Criminalistic Criminological Research Center investigates repeat and serious offenders using IBM SPSS Statistics

The Hessian Police Criminalistic-Criminological Research Center

Published on 11-May-2011

Validated on 16 Aug 2013

"For us, it is the standard solution for professional statistical analyses. We have had confidence in the solution for many years and have implemented it in practice. " - Dr. Claudia Koch-Arzberger, Head of the KKFoSt.

Customer:
Kriminalistisch-Kriminologische Forschungsstelle

Industry:
Government

Deployment country:
Germany

Solution:
BA - Business Analytics, BA - Business Intelligence

Overview

Since it was established in 2004, the KKFoSt has relied exclusively on IBM SPSS Statistics for statistical data analysis.

Business need:
The Hessian Police Criminalistic-Criminological Research Center investigates the conditions and the nature of indictable offenses and crime, with a particular focus on studying serious and repeat offenders. The aim of the KKFoSt (Kriminalistisch-Kriminologische Forschungsstelle, CCRC) project is to use experience in order to optimize the way in which repeat and serious offenders are dealt with and prosecuted.

Solution:
With the help of IBM SPSS Statistics, the KKFoSt uses cluster analysis to identify repeat offenders and those who commit serious crimes.

Benefits:
• Identification of various types of repeat and serious offenders and selective categorization using cluster analysis. • Key identification of dependencies and patterns using univariate, bivariate and multivariate analytical methods. • On the basis of the MIT types identified, it was possible to derive a number of measures for investigative police work and prevention. • Prevention of criminal offenses committed by a certain type of MIT.

Case Study

Click here to read the case story in German.

As its "double-barreled" name implies, the Hessian Police Criminalistic-Criminological Research Center (KKFoSt) dedicates its activity to two academically-connected subject areas: criminology investigates the conditions and nature of indictable offenses and crime (the word "criminology" means the study of crime). Criminology draws upon academic reference disciplines, such as law, psychiatry, sociology, psychology, ethnology, anthropology and economics, to investigate its subject.

KKFoSt criminalistics analyzes the ways and means of combating individual offenses and criminal acts by means of preventive and prosecutionary measures. The aim of criminalistics is to optimize the methods, tactics and techniques for investigating, proving and preventing criminal offenses. Based on this fundamental definition of responsibilities, the KKFoSt studies a wide range of problems, always with the objective of providing answers to support the work undertaken by the police.

Within this context, the Center conducts its own research projects, or assigns them to other research institutions and ensures that the results are published. It also analyzes and documents the literature relevant to police work and provides advice to Hessian police stations.

The challenge: research into serious and repeat offenders

In its current research project "Repeat and serious offenders in Hessen," the KKFoSt is investigating the criminal biographies of repeat and serious offenders (referred to by the Research Center as MITs). MITs are usually juveniles and young adults who have committed 10 or more criminal offenses within two years and who, despite prison sentences and social rehabilitation measures, have so far not been deterred from pursuing their criminal careers. The MIT group only accounts for a small number of all criminal offenders. However, they commit a disproportionately high number of crimes. In 2007, 1502 MITs were registered in Hessen, but had committed a total of 5673 criminal offenses. The aim of the KKFoSt project is to use experience in order to optimize the way in which MITs are dealt with and prosecuted; for example, by designing "tailor-made" preventive measures, combining resources or investigating those who engage in diverse criminal activities and who have a tendency towards criminal activity.

Given the high proportion of their collective criminal activity, suppressing the criminal energy of MITs can effectively reduce the overall crime rate, and thus warrants the high level of research investment. Every offender identified, every criminal career terminated highlights ways to avoid or prevent a multitude of criminal offenses.

The solution: identifying MIT types using cluster analysis

The starting point for the KKFoSt research project is a complete inventory count of MITs. Since 2002, MITs in Hessen have been registered in accordance with the "common directives on the criminal prosecution of repeat/serious offenders in the high-volume/street crime" sector, in order to prosecute offenders more forcefully and prevent further criminal activity. The KKFoSt thus has all data at its disposal regarding the criminal careers of its "target groups": when the crimes were committed, which was the first recorded criminal activity, which sanctions or social rehabilitation programs were imposed or attempted, what the reaction was to these, which types of offenses were committed by which MITs. To complement the quantitative database, the KKFoSt conducted qualitative interviews with selected MITs.

In order to analyze the data collected and to translate it into meaningful knowledge for the police, the KKFoSt uses IBM SPSS Statistics. This software enables researchers to pre-process the structured data from the full MIT survey and the unstructured information from the interviews, so that it can be processed using univariate, bivariate and multivariate analytical methods. Key findings for the police can be extracted from the connections between the variables investigated and the patterns identified.

In this way, a cluster analysis enabled the identification of various MIT types, which could then be categorized selectively. In addition, data were analyzed on the pattern in the interdependency of variables such as disposition towards violence, as well as the type and number of crimes. On the basis of the MIT types identified, a number of measures for investigative police work and prevention were derived. For example, it was possible to make informed statements about how to prevent a certain type of MIT from committing a crime to begin with. That’s because the activity pattern of an MIT type makes it possible to identify which crimes they would normally commit, and then target their prevention.

The benefits: IBM SPSS Statistics as a standard solution for essential procedural steps in research

Since it was established in 2004, the KKFoSt has relied exclusively on IBM SPSS Statistics for statistical data analysis. "For us, it is the standard solution for professional statistical analyses. We have had confidence in the solution for many years and have implemented it in practice," explained Dr. Claudia Koch-Arzberger, Head of the KKFoSt. "A program such as IBM SPSS Statistics is essential for demanding statistical analyses, particularly multivariate analyses." Since such analyses are an essential procedural step in almost every research project, that KKFoSt conducts, IBM SPSS Statistics is part of the everyday toolset for its academic researchers. To ensure that knowledge obtained from the KKFoSt research projects is assimilated as working knowledge by the police, KKFoSt calls upon IBM SPSS Statistics´ robust reporting features. These features allow data to be formatted in such a way that police officers can intuitively comprehend the conclusions, without needing to be statistical experts.

Outlook: Research with IBM SPSS goes to the next level

IBM SPSS Statistics will remain the standard software for the KKFoSt and the basis of analysis in a multitude of research projects. As an example, the KKFoSt is currently working on a study investigating the fear of terrorism and crime. In this instance, the database to be analyzed is generated from a telephone survey undertaken with samples from the Hessian population. IBM SPSS Statistics supports not only the analysis of data requested, but also the survey concept and design.

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Products and services used

IBM products and services that were used in this case study.

Software:
SPSS Statistics Standard, SPSS Statistics Base

Legal Information

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