How to Improve the Productivity of Crime Statistics
Publikuota 2017-06-27

Reikšminiai žodžiai

Crime statistics
victimization surveys

Kaip cituoti

AROMAA K. ir LEHTI M. (2017) „How to Improve the Productivity of Crime Statistics“, Kriminologijos studijos, 4, p. 47-71. doi: 10.15388/CrimLithuan.2016.4.10727.


Problem. Police statistics are the most comprehensive continuous database on crime in most industrialized countries. They also form an important source for quantitative criminological research. They are produced primarily for administrative use and their definitions are closely connected with national legal systems. Because of this, they comprise only a selected and biased part of crime and their comparability across jurisdictions is usually poor. This also applies to their comparability with other information sources of crime, including victimization surveys.
Aim. In this article, we demonstrate that by including a few basic descriptive variables (referring to the main characteristics of each criminal case) in the existing police data collecting systems, we can hugely improve their information value and their comparability.
Method. We have used empirical data from Finland as an example. We have coded a randomized data sample of the assault offences reported to the police in 2005 by using two descriptive variables, proposed by the Expert Group on Violence, appointed by the Finnish National Council for Crime Prevention. After that, we have compared the results with those of the 2006 National Victimization Survey that referred to the same period and used similar descriptive variables.
Results. Even using just the fe additional variables, the comparison of the two data sources gave amply new information of the measured characteristics, and in the process of both data sources. Some of the results were expected; for example, the comparison showed that violence recorded in police statistics was in terms of the injuries for men and women on average clearly more serious than the violence captured by the victimization survey. Similarly, partner violence by men had clearly been recorded in the police data more completely than partner violence by women. Some were, however, unexpected: according to our findings, for example, partner violence in private locations had the highest recording rate of the types of violence against women.
Conclusions. We are proposing that national statistics authorities adopt a simple improvement that increases the usefulness of their police crime data. The only requirements are that the database is electronic and that it records crime as individual events. The improvement is done by adding a small number or descriptive variables to the already existing variables. The descriptive variables should be about the parties involved in the offence, their relationship, and some concrete circumstances of the crime. This proposal does not require a complex reorganization of the existing information systems of police forces. The reform would only mean that a few new standard variables are introduced. Most of the required information is already known to the police, it is just not coded by using standard codes.
This reform would greatly improve the usefulness of the police crime data for purposes of crime analysis. It would also allow much better interpretations of crime trends and of regional crime differences. A further advantage of this reform would be that police-recorded crime and victimization survey data become directly comparable if they contain identical variables that describe the crime events. Our approach is not restricted by criminal codes, since we are not suggesting any changes to the recording principles currently applied. We are only suggesting additional variables. We emphasize that our proposal is much simpler and much more easily introduced than the one being currently recommended by the United Nations (International Classification of Crime 2015).


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