Not in the Same Mental Drawer: Internalized Sexual Stigma,Dissociation, and the Role of Religion in a Sample of Italian Gay Men

ABSTRACT

Several studies have highlighted the relationship between internalized sexual stigma (ISS) and dissociation. The aim of the present study was to empirically investigate this relationship through a quantitative study. The Measure of Internalized Sexual Stigma for Lesbians and Gay Men (MISS-LG) and the Dissociation Scale (DIS) of the Trauma Symptom Inventory (TSI) were administered to 120 Caucasian participants who self-identified as gay men. Findings suggested that dissociative symptomatology, as measured by DIS—an estimation of the use of dissociation as a defense mechanism—was positively associated with MISS general index and all dimensions of MISS, especially the sexuality dimension (ISS-S). Moreover, the effect of the ISS-S on DIS was amplified in Catholic participants, suggesting a moderating role of religiosity. Implications for future research and clinical practice are discussed.     

Belohnungen und Bestrafungen im Netz: Verhaltenskontrolle in Chat-Foren

It is often lamented that the anonymity and physical distance of the Internet prevent effective punishment for antisocial behavior such as insulting, racist or sexist comments. It is thus claimed that anomie regins on the Internet. However, if we look at individual Internet forums and the virtual groups which frequent them, it becomes evident that behavioral rules are often explicated and a row of rewards and punishments are used for behavioral control. With the help of systematic behavioral observations, analysis of documents and field experiments in 24 selected chat forums in the IRC and WWW this study examines how people use technical and social sanctions to control each other’s behavior in computer-mediated communication. Boundaries and possibilities of behavioral control on the Internet are of interest both for those who use chat forums as well as for those who offer chat forums. Accordingly, practical consequences of the results of the study are discussed with special consideration given to the danger of abuse of power.     

M-quantile models with application to poverty mapping

Over the last decade there has been growing demand for estimates of population characteristics at small area level. Unfortunately, cost constraints in the design of sample surveys lead to small sample sizes within these areas and as a result direct estimation, using only the survey data, is inappropriate since it yields estimates with unacceptable levels of precision. Small area models are designed to tackle the small sample size problem. The most popular class of models for small area estimation is random effects models that include random area effects to account for between area variations. However, such models also depend on strong distributional assumptions, require a formal specification of the random part of the model and do not easily allow for outlier robust inference. An alternative approach to small area estimation that is based on the use of M-quantile models was recently proposed by Chambers and Tzavidis (Biometrika 93(2):255–268, 2006) and Tzavidis and Chambers (Robust prediction of small area means and distributions. Working paper, 2007). Unlike traditional random effects models, M-quantile models do not depend on strong distributional assumption and automatically provide outlier robust inference. In this paper we illustrate for the first time how M-quantile models can be practically employed for deriving small area estimates of poverty and inequality. The methodology we propose improves the traditional poverty mapping methods in the following ways: (a) it enables the estimation of the distribution function of the study variable within the small area of interest both under an M-quantile and a random effects model, (b) it provides analytical, instead of empirical, estimation of the mean squared error of the M-quantile small area mean estimates and (c) it employs a robust to outliers estimation method. The methodology is applied to data from the 2002 Living Standards Measurement Survey (LSMS) in Albania for estimating (a) district level estimates of the incidence of poverty in Albania, (b) district level inequality measures and (c) the distribution function of household per-capita consumption expenditure in each district. Small area estimates of poverty and inequality show that the poorest Albanian districts are in the mountainous regions (north and north east) with the wealthiest districts, which are also linked with high levels of inequality, in the coastal (south west) and southern part of country. We discuss the practical advantages of our methodology and note the consistency of our results with results from previous studies. We further demonstrate the usefulness of the M-quantile estimation framework through design-based simulations based on two realistic survey data sets containing small area information and show that the M-quantile approach may be preferable when the aim is to estimate the small area distribution function.     

An Integrated Approach to Select Key Quality Indicators in Transit Services

Social Indicators Research - Recent interests in transit services have captured attention of experts on the monitoring of public transport quality. Previous research focused on relevant models and...     

Maximum likelihood estimation of correlation between maximal oxygen consumption and the 6-min walk test in patients with chronic heart failure

Maximal oxygen consumption (VO₂max) is the standard measurement used to quantify cardiovascular functional capacity and aerobic fitness. Unfortunately, it is a costly, impractical and labour-intensive measure to obtain. The 6-min walk test (6MWT) also assesses cardiopulmonary function, but in contrast to the VO₂max test, it is inexpensive and can be performed almost anywhere. Various medical studies have addressed the correlation between VO₂max and 6MWT in patients with chronic heart failure. Of particular interest, from a medical point of view, is the conditional correlation between the two measures given the individual's height, weight, age and gender. In this paper, we have calculated the maximum likelihood estimate of the conditional correlation in patients with chronic heart failure under the assumption of skew normality. Data were recorded from 98 patients in the Operative Unit of Thoracic Surgery in Bari, Italy. The estimated conditional correlation was found to be much smaller than estimated marginal correlations reported in the medical literature.     

A Critical Discussion and Practical Recommendations on Some Issues Relevant to the Nonprobabilistic Treatment of Uncertainty in Engineering Risk Assessment

Models for the assessment of the risk of complex engineering systems are affected by uncertainties due to the randomness of several phenomena involved and the incomplete knowledge about some of the characteristics of the system. The objective of this article is to provide operative guidelines to handle some conceptual and technical issues related to the treatment of uncertainty in risk assessment for engineering practice. In particular, the following issues are addressed: (1) quantitative modeling and representation of uncertainty coherently with the information available on the system of interest; (2) propagation of the uncertainty from the input(s) to the output(s) of the system model; (3) (Bayesian) updating as new information on the system becomes available; and (4) modeling and representation of dependences among the input variables and parameters of the system model. Different approaches and methods are recommended for efficiently tackling each of issues (1)?(4) above; the tools considered are derived from both classical probability theory as well as alternative, nonfully probabilistic uncertainty representation frameworks (e.g., possibility theory). The recommendations drawn are supported by the results obtained in illustrative applications of literature.     

Clustering via nonparametric density estimation

Although Hartigan (1975) had already put forward the idea of connecting identification of subpopulations with regions with high density of the underlying probability distribution, the actual development of methods for cluster analysis has largely shifted towards other directions, for computational convenience. Current computational resources allow us to reconsider this formulation and to develop clustering techniques directly in order to identify local modes of the density. Given a set of observations, a nonparametric estimate of the underlying density function is constructed, and subsets of points with high density are formed through suitable manipulation of the associated Delaunay triangulation. The method is illustrated with some numerical examples.     

International Migration and Development in Asia: Exploring Knowledge Frameworks

There is revived interest and debate on the relation between international migration and development, with Asia emerging as one important locus for such deliberations. A number of institutions, journals, people and organizations have emerged as key players in these discussions but so far there have been few attempts to investigate the information gathered from the perspective of “knowledge production”. This paper’s objective, therefore, is to outline some of the ways in which knowledge about migration and development is being produced in Asia. We focus on selected aspects of knowledge production to identify the lenses through which much of the work is currently generated and the research imagination resulting from existing approaches.