Populist Communication in the Context of European Parliament Elections 2014

Over the last decade European democracies have been facing a challenge by the rising force of new populist movements. The emergence of the financial and sovereign debt crisis in Europe created new fertile soil for the strengthening of old-established – and the development of new – populist parties in several EU-member states. José Manuel Barroso, president of the European Commission, emphasized his increased unease concerning these developments when he was speaking at the annual Brussels Think Tank Forum on 22. April 2013: “I am deeply concerned about the divisions that we see emerging: political extremes and populism tearing apart the political support and the social fabric that we need to deal with the crisis; […]” (Barroso 2013). Indeed, European elites seem to be increasingly worried by these recent developments which are perceived as an impending stress test of the Union and the project of European integration as a whole (Hartleb 2013). Sure enough, the results of the recent European Parliament Elections 2014 revealed a great support for populist political parties in many societies of EU-member countries. To understand the success of populist parties in Europe it is crucial to first shed light on the nature of populist party communication itself. Significant communicative differences may explain the varying success of populist parties between and within countries, while a pure demand-side approach (i.e. a focus on the preferences of the electorate) often fails to do so (Mudde 2010). The aim of this study is therefore to analyse what different types of populist communication styles emerge during the EP election campaign 2014 and under which conditions populist communication styles are selected by political parties. So far, the empirical measurement of populism has received only scarce attention (Rooduijn & Pauwels 2011). Besides, most of the existing empirical investigations of populism are single case studies (Albertazzi & McDonnell 2008) and scholars have not yet developed systematic methods to measure populism in a comparative way (Rooduijn & Pauwels 2011). This is a consequence of a lack of conceptual clarity which goes along with populism (Taggart 2000; Barr 2009; Canovan 1999) due to its contextual sensitivity. Hence, populism in Europe should be analysed in a way that clarifies the concept of populism and moreover takes into account that the Europeanization of politics has an influence on the type of populist party communication, which is intended in the course of that study.

Bone Volume Fraction and Fabric Anisotropy Are Better Determinants of Trabecular Bone Stiffness than Other Morphological Variables

As our population ages, more individuals suffer from osteoporosis. This disease leads to impaired trabecular architecture and increased fracture risk. It is essential to understand how morphological and mechanical properties of the cancellous bone are related. Morphologyelasticity relationships based on bone volume fraction (BV/TV) and fabric anisotropy explain up to 98% of the variation in elastic properties. Yet, other morphological variables such as individual trabeculae segmentation (ITS) and trabecular bone score (TBS) could improve the stiffness predictions. A total of 743 micro-computed tomography reconstructions of cubic trabecular bone samples extracted from femur, radius, vertebrae and iliac crest were analysed. Their morphology was assessed via 25 variables and their stiffness tensor (inline image) was computed from six independent load cases using micro finite element analyses. Variance inflation factors were calculated to evaluate collinearity between morphological variables and decide upon their inclusion in morphology-elasticity relationships. The statistically admissible morphological variables were included in a multi-linear regression modelling the dependent variable inline image. The contribution of each independent variable was evaluated (ANOVA). Our results show that BV/TV is the best determinant of inline image (inline image=0.889), especially in combination with fabric (inline image=0.968). Including the other independent predictors hardly affected the amount of variance explained by the model (inline image=0.975). Across all anatomical sites, BV/TV explained 87% of the variance of the bone elastic properties. Fabric further described 10% of the bone stiffness, but the improvement in variance explanation by adding other independent factors was marginal (<1%). These findings confirm that BV/TV and fabric are the best determinants of trabecular bone stiffness and show, against common belief, that other morphological variables do not bring any further contribution. These overall conclusions remain to be confirmed for specific bone diseases and post-elastic properties.