Predicting Consistency Between Officially Recorded and Self-Reported Records of Arrest

National Youth Survey Family Study (NYSFS) respondents were examined to identify the characteristics of individuals and their sociological environments, that would make them more likely to have consistency between self reported and officially recorded records of arrest. Somewhat surprisingly, it was found that those most likely to be at risk of arrest (males, high exposure to delinquent friends, higher level of substance use) are more likely to have consistency between officially recorded and self-reported arrests. Findings will be helpful in both producing more accurate information on arrests and in increasing sensitivity to the possibility of bias in arrest records that may be based on sociodemographic or behavioral characteristics of the individual.     

Too central to fail? Terror networks and leadership decapitation

ABSTRACT

Leadership decapitation, as a means of hindering the operations and hastening the demise of terrorist organizations, has been the subject of a growing body of research. However, these studies have not examined how an organization’s position in a broader network impacts its ability to weather decapitation. We argue that highly networked organizations possess characteristics that make decapitation less effective. To test this argument, we combine data on leadership decapitation with network data on terrorist organizations and find that well-networked organizations are resilience to leadership decapitation. Our study has implications for our understanding of how terrorist organizations respond to counterterrorism efforts.     

On-line processing in candidate evaluation: The effects of issue order,issue importance,and sophistication

This article reports the results of a study that replicates and extends the impression-driven model of candidate evaluation reported in Lodge, McGraw, and Stroh (1989). This model holds that evaluations are formed and updated on-line as information is encountered, and that as a result, citizens need not rely on specific information available from memory to form their candidate evaluations. In the present work we explore whether the order in which information is encountered, as well as whether information that is personally important, influences the weight accorded to evidence in on-line processing. In addition, differences in information-processing strategies due to political sophistication are examined. The results indicate that important information receives more weight than unimportant information. In addition, the evidence suggests that political sophisticates are more efficient on-line processors than are less sophisticated individuals. The implications of these results for models of candidate evaluation are discussed.     

A Computational Model of the Citizen as Motivated Reasoner: Modeling the Dynamics of the 2000 Presidential Election

A computational model of political attitudes and beliefs is developed that incorporates contemporary psychological theory with well-documented findings from electoral behavior. We compare this model, John Q. Public (JQP), to a Bayesian learning model via computer simulations of observed changes in candidate evaluations over the 2000 presidential campaign. In these simulations, JQP reproduces responsiveness, persistence, and polarization of political attitudes, while the Bayesian learning model has difficulty accounting for persistence and polarization. We conclude that “motivated reasoning”—the discounting of information that challenges priors along with the uncritical acceptance of attitude-consistent information—is the reason our model can better account for persistence and polarization in candidate evaluations.