Data Mining for Juvenile Offenders

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1 Response

  1. Dr. leff says:

    This is not new. People have been talking about using techniques such
    as regression to predict recidivism and help judges make good sentencing
    decisions.
    Many states used very specific guidelines–I had a programming
    course with many students from my University Law Enforcement and Justice
    Administration Departments. I had the students program the guidelines
    as a real-world example of a complicated if statement.)
    rediction, sentence the juvenile to one randomly and watch the outcomes.
    d be ank going back to the sixties show that statistical approaches
    predict recidivism better than “clinical experts.”
    In six studies, statistical approaches less sophisticated than modern
    data mining, did as well as experts. In 1973, the National
    Advisory Commission on Criminal Justice Standards and Goals
    recommended the use of statistical methods in sentencing decions.
    (Caroll, John S., “Judgments of Recidivism risk: Conflicts between
    Clinical Strategies and Base-Rate Information”,
    Law and Human Behavior
    volume One, Number Two 1977,
    page 191-198.

    One question is whether the more sophisticated techniques of machine
    learning and data mining are doing a better job for
    the citizens of Florida than the techniques of
    regression that have been around for decades.
    The other question is how and when
    can human discretion be best combined with
    the dry, cold and unfeeling application of computer rules.