Reconsidering the Evolution of Nonlinguistic Communication: The Case of Laughter

Nonlinguistic communication is typically proposed to convey representational messages, implying that particular signals are associated with specific signaler emotions, intentions, or external referents. However, common signals produced by both nonhuman primates and humans may not exhibit such specificity, with human laughter for example showing significant diversity in both acoustic form and production context. We therefore outline an alternative to the representational approach, arguing that laughter and other nonlinguistic vocalizations are used to influence the affective states of listeners, thereby also affecting their behavior. In the case of laughter, we propose a primary function of accentuating or inducing positive affect in the perceiver in order to promote a more favorable stance toward the laugher. Two simple strategies are identified, namely producing laughter with acoustic features that have an immediate impact on listener arousal, and pairing these sounds with positive affect in the listener to create learned affective responses. Both depend on factors like the listener's current emotional state and past interactions with the vocalizer, with laughers predicted to adjust their sounds accordingly. This approach is used to explain findings from two experimental studies that examined the use of laughter in same-sex and different-sex dyads composed of either friends or strangers, and may be applicable to other forms of nonlinguistic communication.     

Using Probabilistic Terrorism Risk Modeling for Regulatory Benefit-Cost Analysis: Application to the Western Hemisphere Travel Initiative in the Land Environment

This article presents a framework for using probabilistic terrorism risk modeling in regulatory analysis. We demonstrate the framework with an example application involving a regulation under consideration, the Western Hemisphere Travel Initiative for the Land Environment, (WHTI‐L). First, we estimate annualized loss from terrorist attacks with the Risk Management Solutions (RMS) Probabilistic Terrorism Model. We then estimate the critical risk reduction, which is the risk‐reducing effectiveness of WHTI‐L needed for its benefit, in terms of reduced terrorism loss in the United States, to exceed its cost. Our analysis indicates that the critical risk reduction depends strongly not only on uncertainties in the terrorism risk level, but also on uncertainty in the cost of regulation and how casualties are monetized. For a terrorism risk level based on the RMS standard risk estimate, the baseline regulatory cost estimate for WHTI‐L, and a range of casualty cost estimates based on the willingness‐to‐pay approach, our estimate for the expected annualized loss from terrorism ranges from $2.7 billion to $5.2 billion. For this range in annualized loss, the critical risk reduction for WHTI‐L ranges from 7% to 13%. Basing results on a lower risk level that results in halving the annualized terrorism loss would double the critical risk reduction (14–26%), and basing the results on a higher risk level that results in a doubling of the annualized terrorism loss would cut the critical risk reduction in half (3.5–6.6%). Ideally, decisions about terrorism security regulations and policies would be informed by true benefit‐cost analyses in which the estimated benefits are compared to costs. Such analyses for terrorism security efforts face substantial impediments stemming from the great uncertainty in the terrorist threat and the very low recurrence interval for large attacks. Several approaches can be used to estimate how a terrorism security program or regulation reduces the distribution of risks it is intended to manage. But, continued research to develop additional tools and data is necessary to support application of these approaches. These include refinement of models and simulations, engagement of subject matter experts, implementation of program evaluation, and estimating the costs of casualties from terrorism events.     

Urban Power Structures and Publicly Financed Stadiums

Urban elites are increasingly addressing local social problems though policies that turn their cities into tourist destinations. Often at the heart of these policies are new publicly financed sports stadiums. Ironically, this strategy is flourishing despite near-unanimous academic criticism, and increasing public skepticism, about this approach. Our research addresses this contradiction by exploring how and why powerful decisionmakers continue supporting publicly financed stadiums. We rely on local growth coalition theory to explore this topic because it offers analytical advantages, including looking beyond local sports teams as the focal point of these initiatives, addressing the variation in the outcomes of these initiatives, and acknowledging that policymakers are predisposed toward supporting these initiatives but that this predisposition does not always result in success.     

