Revisiting the “Facts” of Crime

Braithwaite (1989) and Agnew (2005) argue that there are several “facts” of crime that a general theory of crime must account for. While not every Criminologist agrees with all of the facts identified by Braithwaite (1989), there are several crime correlates that have generated a consensus in the field as being top predictors of crime and delinquency. Wilson (1974) in addition to Gottfredson and Hirschi (1990) argue that while Criminologists may be good at establishing what the “facts” are, such knowledge generation is largely useless because the “facts” of crime are often invariant and do not readily lend themselves to policy action. This may be true when the identification and use of mediators are not considered. This article will focus on a select few crime “facts” including age, gender, low self-control, peers, and urbanization, as well as the potential for mediating relationships between these factors and crime and delinquency. In order to accomplish this, an explanation of what mediators are will first be provided, followed by a discussion of the influence mediators have on a select few crime “facts”.

Although crime facts, such as age, gender, low self-control, peers, and urbanization appear to be statistically related to crime and delinquency, the causal nature of such relationships has been questioned. The identification of mediating links (intermediate variables) may play an important role in explaining exactly how such correlates impact crime and delinquency. According to Kraemer and colleagues (2001), mediators are positioned between the independent and dependent variable in a sequential chain. More specifically, the mediator influences the dependent variable, while the independent variable causes variation in the mediator. Simply put, the mediator “explains how or why another variable [independent variable] affects the outcome [dependent variable]” (Kraemer et al., 2001, p. 8).

The identification of mediating variables in causal relationships allows specification in theoretical statements as to the relationship and direction that correlates have on crime and delinquency. Because of the typically discursive nature of criminological theorizing, the identification of mediating variables allows for more recursive theories to develop. For instance, the identification of the mediating link of informal social control between social disorganization and juvenile delinquency allows Shaw and McKay’s theory of Social Disorganization to be amendable to empirical testing (Kornhauser, 1978). Let us now examine how the identification of mediators facilitates the usefulness (particularly in terms of policy) of crime correlates as we revisit the “facts” of crime.

A fairly undisputed crime “fact” is age. Official and self-report data indicate that crime is usually committed by young people against young people. Furthermore, most Criminologists agree that crime peaks between the ages of 15 and 19, and then declines throughout adulthood. This does not mean that older people rarely commit crime, just that rates are highest among young people.

However, while most researchers do not dispute the existence of an agecrime curve, the meaning of this curve is debated (Steffensmeier, Allan, Harer, & Streifel, 1989). For instance, Hirschi and Gottfredson (1983) argue that the curve is reflective of frequency, with the same offenders committing more offenses which are represented by the peak (around ages 16-18). Criminal career researchers, on the other hand, argue that the curve is not a reflection of frequency (i.e., more delinquent or criminal acts being committed), but rather is the result of participation (i.e., more actors committing crime; see Laub & Sampson, 2003).

Another disagreement related to the relationship between age and crime is whether the effect is direct, or indirect and conditioned by some other variable. Laub and Sampson (2003) argue that the impact of age on crime is mediated by social bonds. In other words, an individual’s social bonds are age-graded. If an individual enters into a social role too early (e.g., teenage parenthood or early employment), this can have aversive impacts, including crime and delinquency. For example, Wright and Cullen (2002) looked specifically at the relationship between adolescent employment and delinquency and found that when adolescents entered into adult roles prematurely, they had higher rates of delinquency than did adolescents who maintained age-appropriate roles.

Another obvious correlate of crime and delinquency is gender, with a substantial gap existing in the number of crimes committed by males in comparison to females. Males are vastly over represented in crime, particularly violent crime. Roughly 80% of all criminals are male, with the exception of crimes like prostitution and some types of theft. Likewise, about 90% of arrests for murder are males. Men are also more likely to be the victims of crime, with the exception of offenses like rape or domestic violence. Official reports see larger differences in the gender gap than self report data.

