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Over the last few decades, specialized courts have received an increasing amount of research attention. The existing literature mostly supports drug courts and demonstrates their effectiveness in reducing recidivism and substance abuse, more generally (Belenko, 1998; Bouffard & Richardson, 2007;

Over the last few decades, specialized courts have received an increasing amount of research attention. The existing literature mostly supports drug courts and demonstrates their effectiveness in reducing recidivism and substance abuse, more generally (Belenko, 1998; Bouffard & Richardson, 2007; Gottfredson, Najaka, & Kearley, 2003). Whether the drug court model “works” across offender subgroups remains an open empirical question. The current study uses data originally collected by Rossman and colleagues (2003-2009) for the Multi-Site Adult Drug Court Evaluation (MADCE) to examine the effect of drug court participation on recidivism among unique offender subgroups. First, a context-specific risk score is used to examine recidivism outcomes. Second, offender subgroups are statistically created using latent class analysis (LCA). Recidivism outcomes are then assessed by subgroup, with these results compared to the initial measure of risk. Both analyses are performed using the full sample of drug court participants and the comparison groups. Finally, the third model uses a split sample analysis by court participation to explore the full effects of drug court. The findings of the present study contribute to the theoretical literature and help inform future policy regarding risk assessment and the treatment of offenders in drug courts.
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    Title
    • Specialized Drug Court Participation Across Offender Subtypes
    Contributors
    Date Created
    2018
    Resource Type
  • Text
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    Note
    • thesis
      Partial requirement for: M.S., Arizona State University, 2018
    • bibliography
      Includes bibliographical references (pages 45-52)
    • Field of study: Criminology and Criminal Justice

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    Statement of Responsibility

    by Shayla Fordyce

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