Suzi and Mr. S.: Gender role stereotyping in social workers' court reports in custody and access cases.

This paper analyzes the “gender strategies” of a sample of Israeli women social workers as evidenced in the recommendations that they write for the courts on custody and visiting rights for divorcing couples. Textual analysis of these reports reveals what Hochchild terms a “traditional gender strategy,” manifested in a consistent pattern of gender stereotyping. There are clear differences in the way the social workers present the husband and wife as persons, both separately and in relation to one another, and in the roles that they expect them to fulfill, with the man being assigned the provider role and the woman the parent role. Even the way they collect information about the two parents' relationships with their children is different. The paper concludes with a discussion of the practical implications of the findings.     

A Bayesian Evidence Synthesis for Estimating Campylobacteriosis Prevalence

Stakeholders making decisions in public health and world trade need improved estimations of the burden‐of‐illness of foodborne infectious diseases. In this article, we propose a Bayesian meta‐analysis or more precisely a Bayesian evidence synthesis to assess the burden‐of‐illness of campylobacteriosis in France. Using this case study, we investigate campylobacteriosis prevalence, as well as the probabilities of different events that guide the disease pathway, by (i) employing a Bayesian approach on French and foreign human studies (from active surveillance systems, laboratory surveys, physician surveys, epidemiological surveys, and so on) through the chain of events that occur during an episode of illness and (ii) including expert knowledge about this chain of events. We split the target population using an exhaustive and exclusive partition based on health status and the level of disease investigation. We assume an approximate multinomial model over this population partition. Thereby, each observed data set related to the partition brings information on the parameters of the multinomial model, improving burden‐of‐illness parameter estimates that can be deduced from the parameters of the basic multinomial model. This multinomial model serves as a core model to perform a Bayesian evidence synthesis. Expert knowledge is introduced by way of pseudo‐data. The result is a global estimation of the burden‐of‐illness parameters with their accompanying uncertainty.     

A comparison of test statistics for the recovery of rapid growth‐based enumeration tests

This paper considers five test statistics for comparing the recovery of a rapid growth‐based enumeration test with respect to the compendial microbiological method using a specific nonserial dilution experiment. The finite sample distributions of these test statistics are unknown, because they are functions of correlated count data. A simulation study is conducted to investigate the type I and type II error rates. For a balanced experimental design, the likelihood ratio test and the main effects analysis of variance (ANOVA) test for microbiological methods demonstrated nominal values for the type I error rate and provided the highest power compared with a test on weighted averages and two other ANOVA tests. The likelihood ratio test is preferred because it can also be used for unbalanced designs. It is demonstrated that an increase in power can only be achieved by an increase in the spiked number of organisms used in the experiment. The power is surprisingly not affected by the number of dilutions or the number of test samples. A real case study is provided to illustrate the theory. Copyright © 2013 John Wiley & Sons, Ltd.     

Catastrophe Risk Models for Evaluating Disaster Risk Reduction Investments in Developing Countries

Major natural disasters in recent years have had high human and economic costs, and triggered record high postdisaster relief from governments and international donors. Given the current economic situation worldwide, selecting the most effective disaster risk reduction (DRR) measures is critical. This is especially the case for low‐ and middle‐income countries, which have suffered disproportionally more economic and human losses from disasters. This article discusses a methodology that makes use of advanced probabilistic catastrophe models to estimate benefits of DRR measures. We apply such newly developed models to generate estimates for hurricane risk on residential structures on the island of St. Lucia, and earthquake risk on residential structures in Istanbul, Turkey, as two illustrative case studies. The costs and economic benefits for selected risk reduction measures are estimated taking account of hazard, exposure, and vulnerability. We conclude by emphasizing the advantages and challenges of catastrophe model‐based cost‐benefit analyses for DRR in developing countries.     

A Novel Human Error Probability Assessment Using Fuzzy Modeling

Human error is one of the significant factors contributing to accidents. Traditional human error probability (HEP) studies based on fuzzy number concepts are one of the contributions addressing such a problem. It is particularly useful under circumstances where the lack of data exists. However, the degree of the discriminability of such studies may be questioned when applied under circumstances where experts have adequate information and specific values can be determined in the abscissa of the membership function of linguistic terms, that is, the fuzzy data of each scenario considered are close to each other. In this article, a novel HEP assessment aimed at solving such a difficulty is proposed. Under the framework, the fuzzy data are equipped with linguistic terms and membership values. By establishing a rule base for data combination, followed by the defuzzification and HEP transformation processes, the HEP results can be acquired. The methodology is first examined using a test case consisting of three different scenarios of which the fuzzy data are close to each other. The results generated are compared with the outcomes produced from the traditional fuzzy HEP studies using the same test case. It is concluded that the methodology proposed in this study has a higher degree of the discriminability and is capable of providing more reasonable results. Furthermore, in situations where the lack of data exists, the proposed approach is also capable of providing the range of the HEP results based on different risk viewpoints arbitrarily established as illustrated using a real‐world example.     

