Criminology and the Use of Statistical Evidence

Criminological Theory and Statistical Data

Introduction

Criminological theory is not always based on evidence—that is, on statistical evidence. Sometimes it is based on ideas that seem logical at the time. Theorists will notice correlations in the ways in which crime emerges in certain communities and they will base their theories of crime on these observances, though no statistical evidence is actually accumulated to verify the theory. The theory simply makes sense from a logical or rational point of view and in this manner it can be promoted. Its basis of evidence is qualitative (i.e., content-related, conceptual or thematic) rather than statistical and empirical (i.e., data that can be measured, quantified and verified through testing). Broken Windows Theory is one example of criminological theory that was based on qualitative assessments rather than on statistical data (Jean, 2008). While the theory has been embraced over the years since it was first developed, other researchers have shown that statistically the data does not always support the theory. However, data can also be used to manipulate findings—i.e., a bias can be introduced into the research in terms of what type of sample is used, where data comes from and so on—and this can give the wrong impression about a theory as well. This paper will discuss the pros and cons of using statistical data in criminological theory.

Cons

The biggest con in terms of statistical data’s relationship with criminological theory is that sometimes data can be used in a way that is biased to show that a theory is correct, when a more objective compilation of statistical data will reveal the opposite (Harcourt, 1998)—or vice versa. In other words, just as thematic analysis can be manipulated in qualitative studies, statistical data can be manipulated in terms of how data is collected (a specific population or region might be over-sampled), or where crime is measured, etc. In order for statistical data to be trustworthy, it has to be objectively obtained and objectively analyzed. Anytime that bias is introduced into the equation, it alters the perceptions that follow. Statistical data is not immune to bias because it still relies upon gathering and interpreting. This is the main con associated with using statistical data in terms of criminological theory development.

The other con is that statistical data can be over-replied upon. For example, there may be an insufficient way to measure a certain phenomenon statistically speaking, but qualitatively it can be seen and understood very well. If criminological theory were only based upon statistical data, some theories would never develop that are based on qualitative assessment. Just because they are based on qualitative studies does not mean they are unworthy of the criminal justice field—because not everything can be measured quantitatively (Harcourt, 1998).

Pros

The pros of linking criminological theory to statistical data—when objectively gathered and analyzed in a non-biased manner—are that 1) it helps to support more effectively the theory that is being developed or promoted, and 2) it helps to provide more accurate details in terms of the way that theory is shaped or applied or the effect it has on communities when used to develop strategies for policing, communicating and so on.

The first pro—that it can provide greater support for the theory is based on the idea that statistical data cannot lie: the numbers speak for themselves and tell a story all their own. Individuals might exaggerate their feelings or what they view as the main problem or cause of an issue related to criminology—but the statistics will show where the truth is: they can be used to confirm or deny a report. For criminological theory, statistical data can be used to confirm or deny the theory and the extent to which it validly applies in the real world. That is the beauty of statistical data when applied corrected to criminological research: it leaves no room for guessing as one cannot argue with empirical evidence. However, it is important that researchers show how that evidence was obtained so that the study can be duplicated and its evidence validated. If a study is misleading about its data, then it can no more be trusted than the individual eye witness who exaggerates a story (Corman & Mocan, 2005).

The second pro is that statistical data helps to paint a clearer picture of what is going on in a community, how the variables and factors relate, and what ideas can be generated from this data to make a coherent theory of crime more plausible. Statistical data can help researchers to identify the specific factors that deserve more focus and more scrutiny in research and it can be used to show which variables have no statistical significance in the field with regard to a specific question. Statistical data thus helps to solidify the criminological theory.

Conclusion

Criminologists must rely upon a range of data, both qualitative and quantitative when making or developing their theories. There is no need to rely solely upon one or the other. The fact is that both qualitative data and statistical data can be used to support one another and make a theory even stronger. That is why many researchers advocate for mixed-methods approaches in research in this field.

References

Corman, H., & Mocan, N. (2005). Carrots, sticks, and broken windows. The Journal of Law and Economics, 48(1), 235-266.

Harcourt, B. E. (1998). Reflecting on the subject: A critique of the social influence conception of deterrence, the broken windows theory, and order-maintenance policing New York style. Michigan Law Review, 97(2), 291-389.

Jean, P. K. S. (2008). Pockets of crime: Broken windows, collective efficacy, and the criminal point of view. University of Chicago Press.