German public opinion has become less polarised over the past 30 years

The polarisation of public opinion has been an intensely researched phenomenon in the United States, but there has been relatively little research conducted on polarisation in European countries. Using survey responses from a large number of issue groups over the last 30 years, Simon Munzert and Paul C. Bauer outline the results of a study on polarisation in Germany. In contrast to the American case, they find that German public opinion has in fact become significantly less polarised over recent decades

Political Depolarization in German Public Opinion, 1980-2010

Little is known about political polarization in German public opinion. This article offers an issue-based perspective and explores trends of opinion polarization in Germany. Public opinion polarization is conceptualized and measured as alignment of attitudes. Data from the German General Social Survey (1980 to 2010) comprise attitudes towards manifold issues, which are classified into several dimensions. This study estimates multilevel models that reveal general and issue- as well as dimension-specific levels and trends in attitude alignment for both the whole German population and sub-groups. It finds that public opinion polarization has decreased over the last three decades in Germany. In particular, highly educated and more politically interested people have become less polarized over time. However, polarization seems to have increased in attitudes regarding gender issues. These findings provide interesting contrasts to existing research on the American publi

The conventional wisdom about tactical voting is wrong

Have you ever voted for another party because you felt that your party had no chance of winning the seat? If yes, then you might be among the 5 to 10 per cent of tactical voters. In this article, Michael Herrmann, Simon Munzert, and Peter Selb explain how, contrary to popular belief, the Liberal Democrats were the big winners of tactical voting in 1997 and 2001

The importance of citizenship for deserving COVID-19 treatment

Immigrant non-citizens are often considered less deserving than citizens of welfare and other public services. The logic is that valuable and scarce public resources must be limited somehow, and the club of citizens is one way of drawing a boundary. In this paper, we examine how far that boundary extends, by analyzing the extent to which Germans prioritize citizens over non-citizens for access to life-saving healthcare. We implement a conjoint experiment to elicit preferences in the context of the COVID-19 pandemic. The data were collected between April 2020 and March 2021, in 23 waves of an online rolling cross-sectional survey with roughly 17,000 respondents. Our main finding is that citizens are viewed as more deserving of healthcare than non-citizen immigrants, a relationship that is sizeable and robust. Our findings have implications for debates about social boundaries and how to allocate resources in Western Europe

Ein Ansatz zur Vorhersage der Erststimmenanteile bei Bundestagswahlen

Almost half of the total seats in the German Bundestag are awarded through first-past-the post elections at the electoral-district level. However, many election forecasting models do not consider this. In this paper we present an approach to predicting the candidate-vote shares at the district level for the German Federal Elections. To that end, we combine the national-level election prediction model from zweitstimme.org with two district-level prediction models, a linear regression and an artificial neural network, that both use the same candidate and district characteristics for their predictions. All data in our approach are publicly available prior to the respective election; thus, our model yields real forecasts. The model is therefore able to provide valuable information to running candidates and the interested public in future elections. Moreover, our prediction results are also relevant for substantive research: with the aid of the resulting odds of winning, better measures can be created to characterize the competitiveness of an electoral district and the expected closeness of electoral-district elections, which can influence political behaviour. Furthermore, the prediction allows empirical statements to be made about the expected size of the Bundestag as well as the composition of its personnel.Nahezu die Hälfte der Bundestagsmandate wird über die Direktwahl in den Wahlkreisen vergeben. Das bleibt in einem Großteil der Wahlprognosemodelle jedoch unberücksichtigt. In diesem Beitrag stellen wir einen Ansatz zur Vorhersage der Erststimmenanteile in Wahlkreisen für Bundestagswahlen vor. Dazu kombinieren wir das Zweitstimmenvorhersagemodell von zweitstimme.org mit zwei Erststimmenmodellen, einer linearen Regression und einem künstlichen neuronalen Netzwerk, welche Kandidierenden- und Wahlkreischarakteristika zur Vorhersage nutzen. Für unseren Ansatz sind alle verwendeten Daten vor der jeweiligen Wahl öffentlich verfügbar und somit für eine echte Vorhersage nutzbar. Das Modell kann so bei künftigen Wahlen wertvolle Informationen für Kandidierende und die interessierte Öffentlichkeit bereitstellen. Die Vorhersagen sind darüber hinaus auch für erklärende Forschung relevant: Mithilfe der resultierenden Gewinnwahrscheinlichkeiten lassen sich bessere Messinstrumente zur Charakterisierung der Kompetitivität eines Wahlkreises und der zu erwartenden Knappheit des Wahlkreisrennens erstellen, welche politisches Verhalten beeinflussen können. Zudem erlaubt die Vorhersage, empirische Aussagen zur zu erwartenden Größe des Bundestags sowie seiner personellen Zusammensetzung zu treffen

The 2020 report of The Lancet Countdown on health and climate change: responding to converging crises

The Lancet Countdown is an international collaboration, established to provide an independent, global monitoring system dedicated to tracking the emerging health profile of the changing climate. The 2020 report presents 43 indicators across five sections: climate change impacts, exposures, and vulnerability; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. This report represents the findings and consensus of the 35 leading academic institutions and UN agencies that make up the Lancet Countdown, and draws on the expertise of climate scientists, geographers, and engineers; of energy, food, and transport experts; and of economists, social and political scientists, data scientists, public health professionals, and doctors

Deborah Nolan, Duncan Temple Lang: XML and web technologies for data sciences with R

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