8 datasets found
  1. Data from: Assessing Identity Theft Offenders' Strategies and Perceptions of...

    • icpsr.umich.edu
    • datasets.ai
    • +1more
    Updated Mar 31, 2009
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    Copes, Heith; Vieraitis, Lynne (2009). Assessing Identity Theft Offenders' Strategies and Perceptions of Risk in the United States, 2006-2007 [Dataset]. http://doi.org/10.3886/ICPSR20622.v1
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    Dataset updated
    Mar 31, 2009
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Copes, Heith; Vieraitis, Lynne
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/20622/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/20622/terms

    Time period covered
    Mar 2006 - Feb 2007
    Area covered
    United States
    Description

    The purpose of this study was to examine the crime of identity theft from the offenders' perspectives. The study employed a purposive sampling strategy. Researchers identified potential interview subjects by examining newspapers (using Lexis-Nexis), legal documents (using Lexis-Nexis and Westlaw), and United States Attorneys' Web sites for individuals charged with, indicted, and/or sentenced to prison for identity theft. Once this list was generated, researchers used the Federal Bureau of Prisons (BOP) Inmate Locator to determine if the individuals were currently housed in federal facilities. Researchers visited the facilities that housed the largest number of inmates on the list in each of the six regions in the United States as defined by the BOP (Western, North Central, South Central, North Eastern, Mid-Atlantic, and South Eastern) and solicited the inmates housed in these prisons. A total of 14 correctional facilities were visited and 65 individuals incarcerated for identity theft or identity theft related crimes were interviewed between March 2006 and February 2007. Researchers used semi-structured interviews to explore the offenders' decision-making processes. When possible, interviews were audio recorded and then transcribed verbatim. Part 1 (Quantitative Data) includes the demographic variables age, race, gender, number of children, highest level of education, and socioeconomic class while growing up. Other variables include prior arrests or convictions and offense type, prior drug use and if drug use contributed to identity theft, if employment facilitated identity theft, if they went to trial or plead to charges, and sentence length. Part 2 (Qualitative Data), includes demographic questions such as family situation while growing up, highest level of education, marital status, number of children, and employment status while committing identity theft crimes. Subjects were asked about prior criminal activity and drug use. Questions specific to identity theft include the age at which the person became involved in identity theft, how many identities he or she had stolen, if they had worked with other people to steal identities, why they had become involved in identity theft, the skills necessary to steal identities, and the perceived risks involved in identity theft.

  2. Data from: Study of Race, Crime, and Social Policy in Oakland, California,...

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
    + more versions
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    National Institute of Justice (2025). Study of Race, Crime, and Social Policy in Oakland, California, 1976-1982 [Dataset]. https://catalog.data.gov/dataset/study-of-race-crime-and-social-policy-in-oakland-california-1976-1982-b8cd2
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justicehttp://nij.ojp.gov/
    Area covered
    Oakland, California
    Description