LABOR CONTRACTS AND FLEXIBILITY: EVIDENCE FROM A LABOR MARKET REFORM IN SPAIN

This paper evaluates the effects of a labor market reform in Spain that removed restrictions on fixed‐term or temporary contracts. Our empirical results are based on longitudinal firm‐level data that cover observations before and after the reform. We posit and estimate a dynamic labor demand model with indefinite and fixed‐term labor contracts, and a general structure of labor adjustment costs. Experiments using the estimated model show important positive effects of the reform on total employment (i.e., a 3.5% increase) and job turnover. There is a strong substitution of permanent by temporary workers (i.e., a 10% decline in permanent employment). The effects on labor productivity and the value of firms are very small. In contrast, a counterfactual reform that halved all firing costs would produce the same employment increase as the actual reform, but much larger improvements in productivity and in the value of firms. (JEL J23, J32, J41)     

Applying the international wellbeing index to investigate subjective wellbeing of New Zealanders with European and with Maori heritage

Abstract

The International Wellbeing Index (IWI), a global measure for investigating subjective wellbeing, consists of a Personal Wellbeing Index (PWI) and a National Wellbeing Index (NWI). The index is applied to the two largest ethnic populations in New Zealand—New Zealanders with European heritage and New Zealanders with Maori heritage. Psychometric characteristics of the IWI for both subsamples compare favourably to those found in other countries. However, for both subsamples, the absolute value of reported subjective wellbeing is lower than expected. Consistent with other social indicators, New Zealanders with Maori heritage show even lower values of PWI and NWI than New Zealanders with European heritage.     

Ambivalent sexism and attitudes toward women who engage in premarital sex in Turkey

This study examined the relationship of ambivalent sexism, political conservatism, demographic variables (age, education, and gender), and prior sexual experience to Turkish men's and women's attitudes toward women who engage in premarital sex. Participants included 124 Turkish undergraduate students and 60 nonstudent Turkish adults. Benevolent but not hostile sexism uniquely predicted more negative views of women who engage in premarital sex once other variables were controlled. Regression analyses demonstrated that for both men and women, older, more politically conservative and less sexually experienced respondents and more educated men (but not women) respondents were more likely to disapprove of women who engage in premarital sex. Similarly, regression analysis revealed that men who were older, politically conservative, and less sexually experienced expressed stronger preferences for marrying a virgin. Both hostile and benevolent sexism predicted men's preference for marrying a virgin after all other variables were controlled.     

A New Multicriteria Risk Mapping Approach Based on a Multiattribute Frontier Concept

Invasive species risk maps provide broad guidance on where to allocate resources for pest monitoring and regulation, but they often present individual risk components (such as climatic suitability, host abundance, or introduction potential) as independent entities. These independent risk components are integrated using various multicriteria analysis techniques that typically require prior knowledge of the risk components’ importance. Such information is often nonexistent for many invasive pests. This study proposes a new approach for building integrated risk maps using the principle of a multiattribute efficient frontier and analyzing the partial order of elements of a risk map as distributed in multidimensional criteria space. The integrated risks are estimated as subsequent multiattribute frontiers in dimensions of individual risk criteria. We demonstrate the approach with the example of Agrilus biguttatus Fabricius, a high‐risk pest that may threaten North American oak forests in the near future. Drawing on U.S. and Canadian data, we compare the performance of the multiattribute ranking against a multicriteria linear weighted averaging technique in the presence of uncertainties, using the concept of robustness from info‐gap decision theory. The results show major geographic hotspots where the consideration of tradeoffs between multiple risk components changes integrated risk rankings. Both methods delineate similar geographical regions of high and low risks. Overall, aggregation based on a delineation of multiattribute efficient frontiers can be a useful tool to prioritize risks for anticipated invasive pests, which usually have an extremely poor prior knowledge base.