Measuring Congruence Between Voters and Parties in Online Surveys: Does Question Wording Matter?

Congruence on policies between political parties and voters is a frequently assumed re­quirement for democracy. To be able to study this, we should be able to calculate accurate and precise measures of policy congruence in political systems. This could then tell us more about the political system we study, and the "distances" that exist between parties and voters on either issues or broader ideological dimensions. Here, I draw on experimental data from a Voting Advice Application to show that the wording of the issues can influence the degree of congruence one measures. Yet, this comes with the complication that this influence depends on the type of issue, the characteristics of the voters themselves, and the party the congruence is calculated with. These findings should serve as a warning for those who aim to measure congruence that even minor changes in question-wording can (but do not have to) cause relatively large changes in congruence, especially when many parties are involved and the differences between the congruences are small

A Move Forward: Exploring National Identity Through Non-linear Principal Component Analysis in Germany

In research on national identity, scholars have developed a wide variety of approaches to measure and better understand this ubiquitous yet complex concept. To date, most of these approaches have been theory-driven, while only a very few have been data-driven. In this article, we aim to contribute to the latter by introducing a new data-driven method that has not been applied yet - that of non-linear principal component analysis (NLPCA). In contrast to other commonly used methods such as factor analysis, NLPCA distinguishes itself by making relatively few assumptions about the data and by allowing for greater flexibility when discovering underlying dimensions of such a complex concept as national identity. Drawing on the 2013 ISSP National Identity module, our analysis focuses on the case of Germany, also taking into account Western and Eastern Germany. Running an NLPCA, we find four dimensions that cover the multidimensionality of national identity: nationalistic attitudes, national pride and attachment, cosmopolitan beliefs, and membership criteria defining national belonging. This article contributes to the empirical debate on measuring national identity by suggesting a new and flexible methodological approach that better grasps the concept's complexity and which we believe can move empirical research on national identity forward in and beyond Germany

Heightened SAM- and HPA-axis activity during acute stress impairs decision-making: A systematic review on underlying neuropharmacological mechanisms

Individuals might be exposed to intense acute stress while having to make decisions with far-reaching consequences. Acute stress impairs processes required for decision-making by activating different biological stress cascades that in turn affect the brain. By knowing which stress system, brain areas, and receptors are responsible for compromised decision-making processes, we can effectively find potential pharmaceutics that can prevent the deteriorating effects of acute stress. We used a systematic review procedure and found 44 articles providing information on this topic. Decision-making processes could be subdivided into 4 domains (cognitive, motivational, affective, and predictability) and could be referenced to specific brain areas, while mostly being impaired by molecules associated with the sympathetic-adrenal-medullar and hypothalamic-pituitary-adrenal axes. Potential drugs to alleviate these effects included α1 and β adrenoceptor antagonists, α2 adrenoceptor agonists, and corticotropin releasing factor receptor1/2 antagonists, while consistent stress-like effects were found with yohimbine, an α2 adrenoceptor antagonist. We suggest possible avenues for future research

Long-term trajectories of depressive symptoms in deployed military personnel: A 10-year prospective study

Background: Military missions, especially those involving combat exposure, are associated with an increased risk of depression. Understanding the long-term course of depressive symptoms post-deployment is important to improve decision-making regarding deployment and mental health policies in the military. This study investigates trajectories of depressive symptoms in the Dutch army, exploring the influence of factors such as demographics, early-life trauma, posttraumatic stress disorder (PTSD) symptoms, and deployment stressors. Methods: A cohort of 1032 military men and women deployed to Afghanistan (2005–2008) was studied from pre- to 10 years post-deployment. Depressive and PTSD symptoms were assessed using the Symptom CheckList-90 and the Self-Rating Inventory for PTSD. Demographics, early trauma, and deployment experiences were collected at baseline and after deployment, respectively. Latent Class Growth Analysis was used to explore heterogeneity in trajectories of depressive symptoms over time. Results: Four trajectories were found: resilient (65%), intermediate-stable (20%), symptomatic-chronic (9%), and late-onset-increasing (6%). The resilient group experienced fewer deployment stressors, while the symptomatic-chronic group reported more early life traumas. Trajectories with elevated depressive symptoms consistently demonstrated higher PTSD symptoms. Limitations: Potential nonresponse bias and missing information due to the longitudinal design and extensive follow-up times. Conclusions: This study identified multiple trajectories of depressive symptoms in military personnel up to 10 years post-deployment, associated with early trauma, deployment stressors, adverse life events and PTSD symptoms. The prevalence of the resilient trajectory suggests a substantial level of resilience among deployed military personnel. These findings provide valuable insights and a foundation for further research