    In 1980, the National Institute of Justice awarded a grant to the Cornell University College of Human Ecology for the establishment of the Center for the Study of Race, Crime, and Social Policy in Oakland, California. This center mounted a long-term research project that sought to explain the wide variation in crime statistics by race and ethnicity. Using information from eight ethnic communities in Oakland, California, representing working- and middle-class Black, White, Chinese, and Hispanic groups, as well as additional data from Oakland's justice systems and local organizations, the center conducted empirical research to describe the criminalization process and to explore the relationship between race and crime. The differences in observed patterns and levels of crime were analyzed in terms of: (1) the abilities of local ethnic communities to contribute to, resist, neutralize, or otherwise affect the criminalization of its members, (2) the impacts of criminal justice policies on ethnic communities and their members, and (3) the cumulative impacts of criminal justice agency decisions on the processing of individuals in the system. Administrative records data were gathered from two sources, the Alameda County Criminal Oriented Records Production System (CORPUS) (Part 1) and the Oakland District Attorney Legal Information System (DALITE) (Part 2). In addition to collecting administrative data, the researchers also surveyed residents (Part 3), police officers (Part 4), and public defenders and district attorneys (Part 5). The eight study areas included a middle- and low-income pair of census tracts for each of the four racial/ethnic groups: white, Black, Hispanic, and Asian. Part 1, Criminal Oriented Records Production System (CORPUS) Data, contains information on offenders' most serious felony and misdemeanor arrests, dispositions, offense codes, bail arrangements, fines, jail terms, and pleas for both current and prior arrests in Alameda County. Demographic variables include age, sex, race, and marital status. Variables in Part 2, District Attorney Legal Information System (DALITE) Data, include current and prior charges, days from offense to charge, disposition, and arrest, plea agreement conditions, final results from both municipal court and superior court, sentence outcomes, date and outcome of arraignment, disposition, and sentence, number and type of enhancements, numbers of convictions, mistrials, acquittals, insanity pleas, and dismissals, and factors that determined the prison term. For Part 3, Oakland Community Crime Survey Data, researchers interviewed 1,930 Oakland residents from eight communities. Information was gathered from community residents on the quality of schools, shopping, and transportation in their neighborhoods, the neighborhood's racial composition, neighborhood problems, such as noise, abandoned buildings, and drugs, level of crime in the neighborhood, chances of being victimized, how respondents would describe certain types of criminals in terms of age, race, education, and work history, community involvement, crime prevention measures, the performance of the police, judges, and attorneys, victimization experiences, and fear of certain types of crimes. Demographic variables include age, sex, race, and family status. For Part 4, Oakland Police Department Survey Data, Oakland County police officers were asked about why they joined the police force, how they perceived their role, aspects of a good and a bad police officer, why they believed crime was down, and how they would describe certain beats in terms of drug availability, crime rates, socioeconomic status, number of juveniles, potential for violence, residential versus commercial, and degree of danger. Officers were also asked about problems particular neighborhoods were experiencing, strategies for reducing crime, difficulties in doing police work well, and work conditions. Demographic variables include age, sex, race, marital status, level of education, and years on the force. In Part 5, Public Defender/District Attorney Survey Data, public defenders and district attorneys were queried regarding which offenses were increasing most rapidly in Oakland, and they were asked to rank certain offenses in terms of seriousness. Respondents were also asked about the public's influence on criminal justice agencies and on the performance of certain criminal justice agencies. Respondents were presented with a list of crimes and asked how typical these offenses were and what factors influenced their decisions about such cases (e.g., intent, motive, evidence, behavior, prior history, injury or loss, substance abuse, emotional trauma). Other variables measured how often and under what circumstances the public defender and client and the public defender and the district attorney agreed on the case, defendant characteristics in terms of who should not be put on the stand, the effects of Proposition 8, public defender and district attorney plea guidelines, attorney discretion, and advantageous and disadvantageous characteristics of a defendant. Demographic variables include age, sex, race, marital status, religion, years of experience, and area of responsibility.

  3. a

    Percent Non-Hispanic White

    • hub.arcgis.com
    Updated Nov 5, 2021
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    OC Public Works (2021). Percent Non-Hispanic White [Dataset]. https://hub.arcgis.com/maps/OCPW::percent-non-hispanic-white-1
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    Dataset updated
    Nov 5, 2021
    Dataset authored and provided by
    OC Public Works
    Area covered
    Description

    Original census file name: tl_2020_

  4. f

    Absolute changes in life expectancy at age 20 among people in prisons, by...

    • plos.figshare.com
    xls
    Updated Feb 6, 2025
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    Bryan L. Sykes; Ernest K. Chavez; Justin D. Strong (2025). Absolute changes in life expectancy at age 20 among people in prisons, by race & sex across periods, 2000–2014. [Dataset]. http://doi.org/10.1371/journal.pone.0314197.t001
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    xlsAvailable download formats
    Dataset updated
    Feb 6, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Bryan L. Sykes; Ernest K. Chavez; Justin D. Strong
    License

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

    Description

    Absolute changes in life expectancy at age 20 among people in prisons, by race & sex across periods, 2000–2014.

