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In this article, we examine the effects of political change on name changes of units within central government ministries. We expect that changes regarding the policy position of a government will cause changes in the names of ministerial units. To this end we formulate hypotheses combining the politics of structural choice and theories of portfolio allocation to examine the effects of political changes at the cabinet level on the names of intra-ministerial units. We constructed a dataset containing more than 17,000 observations on name changes of ministerial units between 1980 and 2013 from the central governments of Germany, the Netherlands, and France. We regress a series of generalized estimating equations (GEE) with population averaging models for binary outcomes. Finding variations across the three political-bureaucratic systems, we overall report positive effects of governmental change and ideological positions on name changes within ministries.
Voting for Votes
(2022)
Scholars frequently expect parties to act strategically in parliament, hoping to affect their electoral fortunes. Voters assumingly assess parties by their activity and vote accordingly. However, the retrospective voting literature looks mostly at the government's outcomes, leaving the opposition understudied. We argue that, for opposition parties, legislative voting constitutes an effective vote-seeking activity as a signaling tool of their attitude toward the government. We suggest that conflictual voting behavior affects voters through two mechanisms: as a signal of opposition valence and as means of ideological differentiation from the government. We present both aggregate- and individual-level analyses, leveraging a dataset of 169 party observations from 10 democracies and linking it to the CSES survey data of 27,371 respondents. The findings provide support for the existence of both mechanisms. Parliamentary conflict on legislative votes has a general positive effect on opposition parties' electoral performance, conditional on systemic and party-specific factors.
The demand for learning Design Thinking (DT) as a path towards acquiring 21st-century skills has increased globally in the last decade. Because DT education originated in the Silicon Valley context of the d.school at Stanford, it is important to evaluate how the teaching of the methodology adapts to different cultural contexts.The thesis explores the impact of the socio-cultural context on DT education.
DT institutes in Cape Town, South Africa and Kuala Lumpur, Malaysia, were visited to observe their programs and conduct 22 semistructured interviews with local educators regarding their adaption strategies. Grounded theory methodology was used to develop a model of Socio-Cultural Adaptation of Design Thinking Education that maps these strategies onto five dimensions: Planning, Process, People, Place, and Presentation. Based on this model, a list of recommendations is provided to help DT educators and practitioners in designing and delivering culturally inclusive DT education.
Global Legitimacy Crises
(2022)
Global Legitimacy Crises addresses the consequences of legitimacy in global governance, in particular asking: when and how do legitimacy crises affect international organizations and their capacity to rule. The book starts with a new conceptualization of legitimacy crisis that looks at public challenges from a variety of actors. Based on this conceptualization, it applies a mixed-methods approach to identify and examine legitimacy crises, starting with a quantitative analysis of mass media data on challenges of a sample of 32 IOs. It shows that some, but not all organizations have experienced legitimacy crises, spread over several decades from 1985 to 2020. Following this, the book presents a qualitative study to further examine legitimacy crises of two selected case studies: the WTO and the UNFCCC. Whereas earlier research assumed that legitimacy crises have negative consequences, the book introduces a theoretical framework that privileges the activation inherent in a legitimacy crisis. It holds that this activation may not only harm an IO, but could also strengthen it, in terms of its material, institutional, and decision-making capacity. The following statistical analysis shows that whether a crisis has predominantly negative or positive effects depends on a variety of factors. These include the specific audience whose challenges define a certain crisis, and several institutional properties of the targeted organization. The ensuing in-depth analysis of the WTO and the UNFCCC further reveals how legitimacy crises and both positive and negative consequences are interlinked, and that effects of crises are sometimes even visible beyond the organizational borders.
“Broadcast your gender.”
(2022)
Social media platforms provide a large array of behavioral data relevant to social scientific research. However, key information such as sociodemographic characteristics of agents are often missing. This paper aims to compare four methods of classifying social attributes from text. Specifically, we are interested in estimating the gender of German social media creators. By using the example of a random sample of 200 YouTube channels, we compare several classification methods, namely (1) a survey among university staff, (2) a name dictionary method with the World Gender Name Dictionary as a reference list, (3) an algorithmic approach using the website gender-api.com, and (4) a Multinomial Naïve Bayes (MNB) machine learning technique. These different methods identify gender attributes based on YouTube channel names and descriptions in German but are adaptable to other languages. Our contribution will evaluate the share of identifiable channels, accuracy and meaningfulness of classification, as well as limits and benefits of each approach. We aim to address methodological challenges connected to classifying gender attributes for YouTube channels as well as related to reinforcing stereotypes and ethical implications.
“Broadcast your gender.”
