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Faced with an accelerating climate crisis caused by burning fossil fuels we have to change the way the economy works. We can no longer go on with a system that just maximises private profit without consideration for its effects. Instead we have to conciously plan how to change to a fossil fuel free society.
The need is urgent.
The transformation will be vast.
Nothing similar has been done in the West since the days of wartime mobilisation.
This book explains the basic science of climate change before looking at the transformations needed to our energy and basic industries. It looks at the previous successful history of deliberate planning practiced in the UK from 1939 to the 1960s and how, using modern computing techniques it will be possible to organise resources so as to effect the change.
Einleitung
(2022)
Ausblick
(2022)
Is Vienna still a just city?
(2022)
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.
“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.
Die Transformation der öffentlichen Verantwortung im Bereich der sozialen Wohlfahrt führte in den letzten Jahren zu einem gestiegenen Forschungsinteresse an Mitarbeiten-den, die sich an der Schnittstelle zwischen öffentlicher Verwaltung und direktem Kontakt zu Klient*innen befinden. Die vorliegende Arbeit geht am Beispiel der Schulsozialarbeit an Potsdamer Grundschulen der Frage nach, inwieweit Vertrauen in Klient*innen die Nutzung von Ermessensspielräumen durch Schulsozialarbeiter*innen beeinflusst. Das Street-Level Bureaucracy Framework nach Michael Lipsky spannt dabei den theoretischen Rahmen, während qualitative Interviews mit Schulsozialarbei-ter*innen die Basis für die Beantwortung der Forschungsfrage darstellen. Die Ergebnis-se zeigen, dass ein geringeres Maß an Vertrauen in Klient*innen dafür sorgt, dass Schulsozialarbeiter*innen durch Bewältigungsstrategien wie der Rationierung von Res-sourcen und dem gedanklichen Rückzug von Klient*innen versuchen, ihre Arbeitslast zu verringern. Ein höheres Maß an Vertrauen in Klient*innen sorgt hingegen dafür, dass sie ihre Ermessensspielräume zu Gunsten dieser Klient*innen nutzen, zum Beispiel durch das Umgehen von Datenschutzregeln zur effektiveren Fallbearbeitung.
“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.
Is There a Rural Penalty in Language Acquisition? Evidence From Germany's Refugee Allocation Policy
(2022)
Emerging evidence has highlighted the important role of local contexts for integration trajectories of asylum seekers and refugees. Germany's policy of randomly allocating asylum seekers across Germany may advantage some and disadvantage others in terms of opportunities for equal participation in society. This study explores the question whether asylum seekers that have been allocated to rural areas experience disadvantages in terms of language acquisition compared to those allocated to urban areas. We derive testable assumptions using a Directed Acyclic Graph (DAG) which are then tested using large-N survey data (IAB-BAMF-SOEP refugee survey). We find that living in a rural area has no negative total effect on language skills. Further the findings suggest that the “null effect” is the result of two processes which offset each other: while asylum seekers in rural areas have slightly lower access for formal, federally organized language courses, they have more regular exposure to German speakers.
Is There a Rural Penalty in Language Acquisition? Evidence From Germany's Refugee Allocation Policy
(2022)
Emerging evidence has highlighted the important role of local contexts for integration trajectories of asylum seekers and refugees. Germany's policy of randomly allocating asylum seekers across Germany may advantage some and disadvantage others in terms of opportunities for equal participation in society. This study explores the question whether asylum seekers that have been allocated to rural areas experience disadvantages in terms of language acquisition compared to those allocated to urban areas. We derive testable assumptions using a Directed Acyclic Graph (DAG) which are then tested using large-N survey data (IAB-BAMF-SOEP refugee survey). We find that living in a rural area has no negative total effect on language skills. Further the findings suggest that the “null effect” is the result of two processes which offset each other: while asylum seekers in rural areas have slightly lower access for formal, federally organized language courses, they have more regular exposure to German speakers.
