Yet another minority issue or good news for all? Approaching LGBT issues in European social work education

ABSTRACT

This article addresses the questions of why to include and how to approach LGBT issues in the context of European social work education. Referring to social work’s commitment to LGBT people, the article points out its ongoing relevance as questions of marginalisation and discrimination point far beyond formal equality in legislation and normalisation of homosexuality within existing societal institutions. Furthermore, new questions and dynamics in rapidly changing and highly diverse societal contexts bring about new challenges in addressing LGBT issues. Against this background, the article discusses problems of representation and knowledge and underlines the potential of a queer approach. A queer perspective questions taken-for-granted assumptions about sexual orientation, gender identity and intimate relationships. It challenges normalising categories of sex, gender and desire and brings out possibilities existing beyond the heteronormative order. This way, it offers social work education a powerful theoretical lens to address issues on sexual orientation and gender identity not only as yet another minority issue, but as transversal matter and as good news for all. In this article, we use the acronym LGBT to refer to lesbian, gay, bisexual and trans people. LGBT is meant to include and at the same time emphasise the differences between people who do not (exclusively) define themselves as heterosexual and who cannot or do not want to match or identify with binarities of sex, gender and desire. We do not use the acronym LGBTI because we find it problematic to include intersex people without taking explicitly into account their specific situations and needs. Making a plea for a queer approach, we share – of course – a critical view on categorisations and identity labels.     

Multivariate Return Decomposition: Theory and Implications

In this paper, we propose a model based on multivariate decomposition of multiplicative – absolute values and signs – components of asset returns. In the m-variate case, the marginals for the m absolute values and the binary marginals for the m directions are linked through a 2m-dimensional copula. The approach is detailed in the case of a bivariate decomposition. We outline the construction of the likelihood function and the computation of different conditional measures. The finite-sample properties of the maximum likelihood estimator are assessed by simulation. An application to predicting bond returns illustrates the usefulness of the proposed method.     

On smoothness of Tukey depth contours

The smoothness of Tukey depth contours is a regularity condition often encountered in asymptotic theory, among others. This condition ensures that the Tukey depth fully characterizes the underlying multivariate probability distribution. In this paper we demonstrate that this regularity condition is rarely satisfied. It is shown that even well-behaved probability distributions with symmetrical, smooth and (strictly) quasi-concave densities may have non-smooth Tukey depth contours, and that the smoothness behaviour of depth contours is fairly unpredictable.     

Feature Selection for Consistent Biclustering via Fractional 0–1 Programming

Biclustering consists in simultaneous partitioning of the set of samples and the set of their attributes (features) into subsets (classes). Samples and features classified together are supposed to have a high relevance to each other which can be observed by intensity of their expressions. We define the notion of consistency for biclustering using interrelation between centroids of sample and feature classes. We prove that consistent biclustering implies separability of the classes by convex cones. While previous works on biclustering concentrated on unsupervised learning and did not consider employing a training set, whose classification is given, we propose a model for supervised biclustering, whose consistency is achieved by feature selection. The developed model involves solution of a fractional 0–1 programming problem. Preliminary computational results on microarray data mining problems are reported.This research work was partially supported by NSF, NIH and AirForce grants.     

Does state ownership really matter? The dynamic alignment of China's resource environment and firm internationalization strategies

Recent research suggests that unequal access to home country institutional resources affects firm internationalization strategies. We add to this debate, based on an analysis of state-owned (SOEs) and non-state-owned (NSOEs) Chinese mining firms, by developing a more dynamic and multi-layered understanding of this interplay. We find that home institutional support can be ownership-based or performance-based, whereby the former benefits SOEs and the latter favors high-performing NSOEs. Combined, these support structures serve as institutional control mechanisms in promoting competition, performance and loyalty to national policies. In addition, they establish a permanent link between firm- and home country-specific assets and incentivize firms to develop dynamic resource access capabilities at home and abroad. Our findings inform our understanding of the firms-institutions nexus and Chinese foreign direct investment dynamics, especially in industries of strategic importance to the state.     

Synergy evaluation of non-normalizable dose–response data: Generalization of combination index for the linear effect of drugs

The study of drug synergy plays a prominent role in the search for drug combinations with beneficial interactions. Firstly, in this process, the drug-effect response of individual parts and the mixture needs to be derived. This function is usually well described by Hill (or other logistic or sigmoid) curve. Due to its boundedness, it allows the measured data to be normalized. The normalized data can then be processed by interaction analysis using the Loewe, Bliss, or other models to evaluate possible synergy or antagonism of two or more drugs. However, sometimes, the drug-effect responses observed in pharmaceutical research do not appear to be bounded. Theoretically, the drug-effect curve cannot grow to infinity, but it may be impossible to determine its upper bound within the observed region. In this case, standard models cannot be used, since they assume that data are normalized. The approach of this article bypasses the need to normalize the data, allowing its broader application and usefulness in finding potential synergies in pharmaceutical research.     

The Development of Students' Mathematics Self‐Concept in Relation to Gender: Different Countries,Different Trajectories?

Gender differences in the development of children's and adolescents' academic self‐perceptions have received increasing attention in recent years. This study extends previous research by examining the development of mathematics self‐concept across grades 7–12 in three cultural settings: Australia (Sydney; N=1,333), the United States (Michigan; N=2,443), and Germany (four federal states; N=4,688). Results of latent growth curve models document very similar patterns of self‐concept development in males and females in the three settings. First, gender differences in favor of boys were observed at the beginning of the observation period (grade 7). Second, gender was not significantly related to self‐concept change in either group, meaning that initial differences persisted across time. Third, the results provided no evidence that the form of the longitudinal change trajectories for mathematics self‐concept differed across the cultural settings. This pattern of results is inconsistent with explanatory models that predict converging or diverging gender differences in mathematics self‐concept. Furthermore, the results indicate that self‐concept development may be highly similar across western cultural settings.