Introduction to Quantitative Text Analysis

Welcome to our introductory textbook on quantitative text analysis! This book originated as a collection of assignments and lecture slides that we prepared for the ECPR Winter and Summer Schools in Methods and Techniques. Later, as we taught the Introduction to Quantitative Analysis course at the ECPR Schools, the MethodsNET Summer School, and seminars at the Max Planck Institute for the Study of Societies, Goethe University Frankfurt, Chalmers University, and the Cyprus University of Technology, we added more and more material and text, resulting in this book. The version you see today has been updated with the help of a grant from the [Learning Development Network] (https://ldn.cut.ac.cy/) at the Cyprus University of Technology. For now, the book focuses on some of the best-known quantitative text analysis methods in the field, showing what they are and how to run them in R. So why bother with quantitative content analysis? For one thing, we can say that developments over the last twenty years have made research using quantitative text analysis a particularly exciting proposition. First, the huge increase in computing power has made it possible to work with large amounts of text. Second, there is the development of R - a free, open-source, cross-platform statistical software. This development has enabled many researchers and programmers to develop packages for statistical methods for working with text. In addition, the spread of the internet has made many interesting sources of textual data available in digital form. Add to this the emergence of social media as a massive source of text generated daily by millions of users around the world. However, quantitative text analysis can be a daunting experience for someone unfamiliar with quantitative methods or programming. Our aim with this book is to guide you through it, combining theoretical explanations with a step-by-step explanation of the code. There are also several exercises designed for those with little or no experience in text analysis, R, or quantitative methods. Ultimately, we hope that you will find this book not only informative but also engaging and educational

Patterns in the Press Releases of Trade Unions: How to Use Structural Topic Models in the Field of Industrial Relations

Quantitative text analysis and the use of large data sets have received only limited attention in the field of Industrial Relations. This is unfortunate, given the variety of opportunities and possibilities these methods can address. We demonstrate the use of one promising technique of quantitative text analysis - the Structural Topic Model (STM) - to test the Insider-Outsider theory. This technique allowed us to find underlying topics in a text corpus of nearly 2,000 German trade union press releases (from 2000 to 2014). We provide a step-by-step overview of how to use STM since we see this method as useful to the future of research in the field of Industrial Relations. Until now the methodological publications regarding STM mostly focus on the mathematics of the method and provide only aminimal discussion of their implementation. Instead, we provide a practical application of STM and apply this method to one of the most prominent theories in the field of Industrial Relations. Contrary to the original Insider-Outsider arguments, but in line with the current state of research, we show that unions do in fact use topics within their press releases which are relevant for both Insider and Outsider groups.Quantitative Textanalysen und die Verwendung von großen Datensätzen wurden im Bereich der Industriellen Beziehungen bisher nur wenig Aufmerksamkeit geschenkt. Das ist bedauerlich, wenn man bedenkt, welche Vielfalt an Möglichkeiten diese Methoden bieten. Wir zeigen daher wie eine neue und vielversprechende Technik der quantitativen Textanalyse - Structural Topic Model (STM) - eingesetzt werden kann, um große Datenmengen zu reduzieren und die Insider-Outsider Theorie zu testen. Diese Technik ermöglicht es in einem Textkorpus von fast 2000 Pressemitteilungen deutscher Gewerkschaften zwischen 2000 und 2014 die zugrundeliegenden Muster zu finden. Wir geben eine schrittweise Einführung zur Anwendung von STM, weil wir die Zukunft der Forschungsmethodik im Feld der Industriellen Beziehungen auch bei quantitativen Analysetechniken sehen. Bisherige methodologische Literatur zu STM konzentriert sich überwiegend auf die Mathematik der Methodik und weniger auf deren Umsetzung und Diskussion. Daher geben wir ein praktisches Anwendungsbeispiel der STM und testen eine der bekanntesten Theorien im Bereich der Industriellen Beziehungen. Entgegen den ursprünglichen Annahmen der Insider-Outsider Theorie, aber im Einklang mit dem aktuellen Forschungsstand, zeigen wir, dass Gewerkschaften in ihren Pressemitteilungen Themen ansprechen, die sowohl für die Gruppe der Insider als auch für die Gruppe der Outsider relevant sind