Roma and the politics of double discourse in contemporary Europe

ABSTRACT

The article analyses the politics of ‘double discourse’ in relation to Roma that has evolved in contemporary neoliberal Europe. On the one hand, the double discourse promotes the integration, rights and equal opportunities of Roma, on the other, it denies recognition of, and ways to address, enduring structural violence and rising social insecurity. The article argues that the politics of ‘double discourse’, as a neoliberal approach towards Roma, is structured by two contradictory discourses that speak to different audiences, using duplicitous approaches to create anti-Roma consensus and maintain the critical difference and subordinated position of the racialised Romani populations in Europe. By studying the representation of Roma in the cases of so-called 'child theft' in Greece and Ireland, and in the recent ‘refugee crisis’, the paper identifies and discusses three dimensions of contemporary neoliberal double discourse: racialised de-Europeanisation, neoliberal undeservingness and (dis)articulation of citizenship.     

Dynamic heterogeneity: a framework to promote ecological integration and hypothesis generation in urban systems

Urban areas are understood to be extraordinarily spatially heterogeneous. Spatial heterogeneity, and its causes, consequences, and changes, are central to ecological science. The social sciences and urban design and planning professions also include spatial heterogeneity as a key concern. However, urban ecology, as a pursuit that integrates across these disciplines, lacks a theoretical framework that synthesizes the diverse and important aspects of heterogeneity. This paper presents the concept of dynamic heterogeneity as a tool to explore how social and ecological heterogeneities interact and how they together act as both an outcome of past interactions and a driver future heterogeneity and system functions. To accomplish this goal, we relate heterogeneity to the fundamental concept of the human ecosystem. The human ecosystem concept identifies key processes that require operationalized models of dynamic heterogeneity in three process realms: the flow of materials, the assembly of urban ecosystem biota, and the locational choices humans make concerning land. We exemplify a specific dynamic model of heterogeneity in each of these realms, and indicate a range of complementary statistical approaches to integrate the drivers and outcomes of dynamic heterogeneity across the three realms. We synthesize a hierarchical framework for a theory of dynamic urban heterogeneity, noting its complementarity to other major urban theories and general model approaches. We hypothesize that human actions and structures amplify the dynamics of heterogeneity in urban systems.     

‘Power Differences’ and ‘the Power of Difference’: The Dominance of Secularism as Ontological Injustice

Abstract

Recent religious studies and international relations scholarship has highlighted secularism as a critical element in dominant modes of identity, power, and exclusion in global politics. Yet, the implications of these insights for global justice theory and practice have rarely been considered. This article suggests that the current dominance of secularism within global justice theory and practice risks undermining the global justice project. Specifically, I argue that secularism’s dominance constitutes an ontological injustice, where both alternative non-secular visions of the world and visions of alternative non-secular worlds are subordinated to secular ontologies. However, this argument raises a crucial question: if, despite secularism’s claim to neutrality and universality, the dominance of secular ontologies contributes to rather than ameliorates injustice, the question that remains is: what are the alternatives? The article concludes by exploring some preliminary responses to this question.     

Parenting perceptions among college students: A qualitative examination

This study assessed the knowledge and attitudes of young adults without children in regard to discipline and parenting practices. A qualitative design was utilized (n?=?26) with semistructured focus groups. Results indicated participants believed discipline is important, with spanking and loss of privileges being the most effective strategy for behavior change. The majority of participants reported plans to discipline future children the way in which they were disciplined, suggesting a high percentage intend to utilize spanking. Findings suggest that personal experiences shape parenting beliefs, attitudes, and knowledge. Results inform efforts at educating future parents on appropriate parenting practices and indicate the need for protocols for young adults to educate about practices that may diverge from their personal experiences.     

Differences in Experiences of Discrimination in Accessing Social Services Among Transgender/Gender Nonconforming Individuals by (Dis)Ability

Transgender and gender nonconforming (GNC) individuals frequently experience discrimination and potentially a lack of respect from service providers, suggesting they have decreased access to professionals with cultural competency. Similarly, people with disabilities experience higher levels of discrimination in social services than their nondisabled counterparts. From an intersectional perspective, this study examines rates of discrimination in accessing social services faced by transgender and GNC people, comparing across ability. Data indicate that although transgender and GNC individuals of all abilities experience gender-based discrimination when accessing social services, those with disabilities experience higher levels of antitransgender discrimination in mental health centers, rape crisis centers, and domestic violence shelters.     

