Dating and Sexual Behavior Among Single Parents of Young Children in the United States

Theory and research on partnered parents suggests trade-offs between parenting and sexuality, with those trade-offs most pronounced among mothers of young children. However, little research has focused on how a growing demographic of single parents negotiates dating and sexual activity. The current study drew upon a 2012 nationally representative sample of 5,481 single Americans 21 years of age and older, of whom 4.3% were parents of a child age five or younger. Dependent variables were sexual thoughts, frequency of sexual activity, number of sexual partners in the past year, dates during the previous three months, and whether one was actively seeking a relationship partner. Covariates included parental age, sex/gender, sexual orientation, education, and income. Using the entire sample of singles, we found no main effects of number (0, 1, 2+) of children aged five years and younger or number of children aged two years and younger on dating and sexual behavior variables. Next, using analyses restricted to single parents (n = 2,121), we found that single parents with a child aged five years or younger, adjusting for covariates, reported greater frequency of sexual activity and first dates but no differences in other outcomes compared with single parents of older children.     

The ARCH(2) model: Pseudo-maximum estimation and asymptotic results under dependent innovations

This paper investigates the pseudo-maximum likelihood (PML) estimation of an ARCH(2) model when the innovations' law belongs to the quadratic exponential family. In addition, the error terms are conditionally independent, but not necessarily dependent. The consistency and asymptotic normality of the PML estimator are obtained by means of martingale techniques.     

A COMPUTER SIMULATION MODEL OF AN INDUSTRIAL WORK GROUP

The paper illustrates the desirability and feasibility of the computer simulation technique in socio-psychological research. A computer simulation model of a five-man industrial work group is constructed. After the model has successfully passed a two stage validation procedure, an experimentation phase is conducted. In a 2 times 3 replicated factorial experiment, five years of simulated weekly data is used to test several hypotheses which relate the independent variables–supervisory style and worker interpersonal orientation–to productivity, worker job satisfaction and group cohesiveness. The hypotheses were derived from the findings of prior short-lived laboratory and field research. The study indicates that the computer simulation approach is a valuable adjunct to the classical organizational research techniques.     

The Future of Nuclear Power: Value Orientations and Risk Perception

Since the turn of the 21st century, there has been a revival of interest in nuclear power. Two decades ago, the expansion of nuclear power in the United States was halted by widespread public opposition as well as rising costs and less than projected increases in demand for electricity. Can the renewed enthusiasm for nuclear power overcome its history of public resistance that has persisted for decades? We propose that attitudes toward nuclear power are a function of perceived risk, and that both attitudes and risk perceptions are a function of values, beliefs, and trust in the institutions that influence nuclear policy. Applying structural equation models to data from a U.S. national survey, we find that increased trust in the nuclear governance institutions reduces perceived risk of nuclear power and together higher trust and lower risk perceptions predict positive attitudes toward nuclear power. Trust in environmental institutions and perceived risks from global environmental problems do not predict attitudes toward nuclear power. Values do predict attitudes: individuals with traditional values have greater support for, while those with altruistic values have greater opposition to, nuclear power. Nuclear attitudes do not vary by gender, age, education, income, or political orientation, though nonwhites are more supportive than whites. These findings are consistent with, and provide an explanation for, a long series of public opinion polls showing public ambivalence toward nuclear power that persists even in the face of renewed interest for nuclear power in policy circles.     

Does federal flood hazard mitigation assistance affect community rating system participation?

With the inexorable march of climate change, increased flooding is inevitable. Understanding the feedback between federal flood mitigation policies and the ways in which local governments build flood resilience is a significant gap in the literature. In particular, the effect that federal flood mitigation grants have on the intensity of local flood mitigation is nonexistent. This work measures flood risk mitigation by using the level of participation in FEMA's Community Rating System (CRS). Communities that participate in the CRS and undertake mitigation are awarded points; more points imply a higher level of participation. Since its inception in 1990, CRS communities have received considerably more federal pre-disaster flood mitigation grants compared to non-CRS communities. This study assesses the effect of federal pre-disaster flood mitigation grants on the level of participation in the CRS program. We use data on Hazard Mitigation Assistance programs and CRS participation data between 2010 and 2015. We link these data to flood risk and socioeconomic information. Our results indicate (i) federal pre-disaster flood mitigation grants do not appear to significantly influence the level of CRS participation, (ii) the effect of flood risk and socioeconomic factors on the level of CRS participation are mixed, and (iii) the current level of CRS participation is influenced by the previous level of CRS participation, which is not tied to federal pre-disaster flood mitigation grant. These findings add to the growing discussions on the drivers and barriers of local flood risk mitigation.     

Large-scale simultaneous inference under dependence

Simultaneous inference allows for the exploration of data while deciding on criteria for proclaiming discoveries. It was recently proved that all admissible post hoc inference methods for the true discoveries must employ closed testing. In this paper, we investigate efficient closed testing with local tests of a special form: thresholding a function of sums of test scores for the individual hypotheses. Under this special design, we propose a new statistic that quantifies the cost of multiplicity adjustments, and we develop fast (mostly linear-time) algorithms for post hoc inference. Paired with recent advances in global null tests based on generalized means, our work instantiates a series of simultaneous inference methods that can handle many dependence structures and signal compositions. We provide guidance on the method choices via theoretical investigation of the conservativeness and sensitivity for different local tests, as well as simulations that find analogous behavior for local tests and full closed testing.