Perceptions of Randomized Security Schedules

Security of infrastructure is a major concern. Traditional security schedules are unable to provide omnipresent coverage; consequently, adversaries can exploit predictable vulnerabilities to their advantage. Randomized security schedules, which randomly deploy security measures, overcome these limitations, but public perceptions of such schedules have not been examined. In this experiment, participants were asked to make a choice between attending a venue that employed a traditional (i.e., search everyone) or a random (i.e., a probability of being searched) security schedule. The absolute probability of detecting contraband was manipulated (i.e., 1/10, 1/4, 1/2) but equivalent between the two schedule types. In general, participants were indifferent to either security schedule, regardless of the probability of detection. The randomized schedule was deemed more convenient, but the traditional schedule was considered fairer and safer. There were no differences between traditional and random schedule in terms of perceived effectiveness or deterrence. Policy implications for the implementation and utilization of randomized schedules are discussed.     

美国视频通信市场的转型——付费视频内容转向互联网

本文概述了当前美国有线电视行业／付费视频行业的局势，以及一些重要问题和面临的挑战，展望了未来的视频市场，概述了一个未来视频／宽带市场的战略愿景，然后回归到政策建议及具体的立法和管制行动。这将帮助我们在最短的、可操作的时间内通向一个开放的、非歧视性的、无处不在的宽带网络。     

Classroom sex composition and first-grade school outcomes: The role of classroom behavior

Using nationally representative data from the Early Childhood Longitudinal Study-Kindergarten Cohort (N = 21,409; 10,452 girls and 10,957 boys; mean age = 7.24 years), the association between first-grade classroom sex composition (CSC), measured as the percentage of female students, and end of the year academic (reading, mathematics) and socio-emotional (externalizing problems, internalizing problems, self-control, interpersonal skills) outcomes was examined. Using multilevel modeling techniques and controlling for prior achievement levels, CSC was positively associated with children’s reading achievement at the end of first grade; students performed better in reading in classes with a higher percentage of female students. CSC was also associated with three of the socio-emotional outcomes; controlling for prior levels, students in classrooms with a higher percentage of girls had better self-control and interpersonal skills and fewer internalizing problems. Classroom behavior mediated the effects of CSC on reading achievement and the socio-emotional outcomes. Implications for the composition of first-grade classrooms are discussed.     

Interplay between Friends' Aggression and Friendship Quality in the Development of Child Aggression during the Early School Years

The aim of this study was to investigate the unique and combined role of friendship quality and friends' aggression in regard to the persistence of young children's physical aggression from kindergarten to grade 2. The sample included 1555 children (808 girls) assessed annually using teacher ratings. Two theoretical perspectives (i.e., the social learning and the social bonding perspectives) served as frameworks to guide the analyses and interpret the results. In line with the social learning perspective, friends' aggression was related to a significant increase in children's physical aggression. However, in line with the social bonding perspective, good friendship quality played both a compensatory and a protective role, by, respectively, reducing children's initial level of physical aggression and by mitigating, albeit marginally, the associations between friends' and children's physical aggression. These results suggest that fostering a positive relationship between friends in the early school years may decrease physical aggression even if the friends are aggressive.     

Female Labor Supply,Human Capital,and Welfare Reform

We estimate a dynamic model of employment, human capital accumulation—including education, and savings for women in the United Kingdom, exploiting tax and benefit reforms, and use it to analyze the effects of welfare policy. We find substantial elasticities for labor supply and particularly for lone mothers. Returns to experience, which are important in determining the longer‐term effects of policy, increase with education, but experience mainly accumulates when in full‐time employment. Tax credits are welfare improving in the U.K., increase lone‐mother labor supply and marginally reduce educational attainment, but the employment effects do not extend beyond the period of eligibility. Marginal increases in tax credits improve welfare more than equally costly increases in income support or tax cuts.     

Signaling to Partially Informed Investors in the Newsvendor Model

We analyze a signaling game between the manager of a firm and an investor in the firm. The manager has private information about the firm's demand and cares about the short‐term stock price assigned by the investor. Previous research has shown that under continuous decision choices and the Intuitive Criterion refinement, the least‐cost separating equilibrium will result, in which a low‐quality firm chooses its optimal capacity and a high‐quality firm over‐invests in order to signal its quality to investors. We build on this research by showing the existence of pooling outcomes in which low‐quality firms over‐invest and high‐quality firms under‐invest so as to provide identical signals to investors. The pooling equilibrium is practically appealing because it yields a Pareto improvement compared to the least‐cost separating equilibrium. Distinguishing features of our analysis are that: (i) we allow the capacity decision to have either discrete or continuous support, and (ii) we allow beliefs to be refined based on either the Undefeated refinement or the Intuitive Criterion refinement. We find that the newsvendor model parameters impact the likelihood of a pooling outcome, and this impact changes in both sign and magnitude depending on which refinement is used.     

Further Beyond the Basic Background Check: Predicting Future Unethical Behavior

In this paper, we analyze the ethical issues of using honesty and integrity tests in employment screening. Our focus will be on the United States context: legal requirements related to applicant privacy differ in other countries, but we posit that our proposed balancing test is broadly applicable. We start by discussing why companies have ethical and legal obligations, based on a stakeholder analysis, to assess the integrity of potential employees. We then move to a consideration of how companies currently use background checks as a pre‐employment screening tool, noting their limitations. We then take up honesty and integrity testing, focusing particularly on the problems of false positives and due process. We offer a balancing test for the use of honesty and integrity testing that takes in three factors: (1) the potential harm posed by a dishonest employee in a particular job, (2) the linkage between the test and the assessment process, and (3) the accuracy and validity of the honesty and integrity test. We conclude with implications for practice and future research.     

Nonparametric Estimation of the Number of Drug Users in Hong Kong Using Repeated Multiple Lists

We update a previous approach to the estimation of the size of an open population when there are multiple lists at each time point. Our motivation is 35 years of longitudinal data on the detection of drug users by the Central Registry of Drug Abuse in Hong Kong. We develop a two‐stage smoothing spline approach. This gives a flexible and easily implemented alternative to the previous method which was based on kernel smoothing. The new method retains the property of reducing the variability of the individual estimates at each time point. We evaluate the new method by means of a simulation study that includes an examination of the effects of variable selection. The new method is then applied to data collected by the Central Registry of Drug Abuse. The parameter estimates obtained are compared with the well known Jolly–Seber estimates based on single capture methods.     

Predictive Inference for Big,Spatial, Non‐Gaussian Data: MODIS Cloud Data and its Change‐of‐Support

Remote sensing of the earth with satellites yields datasets that can be massive in size, nonstationary in space, and non‐Gaussian in distribution. To overcome computational challenges, we use the reduced‐rank spatial random effects (SRE) model in a statistical analysis of cloud‐mask data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board NASA's Terra satellite. Parameterisations of cloud processes are the biggest source of uncertainty and sensitivity in different climate models’ future projections of Earth's climate. An accurate quantification of the spatial distribution of clouds, as well as a rigorously estimated pixel‐scale clear‐sky‐probability process, is needed to establish reliable estimates of cloud‐distributional changes and trends caused by climate change. Here we give a hierarchical spatial‐statistical modelling approach for a very large spatial dataset of 2.75 million pixels, corresponding to a granule of MODIS cloud‐mask data, and we use spatial change‐of‐Support relationships to estimate cloud fraction at coarser resolutions. Our model is non‐Gaussian; it postulates a hidden process for the clear‐sky probability that makes use of the SRE model, EM‐estimation, and optimal (empirical Bayes) spatial prediction of the clear‐sky‐probability process. Measures of prediction uncertainty are also given.