Statistics for Criminology and Criminal Justice
SAGE Journal Articles
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The purpose of this study is to extend White’s analysis predicting successful police recruit performance during academy training. Using police personnel data collected on 486 officers hired between 1996 and 2006 by a Midwestern police department, the authors examine characteristics related to academy success as well as active police service. The results show that most demographic and experience variables did not predict academy or active service success. However, White recruits and those scoring higher on the civil service exam consistently performed better on multiple academy outcome measures than their counterparts. In addition, those scoring higher on the overall academy success measure generally received better evaluations from their superiors. The results also show that higher education is not related to any of the measures of academy or on the job success used in these analyses.
Psychological selection criteria for police officers have traditionally been part of a "screening out" model. This model has targeted for elimination from further consideration candidates with problems in one or more of the following areas: inability to tolerate stress; prejudicial attitudes toward ethnic minority groups, homosexuals, women, or the homeless; poor interpersonal relationships; poor judgment; disordered thought processes; and lack of impulse control. The screening out model is reviewed, including selected individual components and their effectiveness. Both positive and negative aspects of screening out problematic candidates are evaluated, along with the rationale for the development of an alternative, prosocial selection system that can be implemented using the assessment center approach.
This study examines the antecedents of online consumers’ estimates of the risk of credit card theft victimization and whetherrisk perceptions are empirically linked to online lifestyles. Using telephone survey data from a sample of adult Internet users inthe state of Florida (N = 573), the regression analysis shows that socially vulnerable (e.g., lower socioeconomic status consumers) and financially impulsive respondents perceive higher levels of risk when using their credit card online. Results from the negative binomial models show that consumers with higher risk scores spend significantly less time on the Internet and make fewer purchases from Web sites, yet financially impulsive respondents fail to engage in such risk-reduction strategies. Overall, these findings suggest that key features of Ferraro’s risk interpretation model generalize to the online victimization context.