Juvenile Hackers: An Empirical Test of Self-Control Theory and Social Bonding Theory

In accordance with a similar growth in information technology, computer hacking has become a pervasive issue as a form of crime worldwide in recent years. Self-control theory and social bonding theory have frequently been employed to explain various types of crimes, but rarely to explore computer hacking. Drawing from Gottfredson and Hirschi’s (1990) self-control theory and Hirschi’s (1969) social bonding theory, the purpose of this study is to empirically examine the suitability of these two theories in explaining juvenile computer hacking offenses. The self-report survey data utilized for the present study was derived from middle school and high school students in the United States, Russia, Spain, Venezuela, France, Hungary, Germany, and Poland. The current study hypothesizes that hackers’ self-control and social bonding are significant predictors for the commission of computer hacking offenses. The findings of this study provide strong support for Gottfredson and Hirschi’s (1990) self-control theory. In addition, the findings can be interpreted as partially supportive of Hirschi’s (1969) social bonding theory. The authors conclude with a discussion on policy implications

Race, Ethnicity, and Prosecution in Cook County, Illinois

The analyses reveal few differences in outcomes across racial/ ethnic groups in Cook County. When looking at case approval, dispositions, and charge reductions for all felony offenses combined, differences in the probability of specific outcomes by race/ethnicity are relatively small after accounting for other case factors such as offense severity or number of charges. For many decision points, differences in the probability of specific outcomes range from just 0 percentage points to 4 percentage points across racial/ethnic groups. When looking at specific offense types – person, weapons, property, drugs – differences in the probability of case approval, dispositions, and charge reductions across racial/ethnic groups remain relatively small. Differences in outcomes, however, are more pronounced when examining the use of alternative prosecution and the imposition of custodial sentences. For drug offenses, Black defendants are less likely than White defendants to be referred to an alternative prosecution program (e.g., deferred prosecution, drug court) – differences in the probability of entering an alternative prosecution are roughly 8 percentage points lower for Black defendants than for White defendants. In contrast, differences in the probability of entering an alternative prosecution program are just 2 percentage points lower for Hispanic defendants than for White defendants. In turn, for all offense types, Black defendants are more likely than White defendants to receive a custodial sentence following conviction – differences between Black and White defendants in the probability of custodial sentence range from 6 percentage points for property offenses to 21 percentage points for drug offenses. Again, the probability of receiving a custodial sentence following conviction is more similar for Hispanic and White defendants. Despite these findings, there are limitations to the analyses that prevent drawing strong conclusions. First, the analyses are unable to account for differences in defendant eligibility for alternative prosecution programs, defendant interest in such programs, economic or geographic barriers to participation in alternative prosecution programs – factors that may explain differences in outcomes across groups. Second, the analyses are unable to account for differences in defendant criminal history – a factor that affects both eligibility for alternative prosecution and the imposition of custodial sentences. Differences in criminal history across racial/ethnic groups likely explain much of the difference in custodial sentences across these groups; as such, these results should be viewed very cautiously. There are additional findings to consider beyond differences across racial/ethnic groups. For example, the no probable cause rates and dismissal rates for felony drug cases both appear to be high: roughly 11% of felony drug cases receive a finding of no probable cause and 32% are dismissed (nolle pros). Felony drug cases are unique since they are direct filed by law enforcement and do not go through felony review; thus, after case initiation or at preliminary hearing is the first opportunity a prosecutor has to review a case, which explains some of the higher rates. Relative to other offense types, however, the rates appear high even after accounting for the proportion of person, weapons, and property cases rejected at felony review. The findings suggest opportunities to conserve resources and reduce the burden on defendants by examining how felony drug cases enter the system and how long it takes to dismiss such cases