Aktuelle Publikationen

Frontline workers who are confronted with crises need enormous resilience and the ability to deal with stress from crisis‐related increases in demands and risks. Simultaneously, populist governments with an illiberal agenda may undermine the work of street‐level bureaucracies for political reasons. Little is known about how deconstruction of the administrative state by populist government—through lacking government support when it is needed the most—affects frontline work. Thus, this article asks: how does lacking support by a populist government affect frontline workers' self‐efficacy when they face a crisis? Based on unique data from an online survey of 3229 Brazilian frontline workers during the early COVID‐19 pandemic, when the Bolsonaro government denied the existence of the pandemic, we test the relationship between government support, demands, and resources on frontline workers' perceived self‐efficacy. Results show that lacking government support from the federal and local government are negatively associated with frontline workers' self‐efficacy. At the same time, resources and managerial support exhibit positive associations—but they cannot always compensate for a lack of government assistance.

In response to changing climatic conditions, people are increasingly likely to migrate. However, individual-level survey data reveal that people mainly state economic, social, or political reasons as the main drivers for their relocation decision–not environmental motives or climate change specifically. To shed light on this discrepancy, we distinguish between sudden-onset (e.g., floods and storms) and slow-onset (e.g., droughts and salinity) climatic changes and argue that the salience of environmental conditions in individuals’ migration decisions is shaped by the type of climate event experienced. Empirically, we combine individual-level surveys with geographic information on objective climatic changes in Vietnam and Kenya. The empirical evidence suggests that sudden-onset climate events make individuals more likely to link environmental conditions to their migration decision and, hence, to identify themselves as “environmental migrants.” Regression analyses support these results and are consistent with the view that slow-onset events tend to be linked with migration decisions that are more economically motivated.

Most states acknowledge the significance of Indigenous rights to rectify past injustices. Yet, on the domestic level, the realization of these rights depends on national policies. For democratic societies, questions about public opinion toward Indigenous policies are thus of great interest but remain largely unstudied. To what extent does the ethnic majority support policies conducive to Indigenous rights realization? And how different are the Indigenous population’s policy preferences? I use original experimental data from a vignette study to investigate these questions in the case of the Sámi people in Norway and Sweden. I hypothesize that groups’ attitudes are shaped by policies’ potential to alter the social status hierarchy between the majority and Indigenous populations. The results provide a nuanced picture. The ethnic majority shows significantly less support for policies facilitating Sámi linguistic, self-governance, and territorial rights. While the Sámi have, in general, more positive attitudes toward such policies, their support seems to be less pronounced than the majority’s resistance. Moreover, as attitudes are surprisingly similar when compared between Norway and Sweden, a country’s existing policy context does not appear to be crucial in the formation of these preferences.

In this article, we analyze how European Union Politics has evolved over the last 25 years. Our analysis demonstrates that the goals the editorial team has pursued over this quarter century have only partly been reached. While the journal has helped to consolidate EU studies as a field of research in its own rights, several problems of representation persist in the journal and the social sciences in general. We identify besides the well-known gender gap that especially authors from the (European) South and East continue to be underrepresented in submitted and published articles. While less represented and successful at the submission stage, our results show that female scholars are more likely than male author teams to publish high-impact articles. Our findings indicate that studies of political behavior, broadly conceived, and articles using quantitative methods are well-represented. The article concludes with some remarks on how the journal might help to further professionalize the study of the EU in the coming years.

Face-to-face interactions between public officials and citizens are a key venue of state service delivery, but they are rarely studied empirically. To address this gap, we present a novel conceptual taxonomy of spoken administrative language. We combine theoretical insights from communication studies and an analysis of 64 exploratory expert interviews with frontline officials. In these interviews, we asked what officials perceive as those aspects of spoken administrative language that affect citizen (dis-)satisfaction with the encounter. The ensuing taxonomy consists of an informational component with two dimensions: comprehensibility (is the language comprehensible?) and reification (is the regulative context explained?); and a relational component with two dimensions: emotionality (does language convey personal commitment to client concerns?) and complaisance (does language impart support and helpfulness?). With its theoretical and empirical insights, the paper contributes a novel conceptualization of administrative language enabling measurement of spoken communication in public service encounters.

