Presenters

Jacob RybakFollow

Disciplines

Applied Statistics | Categorical Data Analysis | Criminology and Criminal Justice | Social Justice

Abstract (300 words maximum)

What leads to an offender to go back to prison? Iowa has collected data tracking recidivism to evaluate the effectiveness of its programs for released offenders. This data set includes the following for all of the offenders: age groups, type of release (parole vs being discharged at the end of their sentence), race, sex, year of release, supervising district, original offense, and whether they recidivated. For the offenders who return to prison, the data set includes measures on days to return, type of recidivism (technicality or new crime), and what the specific offense was that caused their return.

In the past, this data set was used to predict whether an offender will recidivate. My research focuses on investigating the interrelationships between the variables. I will use nonparametric and parametric hypothesis tests with post hoc comparisons. In addition, I will use statistical graphical displays to convey my findings. I approach this research through the lens of a person who was in the Georgia Department of Corrections from age 18 to 22. My personal experience and insights have given me a heightened understanding of the issues facing offenders released from prison.

The relationships I will investigate include the following: Does race of the offender predict the days to return to prison? Is there a relationship between original offense and the returning offense? Do some original offense types return more quickly than others? How do the different release types affect whether an offender recidivates or the days to return if they do? Does sex predict whether an offender recidivates or the days to return if they do? Prison reform is complicated but if people, especially those of us who are ex-offenders, join forces to find solutions, more offenders will join me in being rehabilitated and reformed.

Academic department under which the project should be listed

CCSE - Data Science and Analytics

Primary Investigator (PI) Name

Susan Mathews Hardy

Additional Faculty

Dr. Austin Brown, Statistics & Analytical Sciences, abrow708@kennesaw.edu

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Why Does an Ex-Offender Reoffend?

What leads to an offender to go back to prison? Iowa has collected data tracking recidivism to evaluate the effectiveness of its programs for released offenders. This data set includes the following for all of the offenders: age groups, type of release (parole vs being discharged at the end of their sentence), race, sex, year of release, supervising district, original offense, and whether they recidivated. For the offenders who return to prison, the data set includes measures on days to return, type of recidivism (technicality or new crime), and what the specific offense was that caused their return.

In the past, this data set was used to predict whether an offender will recidivate. My research focuses on investigating the interrelationships between the variables. I will use nonparametric and parametric hypothesis tests with post hoc comparisons. In addition, I will use statistical graphical displays to convey my findings. I approach this research through the lens of a person who was in the Georgia Department of Corrections from age 18 to 22. My personal experience and insights have given me a heightened understanding of the issues facing offenders released from prison.

The relationships I will investigate include the following: Does race of the offender predict the days to return to prison? Is there a relationship between original offense and the returning offense? Do some original offense types return more quickly than others? How do the different release types affect whether an offender recidivates or the days to return if they do? Does sex predict whether an offender recidivates or the days to return if they do? Prison reform is complicated but if people, especially those of us who are ex-offenders, join forces to find solutions, more offenders will join me in being rehabilitated and reformed.