INCENTIVES FOR COLLECTIVE DEVIANCE: GROUP SIZE AND CHANGES IN PERCEIVED RISK,COST, AND REWARD*

Research has demonstrated that the presence of others shifts decision‐making about risky/deviant behavior. One reason for this shift could be changes in the anticipated experience of formal sanctions, informal costs, and rewards. To investigate this possibility, this study conducted two randomized controlled trials with hypothetical vignettes, in which a range of how many other people were also involved in the criminal act defined the treatment conditions. Across two samples of university students (Ns = 396 and 263), the results revealed that as the size of the involved group increased, the anticipated experience of sanction risk and several informal social costs associated with engaging in the act decreased, and the anticipated experience of two rewards increased. Additional analyses suggest that, with one exception in each data set, these changes are not only tied to the solo/group distinction.     

RETHINKING THE “NORM” OF OFFENDER GENERALITY: INVESTIGATING SPECIALIZATION IN THE SHORT‐TERM

The life‐course approach to criminal career research has devoted a good deal of attention to the generality or specialization of offending behavior. Typically, extant research demonstrates versatility on the part of offenders, yet such findings could be attributable, at least in part, to time and measurement aggregation bias. This work uses a temporally disaggregated and individualized measure of diversity in offending to determine whether the previous findings of generality hold up to shifts in methodology. Using data from a sample of serious felons, results indicated that the magnitude of specialization is greater than in prior studies. Regression results indicated that certain demographic and local life‐circumstance variables are related to the extent of diversity. Theoretical and methodological implications are identified and discussed.     

IN SEARCH OF A DEPENDENT VARIABLE: COMMENT ON AVAKAME, 1998*

In a previous Criminology article, Avakame (1998) applies hierarchical linear modeling (HLM) techniques to Supplementary Homicide Reports (SHR) to disentangle individual‐ and aggregate‐level factors associated with offending. A close reading of his analysis reveals serious flaws in the dependent variable, which renders the results meaningless. Although it is ambiguous whether Avakame intended to model homicide “risk” or “frequency,” either is problematic. “Homicide frequency” has no logical connection to the individual‐level predictors; “homicide risk” is constant in SHR data, which makes the analysis impossible. In detailing these problems, we spell out the logical data requirements and offer sound empirical examples for an HLM analysis.