The relationship between the state and traditional governance institutions (TGI) in contemporary politics has recently received increased scholarly attention. Traditional leaders play important roles in elections, public goods provision or conflict resolution in Sub-Saharan Africa. We analyse under what conditions cooperation or conflict emerge between the state and TGI. We contribute to the understanding of state-traditional relations by studying how governments interact simultaneously with varying TGI of different ethnic groups. We compare state-TGI relations for eight traditional polities in Kenya, Namibia, Tanzania, and Uganda, based on extensive fieldwork and interviews with state and traditional authorities, experts and constituents. We study three factors shaping state relations with different TGI: (1) the significance of TGI – both social and organisational – in each country and ethnic group; (2) the institutional similarity of TGI and state; and (3) the integration of TGI – both legal and political. Our analysis shows TGI with social significance and functional organisations challenge the state more frequently. Constitutional ambiguity fosters conflict between TGI and state. For our cases, relations are less conflictive in countries with more democratic governments. The same governments and TGI often simultaneously engage in cooperative and conflictive relations, highlighting that governments rarely pursue uniform policies with all TGI.

Political polarization is often understood in terms of extreme issue positions. But polarization can only emerge if issue positions are aligned into a single ideological spectrum, ranging from left/ liberal to right/conservative. It is unclear how a high-dimensional space of policy issues can organize itself into a single ideological spectrum and give rise to polarization. We explain this phenomenon using Weighted Balance Theory (WBT), which describes the interaction of issue positions and interpersonal affect. By implementing WBT into an agent-based opinion dynamics model, we generate a single ideological spectrum from an arbitrarily high dimensional issue space. Furthermore, we show that WBT outperforms other models in predicting respondents’ attitudes in 44 years worth of empirical data from the ANES survey. A calibrated version of our model can reproduce properties of empirically observed opinion distributions.

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dc.contributor.author: Galesic, Mirta; Olsson, Henrik

While survey data has long been the focus of quantitative social science analyses, observational and content data, although long-established, are gaining renewed attention; especially when this type of data is obtained by and for observing digital content and behavior. Today, digital technologies allow social scientists to track “everyday behavior” and to extract opinions from public discussions on online platforms. These new types of digital traces of human behavior, together with computational methods for analyzing them, have opened new avenues for analyzing, understanding, and addressing social science research questions. However, even the most innovative and extensive amounts of data are hollow if they are not of high quality. But what does data quality mean for modern social science data? To investigate this rather abstract question the present study focuses on four objectives. First, we provide researchers with a decision tree to identify appropriate data quality frameworks for a given use case. Second, we determine which data types and quality dimensions are already addressed in the existing frameworks. Third, we identify gaps with respect to different data types and data quality dimensions within the existing frameworks which need to be filled. And fourth, we provide a detailed literature overview for the intrinsic and extrinsic perspectives on data quality. By conducting a systematic literature review based on text mining methods, we identified and reviewed 58 data quality frameworks. In our decision tree, the three categories, namely, data type, the perspective it takes, and its level of granularity, help researchers to find appropriate data quality frameworks. We, furthermore, discovered gaps in the available frameworks with respect to visual and especially linked data and point out in our review that even famous frameworks might miss important aspects. The article ends with a critical discussion of the current state of the literature and potential future research avenues.

Objective: Providing country-level estimates for prevalence rates of Generalized Anxiety Disorder (GAD), COVID-19 exposure and food insecurity (FI) and assessing the role of persistent threats to survival—exemplified by exposure to COVID-19 and FI—for the mental health crisis in Africa.

Methods: Original phone-based survey data from Mozambique, Sierra Leone, Tanzania and Uganda (12 consecutive cross-sections in 2021; n = 23,943) were analyzed to estimate prevalence rates of GAD. Logistic regression models and mediation analysis using structural equation models identify risk and protective factors.

Results: The overall prevalence of GAD in 2021 was 23.3%; 40.2% in Mozambique, 17.0% in Sierra Leone, 18.0% in Tanzania, and 19.1% in Uganda. Both COVID-19 exposure (OR_adj. 1.4; CI 1.3–1.6) and FI (OR_adj 3.2; CI 2.7–3.8) are independent and significant predictors of GAD. Thus, the impact of FI on GAD was considerably stronger than that of COVID-19 exposure.

Conclusion: Persistent threats to survival play a substantial role for mental health, specifically GAD. High anxiety prevalence in the population requires programs to reduce violence and enhance social support. Even during a pandemic, addressing FI as a key driver of GAD should be prioritized by policymakers.

The paper asks for the contribution of growth models for the explanation of public sector employment relations in Germany. The paper is subdivided into three parts. The first elaborates on long-term developments as well as forms of employment. The second part analyzes wage setting systems, that is, bilateral collective bargaining for employees and unilateral decision-making for civil servants. The third part compares the empirical outcomes of both sub-systems with the assumptions of growth models and distinguished explicitly various concepts of the state as corporate actor.

