Jurors' use of social framework evidence

Monahan and Walker (1988) delineated three uses of social science evidence within the courts: social authority, social fact, and social framework. Social authority evidence is social science evidence used in making policy or law. Social fact evidence is social science evidence that describes research undertaken expressly for the case at hand. Social framework evidence involves providing conclusions from previously conducted social science research to assist jurors in evaluating the other evidence in the case. Although this type of evidence has traditionally been presented via expert testimony, Monahan and Walker (1988) have suggested that, because the social science research involved comes from the extant literature and is not the province of any particular expert, it would be more economical to have the judge present this information as part of the judicial instructions to the jury. This study tested the implicit assumption that the presentation of the social framework evidence by the judge will have the same impact on juror verdicts as presentation of this evidence by an expert. ^ Two hundred mock jurors watched a videotaped hostile work environment sexual harassment trial. The social framework evidence consisted of the discussion of factors that have been found to increase the likelihood of sex stereotyping of women by men. The trial included either no social framework evidence, social framework evidence presented by the expert, or social framework evidence presented in judicial instructions. ^ Results indicated that men who heard the social framework evidence from the judge were more likely to vote for the defendant than men who heard no social framework evidence. Men who heard the judicial instruction with the social framework evidence also rated the plaintiff as less credible than the other men and women in the study. Thus, it appears that, for men, social framework evidence presented by the judge harms the plaintiff's case by reducing ratings of her credibility, but the same evidence presented by an expert does not affect men's verdicts. For women, however, social framework evidence, irrespective of who presents it, enhances the plaintiff's case. ^

GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.