Investment model predictions of workplace ostracism on K–12 teachers’ commitment to their schools and the profession of teaching

The purpose of this study was to determine how the ostracism of K-12 teachers influences their commitment to their schools and commitment to the teaching profession. The investment model was used to situate ostracism as a predictor of teacher commitment. Participants were 200 full-time K-12 teachers who completed a survey assessing their experiences with ostracism at work and investment model variables (i.e., investments, quality of alternatives, satisfaction, and commitment). Results confirmed investment model predictions with teachers’ investments, quality of alternatives, and satisfaction predicting their commitment to their schools and profession. Results of mediation models also demonstrated that controlling for teachers’ investments and quality of alternatives, ostracism predicted commitment indirectly through its effect on satisfaction. This study revealed that teacher commitment is explained by investment model predictions, but after controlling for those predictions, is further explained by ostracism from teacher colleagues.     

Computationally and statistically efficient model fitting techniques

A significant challenge in fitting metamodels of large-scale simulations with sufficient accuracy is in the computational time required for rigorous statistical validation. This paper addresses the statistical computation issues associated with the Bootstrap and modified PRESS statistic, which yield key metrics for error measurements in metamodelling validation. Experimentation is performed on different programming languages, namely, MATLAB, R, and Python, and implemented on different computing architectures including traditional multicore personal computers and high-power clusters with parallel computing capabilities. This study yields insight into the effect that programming languages and computing architecture have on the computational time for simulation metamodel validation. The experimentation is performed across two scenarios with varying complexity.     

Semi-parametric segmentation of multiple series using a DP-Lasso strategy

We consider a semi-parametric approach to perform the joint segmentation of multiple series sharing a common functional part. We propose an iterative procedure based on Dynamic Programming for the segmentation part and Lasso estimators for the functional part. Our Lasso procedure, based on the dictionary approach, allows us to both estimate smooth functions and functions with local irregularity, which permits more flexibility than previous proposed methods. This yields to a better estimation of the functional part and improvements in the segmentation. The performance of our method is assessed using simulated data and real data from agriculture and geodetic studies. Our estimation procedure results to be a reliable tool to detect changes and to obtain an interpretable estimation of the functional part of the model in terms of known functions.     

Analysis of Type-II hybrid censored competing risks data

Kundu and Gupta [Analysis of hybrid life-tests in presence of competing risks. Metrica. 2007;65:159–170] provided the analysis of Type-I hybrid censored competing risks data, when the lifetime distributions of the competing cause of failures follows exponential distribution. In this paper, we consider the analysis of Type-II hybrid censored competing risks data. It is assumed that latent lifetime distributions of the competing causes of failures follow independent exponential distributions with different scale parameters. It is observed that the maximum likelihood estimators of the unknown parameters do not always exist. We propose the modified estimators of the scale parameters, which coincide with the corresponding maximum likelihood estimators when they exist, and asymptotically they are equivalent. We obtain the exact distribution of the proposed estimators. Using the exact distributions of the proposed estimators, associated confidence intervals are obtained. The asymptotic and bootstrap confidence intervals of the unknown parameters are also provided. Further, Bayesian inference of some unknown parametric functions under a very flexible Beta-Gamma prior is considered. Bayes estimators and associated credible intervals of the unknown parameters are obtained using the Monte Carlo method. Extensive Monte Carlo simulations are performed to see the effectiveness of the proposed estimators and one real data set has been analysed for the illustrative purposes. It is observed that the proposed model and the method work quite well for this data set.     

A varying coefficient approach to estimating hedonic housing price functions and their quantiles

The varying coefficient (VC) model introduced by Hastie and Tibshirani [26 T. Hastie and R. Tibshirani, Varying-coefficient models, J. R. Statist. Soc. (Ser. B) 55 (1993), pp. 757–796.[Web of Science ®] , [Google Scholar]] is arguably one of the most remarkable recent developments in nonparametric regression theory. The VC model is an extension of the ordinary regression model where the coefficients are allowed to vary as smooth functions of an effect modifier possibly different from the regressors. The VC model reduces the modelling bias with its unique structure while also avoiding the ‘curse of dimensionality’ problem. While the VC model has been applied widely in a variety of disciplines, its application in economics has been minimal. The central goal of this paper is to apply VC modelling to the estimation of a hedonic house price function using data from Hong Kong, one of the world's most buoyant real estate markets. We demonstrate the advantages of the VC approach over traditional parametric and semi-parametric regressions in the face of a large number of regressors. We further combine VC modelling with quantile regression to examine the heterogeneity of the marginal effects of attributes across the distribution of housing prices.