“A Statistically Representative Climate Change Debate”: Satirical Television News,Scientific Consensus,and Public Perceptions of Global Warming

Satirical television news programs provide the public with potential sources of information about climate change. This study uses a segment from Last Week Tonight with John Oliver as a test case for exploring how coverage from such programs that features consensus messaging may influence viewers’ perceptions of global warming. The segment presents a “statistically representative climate change debate” to affirm the scientific consensus on anthropogenic climate change and satirize television news coverage “balancing” this consensus with skeptics’ arguments. Results from a randomized experiment demonstrate that watching the segment increased viewers’ own belief in global warming, as well as viewers’ perceptions that most scientists believe in global warming. The latter effect was stronger among participants with low interest in the environment and global warming than among those with high interest. The segment’s impact on perceptions of scientists’ views may have mediated its effects on viewers’ own beliefs about global warming.     

Disability at work: Understanding the impact of the ADA on the workplace

It has been more than 25 years since the Americans with Disabilities Act (ADA) was passed by Congress. Many supporters of the law hoped that it would improve the employment outcomes for people with a disability, yet many scholars argue that it has fallen short in achieving this goal. Such judgments of success or failure are typically offered with little regard for the complex relationship between law and social change. In this paper, I apply a socio‐legal perspective to scholarly research regarding the impact of the ADA on employment. Socio‐legal studies offer a variety of concepts and perspectives, which better capture the complexity of law's impact on social life, and the various paths through which it might have an impact on social change. From this perspective, studies tend to assume that ADA law will either impact social change directly or indirectly. I discuss the findings of both of these approaches and conclude with some directions for future research.     

The struggle for hegemony: the emergence of a counter-public sphere in post-1997 Hong Kong

The present study examines the struggle for hegemony in the public sphere by two different systems, following Hong Kong’s handover to China in 1997. It has been postulated that the new media, particularly social media, has become an important public sphere for the citizens of Hong Kong to engage in an anti-hegemonic struggle against China’s discursive encroachment into Hong Kong since 1997. Given that the public platform provided by legacy media has been bought out or coopted by China, new media has begun to serve as a subaltern public sphere to enable resisting the hegemony imposed by China. This was analyzed through a survey conducted as part of this study, which showed that people who are young, read the Apple Daily, have high expectations of local autonomy, and a high regard for press freedom are prone to using social media to obtain their social and political information. This article analyzes the implications of the emergence of a counter-China hegemonic public sphere.     

Orthogonality of the mean and error distribution in generalized linear models

We show that the mean-model parameter is always orthogonal to the error distribution in generalized linear models. Thus, the maximum likelihood estimator of the mean-model parameter will be asymptotically efficient regardless of whether the error distribution is known completely, known up to a finite vector of parameters, or left completely unspecified, in which case the likelihood is taken to be an appropriate semiparametric likelihood. Moreover, the maximum likelihood estimator of the mean-model parameter will be asymptotically independent of the maximum likelihood estimator of the error distribution. This generalizes some well-known results for the special cases of normal, gamma, and multinomial regression models, and, perhaps more interestingly, suggests that asymptotically efficient estimation and inferences can always be obtained if the error distribution is non parametrically estimated along with the mean. In contrast, estimation and inferences using misspecified error distributions or variance functions are generally not efficient.     

Mitigating Inventory Overstocking: Optimal Order‐up‐to Level to Achieve a Target Fill Rate over a Finite Horizon