While gender differences in crime and delinquency are highly supported by the research literature, few criminological theories attempt to explain such differences (for exceptions see Moffitt et al., 2001 and Hagan, Simpson, & Ellis, 1987). Recent research has indicated that the relationship between gender and crime, while not a direct causal relationship, may be conditioned by factors like opportunity and informal social control. For instance, Forde and Kennedy (1997) suggest that Gottfredson and Hirschi’s theory of self-control is capable of explaining the gender gap in offending through the interaction between opportunity and self control. In their study, they found that opportunity (which was measured by utilizing variables from routine activities theory) and control variables mediated the relationship between gender and crime. Specifically, they found that boys committed more criminal acts than girls in their sample because boys had more opportunity, while girls had more intimate handlers (i.e., were controlled by their parents) and as a result, less opportunities to commit crime.

Research consistently shows that criminals tend to have criminal friends (see Warr, 2002). In fact, association with delinquent peers is considered to be the second best predictor of delinquency. Two of the leading theoretical perspectives, control and learning, attempt to account for the relationship between peers and crime, but in contrasting ways. According to control theorists, any relationship that is found between peers and crime is spurious due to a selection effect (i.e., kids who are predisposed to delinquency are attracted to kids just like them; Hirschi, 1969). Learning theorists, on the other hand, propose that the effect of peers on crime is causal (the norms of the group encourage behavior and individuals learn delinquent definitions through their association with delinquent peers; Akers, 1998). Research, however, has found that the relationship between peers and deviance to be somewhat more complex with more support found for arguments that include both selection and causation effects (Gordon et al., 2004).

In a meta-analysis that examined a combination of 21 studies, Pratt and Cullen (2000) concluded that low self-control is one of the strongest predictors of criminality. Low self-control, according to Gottfredson and Hirschi (1990) is a latent construct comprised of several characteristics (i.e., impulsivity, insensitivity, physicality, risktaking, short-sightedness) resulting in one’s inability to delay gratification. Because crime, as well as behaviors analogous to crime (i.e., smoking, gambling, etc.), are instantly gratifying, individuals with low levels of self-control are more likely to engage in such behaviors.

While not everyone agrees that low self-control is the primary, or the sole cause of crime and delinquency, most research studies today include some type of measurement of low self-control as a control variable. In addition, while Gottfredson and Hirschi (1990) maintain that an individual’s level of self-control has a direct effect on crime and behaviors analogous to crime, other research has found support for selfcontrol as a mediating variable impacting social bonds or decision making. For example, Evans and colleagues (1997) found that adults with low self-control had weaker social bonds than did adults with higher levels of self-control.

Another well-known crime fact is urbanization. Most researchers agree that crime rates are significantly higher in urban areas than rural areas (Laub, 1998). In addition, most research finds that urban areas that have high crime rates have several things in common, including high poverty, racial heterogeneity, high levels of social mobility, high rates of family disruption, and fairly high and stable crime rates. However, Bursik (1988) and other researchers argue that Shaw and McKay did not stipulate that social disorganization has a direct effect on crime. Rather, the relationship between socially disorganized communities and crime is mediated by informal social controls. Research by Sampson and colleagues (1997) has generally supported this argument.

The identification of mediating links is also critical for the creation of policies designed to prevent and/or reduce crime. For instance, several of the well-known facts of crime (i.e., age, gender, race, and class) are static variables. In other words, they are incapable of being changed. Theorists like Gottfredson and Hirschi (1990) argue that because such variables are incapable of change, theories such as their own do not have to account for their impact on crime. However, the identification of mediating linkages between static variables and crime allows for policy efforts to focus on those factors that condition the relationship.

Cohen and Felson (1978) have done just that with their theory of routine activities. They conclude that both an individual’s age and gender impact their everyday activities, which in turn impact victimization risk. As a case-in-point, young boys go out more at night and thus have higher rates of victimization. Policies drawn from the theoretical premises of routine activities, such as increased adult supervision (i.e., increasing capable guardians) and keeping kids off the street at night by establishing curfews (i.e., reducing suitable targets), may be capable of affecting the impact of age and gender on crime.

