Offender Decision-Making: Decision Trees and Displacement, Texas, 2014-2017 (ICPSR 37116)

Version Date: Dec 20, 2018

Principal Investigator(s):
D. Kim Rossmo, Texas State University; Lucia Summers, Texas State University

https://doi.org/10.3886/ICPSR37116.v1

Version V1 ()

  • V2 [2020-01-30]
  • V1 [2018-12-20] unpublished

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Summary

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

This research expanded on offenders' decisions whether or not to offend by having explored a range of alternatives within the "not offending" category, using a framework derived from the concept of crime displacement. Decision trees were employed to analyze the multi-staged decision-making processes of criminals who are blocked from offending due to a situational crime control or prevention measure. The researchers were interested in determining how offenders evaluated displacement options as available alternatives. The data were collected through face-to-face interviews with 200 adult offenders, either in jail or on probation under the authority of the Texas Department of Criminal Justice, from 14 counties. Qualitative data collected as part of this study's methodology are not included as part of the data collection at this time.

Three datasets are included as part of this collection:

  • NIJ-2013-3454__Part1_Participants.sav (200 cases, 9 variables)
  • NIJ-2013-3454__Part2_MeasuresSurvey.sav (2415 cases, 6 variables)
  • NIJ-2013-3454__Part3_Vignettes.sav (1248 cases, 10 variables)

Demographic variables included: age, gender, race, and ethnicity.

Citation

Rossmo, D. Kim, and Summers, Lucia. Offender Decision-Making: Decision Trees and Displacement, Texas, 2014-2017. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2018-12-20. https://doi.org/10.3886/ICPSR37116.v1

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Funding

United States Department of Justice. Office of Justice Programs. National Institute of Justice (2013-R2-CX-0003)

Subject Terms

Geographic Coverage

Smallest Geographic Unit

None

Restrictions

Access to these data is restricted. Users interested in obtaining these data must complete a Restricted Data Use Agreement, specify the reason for the request, and obtain IRB approval or notice of exemption for their research.

Distributor(s)

Inter-university Consortium for Political and Social Research
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Time Period(s)

2014 -- 2017

Date of Collection

2014-11-25 -- 2016-03-24

Data Collection Notes

  1. These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

  2. Qualitative data collected for this study are not available as part of the data collection at this time.

  3. The variable PartID, Participant (offender) ID, may be used to link the datasets within this collection.
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Study Purpose

The researchers posited that studies of offender decision-making have often simplified the analysis into the decision to offend or not offend. This study explored a range of alternatives within the "not offending" category using a framework derived from the concept of crime displacement. Decision trees were employed to analyze the multi-staged decision-making processes of criminals who were blocked from offending due to a situational crime control or prevention measure. The researchers were primarily interested in how offenders evaluated displacement options as available alternatives, and posited that a better understanding of how criminals respond to crime control and prevention efforts, beyond simple desistance, could help to expand offender decision-making theory and provide insight into the efficacy of crime prevention practices.

Study Design

All data were collected through face-to-face offender interviews (n=200). The researchers employed mixed-methods design in that the interview format was designed to allow both open-ended questions as well as hypothetical scenario methods. Each interview involved three parts: (1) offender experiences; (2) a crime control measures survey; and (3) situational crime vignettes. Subjects were first asked about their experiences involving situations in which they wanted to commit a crime but chose not to do so due to a crime control or prevention measure. Next, subjects were asked to assess the effect of a standard list of 10 to 17 control/prevention measures for their particular crime type and to explain why they thought the measure did or did not have an effect. Finally, subjects were given a series of situational vignettes, each describing a prevented crime situation, followed by five displacement options (spatial, temporal, target, persist/tactical, and functional) and a desistance option. Qualitative data from the subjects' explanations and experiences was also obtained to provide a more in-depth understanding of their decisions.

Sample

Semi-structured interviews were conducted with 200 adult offenders, either in jail or on probation under the authority of the Texas Department of Criminal Justice, from 14 counties. To be included in the sample, an offender had to have a minimum of three convictions for predatory property or street crime (auto theft, vehicle burglary, residential/commercial burglary, shoplifting, or street/commercial robbery).

Time Method

Cross-sectional

Universe

Adult offenders, either in jail or on probation under the authority of the Texas Department of criminal Justice, having had a minimum of three convictions for predatory property or street crime (i.e., auto theft, vehicle burglary, residential/commercial burglary, shoplifting, or street/commercial robbery).

Unit(s) of Observation

Individual

Data Type(s)

Mode of Data Collection

Description of Variables

NIJ-2013-3454__Part1_Participants.sav

Variables include basic information about the offenders who participated in the study. The variables in this data set include a unique offender/respondent identifier, which can be used as a key variable when relating this to other datasets from this study (PartID). Apart from basic demographics (i.e., gender, age at the time of the interview, race/ethnicity), information is available about the offender's age at first arrest, and also about the offender's preferred crime type. Finally, two nominal variables indicate whether data are available for the offender form the crime control measures survey and from the situational vignettes.

NIJ-2013-3454__Part2_MeasuresSurvey.sav

The variables in this dataset relate to the data obtained from the crime prevention/control measures survey. The variables in this data set include a unique offender/respondent identifier, which can be used as a key variable when relating this to other datasets from this study (PartID). Additional variables include the crime type preferred by the offender, the crime control/prevention measures, the effect the measures had on the offender's behavior, the rank assigned based on the impact of the offender's behavior, and the offender's response to the crime control/prevention measure.

NIJ-201303454__Part3_Vignettes.sav

Variables included relate to data collected using the situational vignettes. The variables in this data set include a unique offender/respondent identifier, which can be used as a key variable when relating this to other datasets from this study (PartID). Other variables indicate the crime type and control/prevention measure the vignettes depicted, the vignette number, the behavioral responses selected by the offender and the order of preference, as well as a free text field outlining the reasons for their choice. The data in this dataset is clustered both on the individual vignette and the individual offender. Additional variables include crime type offender would displace to when engaging in functional displacement, and the effort, risk, and reward associated with the chosen behavioral response of the offender.

Response Rates

Not available

Presence of Common Scales

None

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Original Release Date

2018-12-20

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Weight

None

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