Service level agreements (SLAs) are widely adopted performance‐based contracts in operations management practice, and fill rate is the most common performance metric among all the measurements in SLAs. Traditional procedures characterizing the order‐up‐to level satisfying a specified fill rate implicitly assume an infinite performance review horizon. However, in practice, inventory managers are liable to maintain and report fill rates over a finite performance review horizon. This horizon discrepancy leads to deviation between the target fill rate and actual achieved fill rate. In this study, we first examine the behavior of the fill rate distribution over a finite horizon with positive lead time. We analytically prove that the expected fill rate assuming an infinite performance review horizon exceeds the expected fill rate assuming a finite performance review horizon, implying that there exists some inventory “waste” (i.e., overstocking) when the traditional procedure is used. Based on this observation and the complexity of the problem, we propose a simulation‐based algorithm to reduce excess inventory while maintaining the contractual target fill rate. When the lead time is significant relative to the length of the contract horizon, we show that the improvement in the inventory system can be over 5%. Further, we extend our basic setting to incorporate the penalty for failing to meet a target, and show how one can solve large‐scale problems via stochastic approximation. The primary managerial implication of our study is that ignoring the performance review horizon in an SLA will cause overstocking, especially when the lead time is large.     

Do perceptions of their partners’ childbearing desires affect young women’s pregnancy risk? Further study of ambivalence

We explore whether young women’s perceptions of their sexual partners’ childbearing desires contribute to their risk of pregnancy. We used weekly journal data collected from 787 young women to measure their childbearing desires and their perceptions of their partners’ childbearing desires. We then conducted hazard modelling to predict pregnancy risk with variables based on interactions between the women’s desires and their perceived partners’ desires. Models that include perceived partners’ desires perform better than one based on women’s desires alone. The best model contains three significant predictors: one confirms the importance of pronatal, ambivalent, and indifferent desires for pregnancy risk; one indicates that the perceived partners’ antinatal desires reduce women’s pregnancy risk; and one suggests that women who both perceive their partners accurately and are in agreement with them have a lower pregnancy risk. The results indicate that perceived partner data can improve prediction and enhance our understanding of pregnancy risk.     

Rejected by Family for Being Gay or Lesbian: Portrayals,Perceptions, and Resilience

A myriad of negative psychosocial outcomes face gay men and lesbians who experience rejection by their family for not being heterosexual. However, what constitutes rejection is not clear, and, more importantly, it is not known how resilience is fostered within such a context. This qualitative study sought to examine these issues by exploring the lived experiences of Australian gay men and lesbians who were previously or were currently experiencing family rejection because of their sexuality. A total of 21 in-depth, semistructured interviews were individually conducted and analyzed. Thematic analysis of the interviews revealed several themes that provided greater understanding of the portrayals and perceptions of family rejection; the impact of family rejection on mental health; and, importantly, how these individuals came to establish resilience in the face of experiencing family rejection. Limitations, directions for future research, and clinical implications of the findings are also discussed.     

Some contributions on the multivariate Poisson–Skellam probability distribution

In this article, we introduce a new form of distribution whose components have the Poisson or Skellam marginal distributions. This new specification allows the incorporation of relevant information on the nature of the correlations between every component. In addition, we present some properties of this distribution. Unlike the multivariate Poisson distribution, it can handle variables with positive and negative correlations. It should be noted that we are only interested in modeling covariances of order 2, which means between all pairs of variables. Some simulations are presented to illustrate the estimation methods. Finally, an application of soccer teams data will highlight the relationship between number of points per season and the goal differential by some covariates.     

Eliciting Dirichlet and Gaussian copula prior distributions for multinomial models

In this paper, we propose novel methods of quantifying expert opinion about prior distributions for multinomial models. Two different multivariate priors are elicited using median and quartile assessments of the multinomial probabilities. First, we start by eliciting a univariate beta distribution for the probability of each category. Then we elicit the hyperparameters of the Dirichlet distribution, as a tractable conjugate prior, from those of the univariate betas through various forms of reconciliation using least-squares techniques. However, a multivariate copula function will give a more flexible correlation structure between multinomial parameters if it is used as their multivariate prior distribution. So, second, we use beta marginal distributions to construct a Gaussian copula as a multivariate normal distribution function that binds these marginals and expresses the dependence structure between them. The proposed method elicits a positive-definite correlation matrix of this Gaussian copula. The two proposed methods are designed to be used through interactive graphical software written in Java.