a loved one is on the trajectory towards targeted violence or terrorism. These intimate bystanders are well positioned to facilitate prevention efforts if there are known and trusted reporting pathways to law enforcement or other resources. Little is known in the United States about the reporting processes for intimate bystanders to targeted violence or terrorism. This study is built on previous Australian and United Kingdom studies to understand the processes of intimate bystanders in the United States, in order to inform new, localized and contextually-sensitive understandings of and approaches to community reporting issues. Qualitative-quantitative interviews were conducted from March 2021 to July 2021 virtually over Zoom with 123 community members living in California and Illinois. The researchers describe their perspectives on barriers, facilitators, and pathways. The study sought to enhance prior studies with a larger and more demographically-diverse sample. It included a focus on ISIS/Al-Qa'eda-inspired foreign-terrorism, White Power movement-inspired domestic terrorism, and--of particular relevance to the US---non-ideologically motivated targeted, workplace violence.

  3. California Historical Fire Perimeters

    • gis.data.ca.gov
    • data.ca.gov
    • +2more
    Updated Aug 29, 2024
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    California Department of Forestry and Fire Protection (2024). California Historical Fire Perimeters [Dataset]. https://gis.data.ca.gov/maps/c3c10388e3b24cec8a954ba10458039d
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    Dataset updated
    Aug 29, 2024
    Dataset authored and provided by
    California Department of Forestry and Fire Protectionhttp://calfire.ca.gov/
    Area covered
    Description

    The California Department of Forestry and Fire Protection's Fire and Resource Assessment Program (FRAP) annually maintains and distributes an historical wildland fire perimeter dataset from across public and private lands in California. The GIS data is developed with the cooperation of the United States Forest Service Region 5, the Bureau of Land Management, California State Parks, National Park Service and the United States Fish and Wildlife Service and is released in the spring with added data from the previous calendar year. Although the dataset represents the most complete digital record of fire perimeters in California, it is still incomplete, and users should be cautious when drawing conclusions based on the data. This data should be used carefully for statistical analysis and reporting due to missing perimeters (see Use Limitation in metadata). Some fires are missing because historical records were lost or damaged, were too small for the minimum cutoffs, had inadequate documentation or have not yet been incorporated into the database. Other errors with the fire perimeter database include duplicate fires and over-generalization. Additionally, over-generalization, particularly with large old fires, may show unburned "islands" within the final perimeter as burned. Users of the fire perimeter database must exercise caution in application of the data. Careful use of the fire perimeter database will prevent users from drawing inaccurate or erroneous conclusions from the data. This data is updated annually in the spring with fire perimeters from the previous fire season. This dataset may differ in California compared to that available from the National Interagency Fire Center (NIFC) due to different requirements between the two datasets. The data covers fires back to 1878. As of May 2025, it represents fire24_1. Please help improve this dataset by filling out this survey with feedback:Historic Fire Perimeter Dataset Feedback (arcgis.com)Current criteria for data collection are as follows:CAL FIRE (including contract counties) submit perimeters ≥10 acres in timber, ≥50 acres in brush, or ≥300 acres in grass, and/or ≥3 impacted residential or commercial structures, and/or caused ≥1 fatality.All cooperating agencies submit perimeters ≥10 acres.Version update:Firep24_1 was released in April 2025. Five hundred forty-eight fires from the 2024 fire season were added to the database (2 from BIA, 56 from BLM, 197 from CAL FIRE, 193 from Contract Counties, 27 from LRA, 8 from NPS, 55 from USFS and 8 from USFW). Six perimeters were added from the 2025 fire season (as a special case due to an unusual January fire siege). Five duplicate fires were removed, and the 2023 Sage was replaced with a more accurate perimeter. There were 900 perimeters that received updated attribution (705 removed “FIRE” from the end of Fire Name field and 148 replaced Complex IRWIN ID with Complex local incident number for COMPLEX_ID field). The following fires were identified as meeting our collection criteria but are not included in this version and will hopefully be added in a future update: Addie (2024-CACND-002119), Alpaugh (2024-CACND-001715), South (2024-CATIA-001375). One perimeter is missing containment date that will be updated in the next release.Cross checking CALFIRS reporting for new CAL FIRE submissions to ensure accuracy with cause class was added to the compilation process. The cause class domain description for “Powerline” was updated to “Electrical Power” to be more inclusive of cause reports.Includes separate layers filtered by criteria as follows:California Fire Perimeters (All): Unfiltered. The entire collection of wildfire perimeters in the database. It is scale dependent and starts displaying at the country level scale. Recent Large Fire Perimeters (≥5000 acres): Filtered for wildfires greater or equal to 5,000 acres for the last 5 years of fires (2020-January 2025), symbolized with color by year and is scale dependent and starts displaying at the country level scale. Year-only labels for recent large fires.California Fire Perimeters (1950+): Filtered for wildfires that started in 1950-January 2025. Symbolized by decade, and display starting at country level scale.Detailed metadata is included in the following documents:Wildland Fire Perimeters (Firep24_1) MetadataFor any questions, please contact the data steward:Kim Wallin, GIS SpecialistCAL FIRE, Fire & Resource Assessment Program (FRAP)kimberly.wallin@fire.ca.gov