In conclusion, Wilson may be partially correct; we cannot manipulate some of the known correlates (i.e., age and gender) of crime, but we can surely modify (through policy) the variables that mediate the link between identified correlates and crime. Similarly, Braithwaite and Agnew are correct; our theories (and our policies) need to address the “facts” of crimes. On the other hand, we need to move beyond talking about the “facts” of crime as direct risk factors of crime and delinquency and start considering the very real possibility that it is the mediating linkages between the “facts” of crime (i.e., age, gender, race, etc.) and other variables (i.e., social bonds, peers, employment, education, etc.) that have the greatest influence on crime and delinquency.

*Faculty at University of North Texas, Department of Criminal Justice

References

Agnew, R. (2005). Why do criminals offend? A general theory of crime and delinquency. Los Angeles: Roxbury Publishing.

Akers, R. L. (1998). Social learning and social structure: A general theory of crime and deviance. Boston: Northeastern University Press.

Braithwaite, J. (1989). Crime, shame, and reintegration. Cambridge: Cambridge University Press.

Bursik, R. J. (1988). Social Disorganization and theories of crime and delinquency:

Problems and prospects. Criminology, 26(4), 519-551.

Cohen, L. E., & Felson, M. (1978). Social change and crime rate trends: A routine activity approach. American Sociological Review, 44, 588-608.

Forde, D. R., & Kennedy, L. W. (1997). Risky lifestyles, routine activities, and the general theory of crime. Justice Quarterly, 14(2), 265-294.

Gottfredson, M. R., & Hirschi, T. (1990). A general theory of crime. Standford, CA: Stanford University Press.

Gordon, R. A., Lahey, B. B., Kawai, E., Loeber, R., Stouthamer-Loeber, M., & Farrington,

D. P. (2004). Antisocial behavior and youth gang membership: Selection and socialization. Criminology, 42(1), 55-88.

Hagan, J., Simpson, J., & Gillis, A. R. (1987). Class in the household: A Power-Control

Theory of gender and delinquency. The American Journal of Sociology, 92(4), 788-816.

Hirschi, T. (1969). Causes of delinquency. Berkeley: University of California Press.

Hirschi, T., & Gottfredson, M. (1983). Age and explanation of crime. The American Journal of Sociology, 89(3), 552-584.

Kornhauser, R. (1978). Social sources of delinquency. Chicago: University of Chicago Press.

Kraemer, H. C., Kazdin, A., Offord, D., & Kuper, D. (2001). How do risk factors work together? Mediators, moderators, and independent, overlapping, and proxy risk factors. American Journal of Psychiatry, 158, 848-856.

Laub, J. H., & Sampson, R. J. (2003). Shared beginnings, divergent lives: Delinquent boys to age 70. Cambridge: Harvard University Press.

Moffitt, T. E., Caspi, A., Rutter, M., & Silva, P. A. (2001). Sex differences in antisocial behavior: Conduct disorder, delinquency, and violence in the Dunedin longitudinal study. Cambridge: University Press.

Pratt, T. C., & Cullen, F. T. (2000). The empirical status of Gottfredson and Hirschi’s General Theory of Crime: A meta-analysis. Criminology, 38(3), 931-964.

Sampson, R. J., Raudenbush, S. W., & Earls, F. (1997). Neighborhoods and violent crime: A multi-level study of collective efficacy. Science, 277(5328), 918-924.

Steffensmeier, D. J., Allan, E. A., Harer, M. D., & Streifel, C. (1989). Age and the distribution of crime. The American Journal of Sociology, 94(4), 803-831.

Warr, M. (2002). Companions in crime. New York: Cambridge University Press.

Wilson, J. Q. (1974). Crime and the criminologists. Commentary, July, 47-53.

Wright, J. P., & Cullen, F. T. (2004). Employment, peers, and life-course transitions. Justice Quarterly, 21(1), 183-205.