(2022)
Social media platforms provide a large array of behavioral data relevant to social scientific research. However, key information such as sociodemographic characteristics of agents are often missing. This paper aims to compare four methods of classifying social attributes from text. Specifically, we are interested in estimating the gender of German social media creators. By using the example of a random sample of 200 YouTube channels, we compare several classification methods, namely (1) a survey among university staff, (2) a name dictionary method with the World Gender Name Dictionary as a reference list, (3) an algorithmic approach using the website gender-api.com, and (4) a Multinomial Naïve Bayes (MNB) machine learning technique. These different methods identify gender attributes based on YouTube channel names and descriptions in German but are adaptable to other languages. Our contribution will evaluate the share of identifiable channels, accuracy and meaningfulness of classification, as well as limits and benefits of each approach. We aim to address methodological challenges connected to classifying gender attributes for YouTube channels as well as related to reinforcing stereotypes and ethical implications.
Research on multi-level implementation of EU legislation has almost exclusively focused on the national level, while little is known about the role of subnational authorities. Nevertheless, it is a prerequisite for the functioning of the European Union that all member states and their subnational authorities apply and enforce EU legislation in due time. I address this research gap and take a closer look at the legal transposition process in the German regional states. Using a novel data set comprising detailed information on about 700 subnational measures, I show that state-level variables, such as political preferences and ministerial resources, account for variation in the timing of legal transposition and repeatedly lead to subnational delay. To conclude, the paper addresses the role of subnational authorities in the EU multi-level system and points to their interest in shaping legal transposition in order to counterbalance their loss of competences to the national level.
Zunehmend komplexe Herausforderungen und Aufgaben lassen sich nicht mehr mit den bisherigen Strukturen, Methoden und Prozessen der klassischen Verwaltung bewältigen. Vielmehr gewinnen Ansätze und Methoden des New Work im öffentlichen Sektor angesichts der sich stetig ändernden und dynamischen Arbeitswelt eine immer größere Bedeutung. Umso mehr besteht die Notwendigkeit, sich in der Verwaltung agil aufzustellen. Unter Agilität wird hierbei die Fähigkeit einer Organisation verstanden, sich schnell verändernden Rahmenbedingungen flexibel und dynamisch anzupassen.
Im Fokus dieser Arbeit steht der Einfluss von Agilität auf die Führungskräfte-Mitarbeiter-Beziehung. Mittels einer halbstandardisierten Online-Befragung im Landesamt für Flüchtlingsangelegenheiten und im Bezirksamt Neukölln von Berlin wird zunächst der vorliegende Agilitätsgrad mit dem Fokus auf agile Organisationsstrukturen, agile Organisationskultur und agile Führung ermittelt und sodann anhand der Qualität der dyadischen Arbeitsbeziehung von Führungskraft und Mitarbeiter (LMX-Qualität) überprüft, inwiefern die agile Arbeitsweise im Vergleich zu einer nicht-agilen Arbeitsumgebung die Beziehung beeinflusst.
Im Ergebnis der Untersuchung zeigt sich, dass ein positiver Zusammenhang zwischen Agilität und der Führungskräfte-Mitarbeiter-Beziehung besteht. Es stellt sich in beiden Ämtern ein mäßig bis starker Agilitätsgrad heraus, wobei besonders agile Führungseigenschaften zu den wesentlichen Faktoren zählen, die eine hochqualitative Beziehung begünstigen. Während im Bezirksamt ein Zusammenhang zwischen Agilität und hoher LMX-Qualität ermittelt wurde, konnte dieser nicht für die untersuchte Stichprobe des Landesamts festgestellt werden. Dennoch ließ sich in beiden Behörden ein positiver Einfluss von Agilität auf zumindest die Entwicklung einer erfolgreichen Führungskräfte-Mitarbeiter-Beziehung erfassen.
Can we rely on computational methods to accurately analyze complex texts? To answer this question, we compared different dictionary and scaling methods used in predicting the sentiment of German literature reviews to the "gold standard " of human-coded sentiments. Literature reviews constitute a challenging text corpus for computational analysis as they not only contain different text levels-for example, a summary of the work and the reviewer's appraisal-but are also characterized by subtle and ambiguous language elements. To take the nuanced sentiments of literature reviews into account, we worked with a metric rather than a dichotomous scale for sentiment analysis. The results of our analyses show that the predicted sentiments of prefabricated dictionaries, which are computationally efficient and require minimal adaption, have a low to medium correlation with the human-coded sentiments (r between 0.32 and 0.39). The accuracy of self-created dictionaries using word embeddings (both pre-trained and self-trained) was considerably lower (r between 0.10 and 0.28). Given the high coding intensity and contingency on seed selection as well as the degree of data pre-processing of word embeddings that we found with our data, we would not recommend them for complex texts without further adaptation. While fully automated approaches appear not to work in accurately predicting text sentiments with complex texts such as ours, we found relatively high correlations with a semiautomated approach (r of around 0.6)-which, however, requires intensive human coding efforts for the training dataset. In addition to illustrating the benefits and limits of computational approaches in analyzing complex text corpora and the potential of metric rather than binary scales of text sentiment, we also provide a practical guide for researchers to select an appropriate method and degree of pre-processing when working with complex texts.