The impact of task difficulty, defendant\u27s race, and race salience on conformity in mock jury deliberations

Understanding what factors affect conformity in jury deliberations is an essential part of understanding the decision making process of reaching a verdict. This study manipulated three variables in a case summary: race salience (not salient vs. salient), defendant race (Black vs. White), and task difficulty (easy vs. difficult). The study used a mock deliberation paradigm based on Kassin, Smith, & Tulloch (1990). Participants read a case summary and provided a verdict with a short explanation. After doing so, participants read notes containing the verdicts and explanations of 5 other fictitious participants. Participants\u27 verdicts were always in the minority. After viewing the decisions of the other participants, the participants were asked to write down a second verdict. In total, there were three rounds of deliberations. Conformity was assessed by number of people who changed their vote in each condition. The participants in this study were college students (N=125). The primary hypothesis was that when the task was unimportant (i.e., the defendant is White), conformity would be equal for the easy and difficult tasks. However, when the task was important (i.e., the defendant is Black), conformity should be higher for the difficult task versus the easy task. This pattern was predicted when race was not salient. The same pattern was predicted for the race salient conditions, however it was anticipated that the effect of task difficulty when the defendant was Black would be amplified. Results provided information about how legally relevant and extralegal variables interact to affect conformity. Aversive racism theories are discussed in the context of the results

Towards the Compositional Verification of Real-Time UML Designs

checking are limited when it comes to the verification of complex distributed embedded real-time systems. Our approach addresses this problem and in particular the state explosion problem for the software controlling mechatronic systems, as we provide a domain specific formal semantic definition for a subset of the UML 2.0 component model and an integrated sequence of design steps. These steps prescribe how to compose complex software systems from domain-specific patterns which model a particular part of the system behavior in a well-defined context. The correctness of these patterns can be verified individually because they have only simple communication behavior and have only a fixed number of participating roles. The composition of these patterns to describe the complete component behavior and the overall system behavior is prescribed by a rigorous syntactic definition which guarantees that the verification of component and system behavior can exploit the results of the verification of individual patterns