Refugee men are found to be less deserving of government support than refugee women. However, is this still the case if they engage in economic reciprocal behavior and attitudes? Following theories on gender stereotypes and benevolent sexism, we argue that economic activity is expected less of female than of male refugees and that this translates into gendered perceptions of deservingness of financial support. Analyzing data from a 2016 factorial survey experiment in Germany, we show that male refugees are more likely to get “punished” if unwilling to work. Future studies should thus include gender-related aspects when assessing deservingness perceptions.

Suicide-related media content has preventive or harmful effects depending on the specific content. Proactive media screening for suicide prevention is hampered by the scarcity of machine learning approaches to detect specific characteristics in news reports. This study applied machine learning to label large quantities of broadcast (TV and radio) media data according to media recommendations reporting suicide. We manually labeled 2519 English transcripts from 44 broadcast sources in Oregon and Washington, USA, published between April 2019 and March 2020. We conducted a content analysis of media reports regarding content characteristics. We trained a benchmark of machine learning models including a majority classifier, approaches based on word frequency (TF-IDF with a linear SVM) and a deep learning model (BERT). We applied these models to a selection of more simple (e.g., focus on a suicide death), and subsequently to putatively more complex tasks (e.g., determining the main focus of a text from 14 categories). Tf-idf with SVM and BERT were clearly better than the naive majority classifier for all characteristics. In a test dataset not used during model training, F1-scores (i.e., the harmonic mean of precision and recall) ranged from 0.90 for celebrity suicide down to 0.58 for the identification of the main focus of the media item. Model performance depended strongly on the number of training samples available, and much less on assumed difficulty of the classification task. This study demonstrates that machine learning models can achieve very satisfactory results for classifying suicide-related broadcast media content, including multi-class characteristics, as long as enough training samples are available. The developed models enable future large-scale screening and investigations of broadcast media.

Recent approaches to text analysis from social media and other corpora rely on word lists to detect topics, measure meaning, or to select relevant documents. These lists are often generated by applying computational lexicon expansion methods to small, manually curated sets of seed words. Despite the wide use of this approach, we still lack an exhaustive comparative analysis of the performance of lexicon expansion methods and how they can be improved with additional linguistic data. In this work, we present LEXpander, a method for lexicon expansion that leverages novel data on colexification, i.e., semantic networks connecting words with multiple meanings according to shared senses. We evaluate LEXpander in a benchmark including widely used methods for lexicon expansion based on word embedding models and synonym networks. We find that LEXpander outperforms existing approaches in terms of both precision and the trade-off between precision and recall of generated word lists in a variety of tests. Our benchmark includes several linguistic categories, as words relating to the financial area or to the concept of friendship, and sentiment variables in English and German. We also show that the expanded word lists constitute a high-performing text analysis method in application cases to various English corpora. This way, LEXpander poses a systematic automated solution to expand short lists of words into exhaustive and accurate word lists that can closely approximate word lists generated by experts in psychology and linguistics.

Does technological change fuel political disruption? Drawing on fine-grained labor market data from Germany, this paper examines how technological change affects regional electorates. We first show that the well-known decline in manufacturing and routine jobs in regions with higher robot adoption or investment in information and communication technology (ICT) was more than compensated by parallel employment growth in the service sector and cognitive non-routine occupations. This change in the regional composition of the workforce has important political implications: Workers trained for these new sectors typically hold progressive political values and support progressive pro-system parties. Overall, this composition effect dominates the politically perilous direct effect of automation-induced substitution. As a result, technology-adopting regions are unlikely to turn into populist-authoritarian strongholds.

To what extent, and under what conditions, have workfare reforms shaped public opinion towards the unemployed? This article unpacks the punitive and enabling dimensions of the workfare turn and examines how changes to the rights and obligations of the unemployed have influenced related policy preferences. To do so, it presents a novel dataset on these reforms across a diverse set of welfare states and investigates potential feedback effects by combining our data with four waves of survey data from Europe and North America. Results suggest that while enabling measures generate more lenient attitudes towards the unemployed, punitive measures have no clear effect on public opinion – but they do accentuate the gap between the preferences of high- and low-income individuals. This leads us to conclude that the trend towards punitive and enabling measures since the 1980s has not broadly undermined solidarity with the unemployed, though it has increased income-based polarization.

This article introduces a theoretical model of truth and honesty from a psychological perspective. We examine its application in political discourse and discuss empirical findings distinguishing between conceptions of honesty and their influence on public perception, misinformation dissemination, and the integrity of democracy.