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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 public.

Sexual harassment has become an important topic in the past few years. There have been many recent developments that have been shaping and redefining what sexual harassment actually is and how to deal with it in the workplace.

Das IFAF – Institut für angewandte Forschung Berlin sowie Studierende zweier Hochschulen und verschiedene Projektpartner erarbeiteten das interdisziplinäre Projekt "XICHT" in Berlin und Potsdam, um den öffentlichen Raum temporär in eine Bühne für behördliche Transparenz zu verwandeln. Ziel war es, komplexe wissenschaftliche Inhalte für ein Publikum niedrigschwellig zu kommunizieren und zu vermitteln.

von Paul Bauer, Katrina Gagelmann, Maria Krautz

AbstractWhile a large body of literature empirically documents an electoral advantage for local candidates, the exact mechanisms accounting for this effect remain less clear. We integrate theories on the political geography of candidate-voter relations with socio-psychological accounts of citizens' local attachment, arguing that citizens vote for candidates from their own local communities as an expression of their place-based identity. To test our argument, we exploit a unique feature of the German mixed-member electoral system. We identify the causal effect of candidates' localness by relying on within-electoral-district variation coupled with a geo-matching strategy on the level of municipalities ($$\hbox {N}=11175$$

N
=
11175

). The results show that voters exhibit a strong bias in favor of local candidates even when they are not competitive. More than only expecting particularistic benefits from representatives, citizens appear to vote for candidates from their own local community to express their place-based social identity.

A trusted media is crucial for a politically informed citizenry, yet media trust has become fragile in many Western countries. An underexplored aspect is the link between media (dis)trust and populism. The authors visualize media trust across news outlets and partisanship in Germany, for both mainstream and "alternative" news sources. For each source, average trust is grouped by partisanship and sorted from left to right, allowing within-source comparisons. The authors find an intriguing horseshoe pattern for mainstream media sources, for which voters of both populist left-wing and right-wing parties express lower levels of trust. The underlying distribution of individual responses reveals that voters of the right-wing populist party are especially likely to "not at all" trust the mainstream outlets that otherwise enjoy high levels of trust. The media trust gap between populist and centrist voters disappears for alternative sources, for which trust is generally low.

AbstractWe propose an alternative decision-making methodology based on adopting a mixed risk-averse and risk-taking behavior, improving the objectivity of decision-making. We demonstrate the methodology by prioritizing Iranian tourism centers' activity under pandemic conditions, providing insights to policymakers on those to keep active or reduce the activity of – hence, those worth developing ahead of future disease outbreaks. This research follows a three-step methodology. First, criteria for evaluation are identified and categorized into tourist attractions, infrastructure, and healthcare dimensions. Second, criterion weights are calculated based on expert opinions, collected using a best-worst method-based questionnaire. Third, tourism centers are evaluated by employing risk-averse and risk-taking best-worst methods. We identify popular attractions, general services, and drugstore accessibility as the primary indicators of tourist attractions, infrastructure, and healthcare, respectively. By clustering tourism centers using K-means algorithm, we find that, in order, the cities of Semnan, Kerman and Zahedan are the tourism centers most suited to staying active during disease outbreaks. For multi-criteria decision-making problems that rely on experts' evaluations, the proposed methodology can improve the reliability of decision-making. The methodology and framework presented can be used to support various types of decision-making, including evaluation, ranking, selection or sorting.