The relationship between sex guilt and sexual desire in a community sample of Chinese and Euro-Canadian women

Many studies have documented significant differences in sexual desire between individuals of European and Chinese descent, but few have examined the mechanisms that underlie these differences. A recent study of university students found that sex guilt is one mechanism by which culture influences sexual desire among Chinese and Euro-Canadian women. The goal of this study was to examine whether sex guilt also mediates the relationship between ethnicity and sexual desire in a sample that is more representative of women in the general population. Euro-Canadian (n = 78; mean age = 42.1 years) and Chinese (n = 87; mean age = 42.8 years) women were recruited from the community. Euro-Canadian women reported greater sexual desire and less sex guilt. In the entire sample, sex guilt mediated the relationship between ethnicity and sexual desire such that the Chinese women reported greater sex guilt, which, in turn, was associated with lower sexual desire. Among the Chinese women, sex guilt mediated the relationship between mainstream acculturation (degree of Westernization) and sexual desire such that more Westernized Chinese women reported less sex guilt, which, in turn, was associated with greater sexual desire. These results support recent findings and further suggest that sex guilt may be one mechanism by which ethnicity affects sexual desire.     

The "Special Path" and the Social Order in Today's Russia

Research data show that Russians still strongly adhere to the notion of a uniquely Russian path as a source of identity, but that this sense of uniqueness is based more on a negative view of the other than a positive view of the contents of Russian uniqueness. This view reinforces a degree of Russian isolation from the outside world, a sense of being surrounded by hostile forces, and a rejection of the West.     

The Myth of a Systemic Crisis in Russia After the Great Reforms of the 1860s-1870s

The material situation of Russia's population measurably improved between 1861 and 1913.     

Two-stage hierarchical modeling for analysis of subpopulations in conditional distributions

In this work, we develop modeling and estimation approach for the analysis of cross-sectional clustered data with multimodal conditional distributions where the main interest is in analysis of subpopulations. It is proposed to model such data in a hierarchical model with conditional distributions viewed as finite mixtures of normal components. With a large number of observations in the lowest level clusters, a two-stage estimation approach is used. In the first stage, the normal mixture parameters in each lowest level cluster are estimated using robust methods. Robust alternatives to the maximum likelihood estimation are used to provide stable results even for data with conditional distributions such that their components may not quite meet normality assumptions. Then the lowest level cluster-specific means and standard deviations are modeled in a mixed effects model in the second stage. A small simulation study was conducted to compare performance of finite normal mixture population parameter estimates based on robust and maximum likelihood estimation in stage 1. The proposed modeling approach is illustrated through the analysis of mice tendon fibril diameters data. Analyses results address genotype differences between corresponding components in the mixtures and demonstrate advantages of robust estimation in stage 1.     

Structural changes and unit roots in non-stationary time series

The problem of testing hypotheses of a unit root and a structural change in one-dimensional time series is considered. A non-parametric two-step method for solution of the problem is proposed. The method is based upon the modified Kolmogorov-Smirnov statistic. At the first step of this method the hypothesis of stationarity of an obtained sample is tested against a unified alternative of a statistical non-stationarity of a time series (a unit root or a structural change). At the second step of the proposed method, in case of rejecting the stationarity hypothesis at the first step, the hypothesis of an unknown structural change is tested against the alternative of a unit root. We prove that probabilities of errors (false classification of hypotheses) of the proposed method converge to zero as the sample size tends to infinity.     

On Robust Analysis of a Normal Location Parameter

Pericchi and Smith considered a normal location parameter problem with double-exponential and Student t prior distributions. These two prior distributions both belong to the class of scale mixtures of normal distributions and are useful in providing a robust analysis of the normal location parameter problem. In this paper we extend the analysis to other scale mixtures of normal distributions, such as the exponential power and the symmetric stable distributions.     

Politique et expertise scientifique. La régulation européenne des médicaments

A study of the EU system for regulating medicinal products is used to show the usefulness of distinguishing between policy-making and scientific expertise when analyzing political decision-making. This approach presupposes identifying the characteristics of scientific expertise. The experts responsible for assessing drugs have to combine knowledge and action. Questions are raised about how work is shared between decision-makers and experts. In the case of medicinal products, the work of experts has absorbed decision-making. Lest we waver between explanations in terms either of science or else of politics, it is necessary to substantively identify expertise’s political dimensions. Two conceptions — the “healthy man’s” and the “sick man’s” — of the purpose of assessing medicinal products stand out in debates; but political authorities pay no heed to them.