An Analysis of Presidential Preferences in the Distribution of Empowerment Zones and Enterprise Communities

Critics regarded the selection of urban empowerment zones and enterprise communities by Secretary Cisneros in 1994 as sympathetic to President Clinton's considerations. However, the secretary countered that cities were chosen based on their ability to revitalize their communities successfully, as outlined in their applications. To determine whether the secretary responded to top-down presidential preferences, data from the complete list of applications is used to test four hypotheses derived from principal—agent theory. The results of the logistic regression models do not validate the significance of the presidential variables (for instance, presidential support score for each city's congressional delegation, marginal districts, and 1992 state vote for President Clinton). Rather, many of the nonpresidential variables (community participation, size of the empowerment zone or enterprise community, and poverty) were significant in supporting the secretary's contention.     

Global Assemblages of Security Governance and Contemporary International Intervention

ABSTRACT

This article draws from the concept of assemblages in order to examine the component parts of contemporary international interventions. It argues that in contrast mainstream analyses of statebuilding and peacebuilding, as well as more critical treatments that tie interventions to the concept of 'international order', the concept of assemblages offers a more compelling vantage point from which to examine the disparate lines of forces that make up modern-day interventions. The article proposes an exploration of some of the component parts that sustain the current assemblage of governance, security, and international intervention and draws our attention to their self-sustaining rationalities.     

Academic copyright in the publishing game: a contest perspective

As scientists are motivated by readership rather than by royalties, one might doubt that academic copyright is required for stimulating research. Consequently, establishing an open access regime is currently intensively being discussed. We contribute to the literature by using a contest-model in which differently talented researchers compete for limited journals space. The contest perspective adds a rent-seeking motive into the publishing game which questions that private incentives for research are always too low due to the positive externalities of scientific progress. In our model, open access always leads to higher social welfare when incentives are too high. When incentives are too low, then open access is only superior if the benefits from larger readership is sufficiently high.     

Generating a Corpus of Mobile Forensic Images for Masquerading user Experimentation

The Periodic Mobile Forensics (PMF) system investigates user behavior on mobile devices. It applies forensic techniques to an enterprise mobile infrastructure, utilizing an on‐device agent named TractorBeam. The agent collects changed storage locations for later acquisition, reconstruction, and analysis. TractorBeam provides its data to an enterprise infrastructure that consists of a cloud‐based queuing service, relational database, and analytical framework for running forensic processes. During a 3‐month experiment with Purdue University, TractorBeam was utilized in a simulated operational setting across 34 users to evaluate techniques to identify masquerading users (i.e., users other than the intended device user). The research team surmises that all masqueraders are undesirable to an enterprise, even when a masquerader lacks malicious intent. The PMF system reconstructed 821 forensic images, extracted one million audit events, and accurately detected masqueraders. Evaluation revealed that developed methods reduced storage requirements 50‐fold. This paper describes the PMF architecture, performance of TractorBeam throughout the protocol, and results of the masquerading user analysis.     

Perceived Criminal Threat from Undocumented Immigrants: Antecedents and Consequences for Policy Preferences

Drawing on the group threat perspective, this paper examines the perception of criminal threat from undocumented immigrants and its relation to both contextual measures of threat and public support for enhanced controls against undocumented immigrants. With data from a national telephone survey of non-Latino adults (N?=?1,364), we estimate the predictors of perceived criminal threat as well as the effects of perceived threat and other factors on immigration policy preferences. Results indicate that political ideology and education are the strongest predictors of perceived criminal threat. Perceived criminal threat has the greatest influence on support for more punitive controls and partially mediates the effects of race, education, political ideology, and contextual threat on these control preferences. Future social threat research should consider the inclusion of perceptual threat measures instead of relying solely on contextual indicators of threat. In addition, contextual threat should be explored more often in dynamic, rather than static, terms.