  4. d

    Florida Legal Data - Court Data, Litigation Data, and Attorney Data. Contact...

    • datarade.ai
    Updated Nov 26, 2024
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    APISCRAPY (2024). Florida Legal Data - Court Data, Litigation Data, and Attorney Data. Contact APISCRAPY for all legal-related data in Florida and across the USA. [Dataset]. https://datarade.ai/data-products/florida-legal-data-court-data-litigation-data-and-attorne-apiscrapy
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    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Nov 26, 2024
    Dataset authored and provided by
    APISCRAPY
    Area covered
    United States
    Description

    APISCRAPY delivers comprehensive Florida legal data, including court data, litigation records, and attorney information, alongside legal datasets for other states like Texas, California, New York, Illinois, and more. Our AI-powered web scraping tool ensures precise data extraction and easy integration into your systems.

    Gain access to state-specific law data, including detailed information on lawyers, while reducing costs by 50% compared to traditional methods. We also offer free data samples to help you evaluate the quality of our service before committing.

    Key Features:

    Extract and process court data and litigation records specific to Florida. Verified and reliable attorney data for legal research and business insights. Automate workflows with advanced web scraping and real-time data delivery. Seamless database and BI tool integrations with no coding required. Flexible, outcome-driven pricing tailored to your needs.

    Whether you're focused on compliance, research, or market intelligence, APISCRAPY is your trusted solution for all legal data requirements in Florida and across the USA. Contact us today to get started!

  5. A

    Voice of the People, 2004

    • abacus.library.ubc.ca
    • icpsr.umich.edu
    Updated Jul 22, 2010
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    Abacus Data Network (2010). Voice of the People, 2004 [Dataset]. https://abacus.library.ubc.ca/dataset.xhtml?persistentId=hdl:11272.1/AB2/KVWJUC
    Explore at:
    txt(2010), application/x-spss-syntax(17188), pdf(170736), stc(13851760), application/x-stata-syntax(10748), bin(8239), application/x-sas-syntax(19756), tsv(6826089)Available download formats
    Dataset updated
    Jul 22, 2010
    Dataset provided by
    Abacus Data Network
    Area covered
    Netherlands, Russian Federation, Ecuador, Afghanistan, Uruguay, Peru, Uganda, Philippines, Hong Kong, Mexico
    Description

    This annual survey, fielded June to December 2004, was conducted in over 50 countries to solicit public opinion on social and political issues. Respondents were asked what they thought was the most important goal for the world as a whole, whether they trusted people from their ethnic group more than people from other ethnic groups, if they heard about various global institutions, and their thoughts of these institutions. They were also asked for their overall opinion of various countries. Respondents were asked to give their opinion on other issues such as globalization, terrorism, and democracy. They were also asked questions concerning the United States. These included whether they think American foreign policy has a positive effect or negative effect on their country, whether the United States plays a positive, negative, or neutral role in the growth of the world economy, the role the United States plays in keeping peace in the world, the role the United States plays in the fight against poverty in the world, and the role the United States plays in the protection of the environment. Additional questions addressed respondents' thoughts on whether their country was governed by the will of the people and whether elections were free and fair. Demographic information includes sex, age, education level, employment status, religious preference, household income, and type of residential area (e.g., urban or rural).

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California Department of Public Health (2024). Housing Cost Burden [Dataset]. https://data.ca.gov/dataset/housing-cost-burden
Organization logo

Housing Cost Burden

Explore at:
xlsx, pdf, zipAvailable download formats
Dataset updated
Aug 28, 2024
Dataset authored and provided by
California Department of Public Healthhttps://www.cdph.ca.gov/
License

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

Description

This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

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