In countries with long-standing agency traditions, the creation of new agencies rarely comes as a large-scale reform but rather as one structural choice of many possible, most notably a ministerial division. In order to make sense of these choices, the article discusses the role of political design-focusing on the role of political motivations, such as ideological turnover, replacement risks and ideological stands toward administrative efficiency-and organizational dynamics-focusing on the role of administrative legacies and existing organizational palettes. The article utilizes data on organizational creations in the Norwegian central state between 1947 and 2019, in order to explore how political design and organizational dynamics help us understand the creation of agencies relative to ministry divisions over time. We find that political motives matter a great deal for the structural choices made by consecutive Norwegian governments, but that structural path dependencies may also be at play.
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.
To meet the Paris Agreement targets, carbon emissions from the energy system must be eliminated by mid-century, implying vast investment and systemic change challenges ahead. In an article in WIREs Climate Change, we reviewed the empirical evidence for effects of carbon pricing systems on technological change towards full decarbonisation, finding weak or no effects. In response, van den Bergh and Savin (2021) criticised our review in an article in this journal, claiming that it is "unfair", incomplete and flawed in various ways. Here, we respond to this critique by elaborating on the conceptual roots of our argumentation based on the importance of short-term emission reductions and longer-term technological change, and by expanding the review. This verifies our original findings: existing carbon pricing schemes have sometimes reduced emissions, mainly through switching to lower-carbon fossil fuels and efficiency increases, and have triggered weak innovation increases. There is no evidence that carbon pricing systems have triggered zero-carbon investments, and scarce but consistent evidence that they have not. Our findings highlight the importance of adapting and improving climate policy assessment metrics beyond short-term emissions by also assessing the quality of emission reductions and the progress of underlying technological change.
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.
Typen von Forschungsdesigns
(2022)
Sozialwissenschaftliche Forschungsdesigns umfassen alle wesentlichen Entscheidungen, die im Forschungsprozess getroffen werden müssen. Der Beitrag unterscheidet drei rundlegende Typen von Forschungsdesigns: x-zentriert, y-zentriert und kontrastiv. Das x-zentrierte Design versucht einen theoretisch spezifizierten kausalen Effekt zu identifizieren und dessen Größe möglichst genau und ohne Verzerrungen zu schätzen. Das y-zentrierte Design versucht mehrere komplementäre Theorien über kausale Effekte so zu kombinieren, dass bestimmte Phänomene möglichst gut erklärt werden. Das kontrastive Design vergleicht die Erklärungskraft von zwei oder mehr konkurrierenden Theorien. Die Unterscheidung der drei Typen ist für qualitative Fallstudien ebenso relevant wie für Experimente oder statistische Studien mit Beobachtungsdaten. Der Beitrag grenzt die drei Typen voneinander ab, erklärt ihre jeweiligen Annahmen und diskutiert ihre Vor- und Nachteile sowie die Möglichkeiten und Grenzen ihrer Kombination. Daneben diskutiert er den Unterschied zwischen Modellen und Theorien sowie die Bedeutung des Sparsamkeitsprinzips bei der Entwicklung und Bewertung wissenschaftlicher Theorien und Erklärungen.
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.
Real options are widely applied in strategic and operational decision-making, allowing for managerial flexibility in uncertain contexts. Increased scholarly interest has led to an extensive but fragmented research landscape. We aim to measure and systematize the research field quantitatively. To achieve this goal, we conduct bibliometric performance analyses and bibliographic coupling analyses with an in-depth content review. The results of the performance analyses show an increasing interest in real options since the beginning of the 2000s and identity the most influential journals and authors. The science mappings reveal six and seven research clusters over the last two decades. Based on an in-depth analysis of their themes, we develop a research framework comprising antecedents, application areas, internal and external contingencies, and uncertainty resolution through real option valuation or reasoning. We identify several gaps in that framework, which we propose to tackle in future research.