  5. a

    CVAP Percent Non-Hispanic Asian

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Nov 5, 2021
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    OC Public Works (2021). CVAP Percent Non-Hispanic Asian [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/OCPW::cvap-percent-non-hispanic-asian-1
    Explore at:
    Dataset updated
    Nov 5, 2021
    Dataset authored and provided by
    OC Public Works
    Area covered
    Description

    Original census file name: tl_2020_

  6. a

    Percent Non-Hispanic Asian

    • data-ocpw.opendata.arcgis.com
    Updated Nov 5, 2021
    + more versions
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    OC Public Works (2021). Percent Non-Hispanic Asian [Dataset]. https://data-ocpw.opendata.arcgis.com/datasets/percent-non-hispanic-asian-1
    Explore at:
    Dataset updated
    Nov 5, 2021
    Dataset authored and provided by
    OC Public Works
    Area covered
    Description

    Original census file name: tl_2020_

  7. Ethnocultural Offenders in Federal Custody: In-Custody Indicators among Men

    • ouvert.canada.ca
    • datasets.ai
    • +1more
    html
    Updated May 5, 2025
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    Correctional Service of Canada (2025). Ethnocultural Offenders in Federal Custody: In-Custody Indicators among Men [Dataset]. https://ouvert.canada.ca/data/dataset/852e0d98-678a-48c0-ab5e-61307f27637f
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    htmlAvailable download formats
    Dataset updated
    May 5, 2025
    Dataset provided by
    Correctional Service of Canadahttp://www.csc-scc.gc.ca/
    License

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

    Description

    The Correctional Service of Canada (CSC) has an ethnoculturally diverse offender population. Study 2 of a three-part study examined differences with respect to in-custody indicators among ethnocultural, White, and Indigenous offenders. It is important to identify differences as they can inform CSC of areas for further examination and action to support a diverse offender population.

  8. f

    Model results for zero-inflated Poisson regression (NESARC-III, 2012–2013).

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 13, 2023
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    George Pro; Ricky Camplain; Charles H. Lea III (2023). Model results for zero-inflated Poisson regression (NESARC-III, 2012–2013). [Dataset]. http://doi.org/10.1371/journal.pone.0268987.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOS ONE
    Authors
    George Pro; Ricky Camplain; Charles H. Lea III
    License

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

    Description

    Model results for zero-inflated Poisson regression (NESARC-III, 2012–2013).

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Copes, Heith; Vieraitis, Lynne (2009). Assessing Identity Theft Offenders' Strategies and Perceptions of Risk in the United States, 2006-2007 [Dataset]. http://doi.org/10.3886/ICPSR20622.v1
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Data from: Assessing Identity Theft Offenders' Strategies and Perceptions of Risk in the United States, 2006-2007

Related Article
Explore at:
Dataset updated
Mar 31, 2009
Dataset provided by
Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
Authors
Copes, Heith; Vieraitis, Lynne
License

https://www.icpsr.umich.edu/web/ICPSR/studies/20622/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/20622/terms

Time period covered
Mar 2006 - Feb 2007
Area covered
United States
Description

The purpose of this study was to examine the crime of identity theft from the offenders' perspectives. The study employed a purposive sampling strategy. Researchers identified potential interview subjects by examining newspapers (using Lexis-Nexis), legal documents (using Lexis-Nexis and Westlaw), and United States Attorneys' Web sites for individuals charged with, indicted, and/or sentenced to prison for identity theft. Once this list was generated, researchers used the Federal Bureau of Prisons (BOP) Inmate Locator to determine if the individuals were currently housed in federal facilities. Researchers visited the facilities that housed the largest number of inmates on the list in each of the six regions in the United States as defined by the BOP (Western, North Central, South Central, North Eastern, Mid-Atlantic, and South Eastern) and solicited the inmates housed in these prisons. A total of 14 correctional facilities were visited and 65 individuals incarcerated for identity theft or identity theft related crimes were interviewed between March 2006 and February 2007. Researchers used semi-structured interviews to explore the offenders' decision-making processes. When possible, interviews were audio recorded and then transcribed verbatim. Part 1 (Quantitative Data) includes the demographic variables age, race, gender, number of children, highest level of education, and socioeconomic class while growing up. Other variables include prior arrests or convictions and offense type, prior drug use and if drug use contributed to identity theft, if employment facilitated identity theft, if they went to trial or plead to charges, and sentence length. Part 2 (Qualitative Data), includes demographic questions such as family situation while growing up, highest level of education, marital status, number of children, and employment status while committing identity theft crimes. Subjects were asked about prior criminal activity and drug use. Questions specific to identity theft include the age at which the person became involved in identity theft, how many identities he or she had stolen, if they had worked with other people to steal identities, why they had become involved in identity theft, the skills necessary to steal identities, and the perceived risks involved in identity theft.

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