Bootstrap Estimation of Benchmark Doses and Confidence Limits with Clustered Quantal Data

The benchmark dose (BMD) is an exposure level that would induce a small risk increase (BMR level) above the background. The BMD approach to deriving a reference dose for risk assessment of noncancer effects is advantageous in that the estimate of BMD is not restricted to experimental doses and utilizes most available dose-response information. To quantify statistical uncertainty of a BMD estimate, we often calculate and report its lower confidence limit (i.e., BMDL), and may even consider it as a more conservative alternative to BMD itself. Computation of BMDL may involve normal confidence limits to BMD in conjunction with the delta method. Therefore, factors, such as small sample size and nonlinearity in model parameters, can affect the performance of the delta method BMDL, and alternative methods are useful. In this article, we propose a bootstrap method to estimate BMDL utilizing a scheme that consists of a resampling of residuals after model fitting and a one-step formula for parameter estimation. We illustrate the method with clustered binary data from developmental toxicity experiments. Our analysis shows that with moderately elevated dose-response data, the distribution of BMD estimator tends to be left-skewed and bootstrap BMDL s are smaller than the delta method BMDL s on average, hence quantifying risk more conservatively. Statistically, the bootstrap BMDL quantifies the uncertainty of the true BMD more honestly than the delta method BMDL as its coverage probability is closer to the nominal level than that of delta method BMDL. We find that BMD and BMDL estimates are generally insensitive to model choices provided that the models fit the data comparably well near the region of BMD. Our analysis also suggests that, in the presence of a significant and moderately strong dose-response relationship, the developmental toxicity experiments under the standard protocol support dose-response assessment at 5% BMR for BMD and 95% confidence level for BMDL.     

Adult Drug Treatment Courts: A Review

Drug treatment courts (DTCs), an alternative to traditional criminal courts, provide an innovative way to legally process some drug offenders. The origin and recent growth of the drug court system in the USA can be explained as an unintended consequence of a failing 'war on drugs'. In this article, we discuss the spread of adult DTCs throughout the USA, the main components of drug courts, controversies surrounding DTCs, and some criticisms of drug courts. We summarize the recent evaluations of adult DTCs, and highlight various DTC factors that have been found to reduce individual drug use and criminal activity. We also offer suggestions for future research on DTCs and conclude with policy recommendations.     

Joint tests of non-nested models and general error specifications

This paper is concerned with joint tests of non-nested models and simultaneous departures from homoskedasticity, serial independence and normality of the disturbance terms. Locally equivalent alternative models are used to construct joint tests since they provide a convenient way to incorporate more than one type of departure from the classical conditions. The joint tests represent a simple asymptotic solution to the “pre-testing” problem in the context of non-nested linear regression models. Our simulation results indicate that the proposed tests have good finite sample properties.     

CORPORATE TAX INCIDENCE AND INEFFICIENCY WHEN CORPORATE AND NONCORPORATE GOODS ARE CLOSE SUBSTITUTES

An important deficiency in Harberger's [1962] model of corporate income taxation is its inability to consider both corporate and noncorporate production of the same good. Within-industry substitution has potentially major implications for both the excess burden and incidence of the corporate tax.
We analyze this within-industry substitution using a model in which each industry/sector contains corporate and noncorporate firms (with identical production functions) which produce goods that are close substitutes. The scope for considerable within-industry substitution of noncorporate for corporate capital leads to a very much larger excess burden than that in the Harberger model.     

Portmanteau test for conditional heteroscedasticity, using ranks of squared residuals

Squared residual autocorrelations have been found useful in detecting departures from linearity in time series models. This is especially the case with data exhibiting heterogeneity in variances. A rank test is proposed which is much more robust than its parametric counterpart.     

Effects of Category Order on Answers in Mail and Telephone Surveys1

Abstract Past research suggests that mail surveys encourage a primacy effect, which is a tendency to choose the first answers from a list, whereas telephone surveys encourage a recency effect, a tendency to choose the last answers from a list. This paper summarizes results from 82 new experiments conducted in 12 separate surveys in seven states. Only four of 33 mail survey comparisons exhibited significant primacy effects, while five of 26 experiments in telephone surveys exhibited recency effects. In addition, only three of 23 cross-method comparisons produced a significant primacy/recency effect in the expected manner. The conclusion is that the prevalence of primacy and recency effects has been over-estimated by past research and a new theoretical approach that takes into account multiple causation is needed for examining these effects.     

The availability of personal and external coping resources: Thier impact on job stress and employee attitudes during organizational restructuring

This study examines the relationships among personal coping resources, social support, external coping resources, job stressors and job strains in a sample of 110 American Telephone and Telegraph employees undergoing a major organizational restructuring. The study expanded on a model suggested by Ashford (1988) by defining another category of coping resources that employees may draw upon to deal with the stressors and strains which occur during major organizational changes. External coping resources were defined as those which provided employees with a sense of 'vicarious control' in stressful situations. Results indicated that personal coping resources, social support and external coping resources had a direct effect upon job stressor and strain levels. No 'buffering' effect of these coplng resources was found. Hierarchical regression analyses indicated that external coping resources added to the prediction of job stressors and strains even when pertonal coping resources and social support were entered first into the prediction questions.