Does Spatial Variation in Heterogeneity Matter? Assessing the Adoption Patterns of Business Improvement Districts

Because they supplement the municipal provision of local public goods, Business Improvement Districts (BIDs) provide an opportunity to examine the space, scope, and determinants of the provision of local public goods. A BID is formed when a group of merchants or commercial property owners in a neighborhood vote in favor of package of self‐assessments and local public goods to be funded with those assessments. These districts solve a collective action problem in the provision of public goods because once a majority has voted in favor, participation is compulsory for all merchants or commercial property owners in the neighborhood. I use a unique dataset on adoption patterns of BIDs in California to test two main claims suggested by the theoretical literature: first, that businesses respond to individual heterogeneity that determines the quality of local public goods, and second, that the type of heterogeneity—overall or spatial—matters. In contrast to the literature on residents, this study finds at best a weak correlation between a city's adoption of a BID and heterogeneity. In addition, despite the theoretical preference for spatial over overall heterogeneity, BIDs are not more likely to be adopted by spatially heterogeneous cities.     

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.     

The Angry Pamphleteer: True Threats,Political Speech,and Applying Watts v. United States in the Age of Twitter

Since the 1969 case Watts v. United States, courts have consistently held that politically motivated speech about or directed to public figures may be punished if it qualifies as a “true threat” rather than protected political hyperbole. Criticism of public officials lies at the core of First Amendment protection, even when that criticism is caustic or crude. Such caustic speech appears on Twitter with increasing frequency, often pushing the boundaries of the constitutional guarantees of free speech. Through an analysis of the political speech-true threat cases that apply Watts, this study identifies and assesses three distinct modes of analysis that lower courts use to distinguish political speech from true threats. They are: (1) criteria-based analysis; (2) ad hoc balancing; and (3) a form of balancing referred to herein as “line-crossing analysis.” This study concludes that criteria-based analysis is the most prominent mode used by lower courts. As applied to new media and political participation, criteria-based analysis risks unduly restricting valuable political speech.     

Abnormal Daily Temperature and Concern about Climate Change Across the United States

The relatively low level of concern about climate change among Americans has important implications for climate policy. While many studies have examined individual characteristics associated with climate change attitudes, fewer studies have considered the effects of environmental conditions on such attitudes. Here, we use two national samples of American adults to explore the impact of abnormal daily temperatures on levels of concern about climate change. We test the hypotheses that (1) abnormally warm temperatures, and (2) both abnormally warm and abnormally cool temperatures are associated with higher levels of concern. Using a generalized ordinal logit, we find that the quadratic form of deviation from mean temperature on the date of the survey is significantly associated with higher levels of concern, thus supporting the second hypothesis. We discuss several theoretical frameworks that may explain this result including availability bias, mental models, and implicit stimuli, and the implications for climate policy.     

The Perils of Politics: Why Staying Apolitical is Good for Both the U.S. Military & the Country

This article seeks to answer several vital questions about contemporary American civil- military relations. For example, why might the most professional military in United States history seem to be especially likely to engage in public dissent and advocacy? Why might political dissent and activity hold appeal for current and upcoming generations of military officers? And, how can present day officers be persuaded that retaining an apolitical ethos is fundamental to the American military, not just because of tradition but because public dissent can do real damage to the military institution and to the country it serves?