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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.
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.
Die vorliegende Research Note stellt die erste systematische Dokumentation der Gesetzgebung in den deutschen Landtagen vor. Der Datensatz umfasst insgesamt 16.610 dokumentierte Gesetzgebungsvorgänge zwischen den Jahren 1990 und 2020. Nach einer Beschreibung des Datensatzes werden einige Gesetzgebungsmuster in den deutschen Ländern exemplarisch dargestellt. Die Landesgesetzgebung erweist sich dabei als stark durch den neuen Dualismus zwischen Regierung und Opposition geprägt. Im Initiativverhalten lassen sich zudem die Anreize des thematischen Parteienwettbewerbs ablesen. Wenig Evidenz findet sich für die These, dass innerkoalitionäre Gegensätze die Dauer der Gesetzgebungsverfahren in die Länge ziehen. Der mit dieser Research Note veröffentlichte Datensatz steht der Forschung für die Untersuchung zahlreicher weiterer Fragestellungen zur Verfügung.
Sustainable electricity systems need renewable and dispatchable energy sources. Solar energy is an abundant source of renewable energy globally which is, though, by nature only available during the day, and especially in clear weather conditions. We compare three technology configurations able to provide dispatchable solar power at times without sunshine: Photovoltaics (PV) combined with battery (BESS) or thermal energy storage (TES) and concentrating solar power (CSP) with TES. Modeling different periods without sunshine, we find that PV+BESS is competitive for shorter storage durations while CSP+TES gains economic advantages for longer storage periods (also over PV+TES). The corresponding tipping points lie at 2-3 hours (current cost), and 4-10 hours if expectations on future cost developments are taken into consideration. PV+TES becomes only more competitive than CSP+TES with immense additional cost reductions of PV. Hence, there remain distinct niches for two technologies: PV+BESS for short storage durations and CSP+TES for longer ones.
Despite new challenges like climate change and digitalization, global and regional organizations recently went through turbulent times due to a lack of support from several of their member states. Next to this crisis of multilateralism, the COVID-19 pandemic now seems to question the added value of international organizations for addressing global governance issues more specifically. This article analyses this double challenge that several organizations are facing and compares their ways of managing the crisis by looking at their institutional and political context, their governance structure, and their behaviour during the pandemic until June 2020. More specifically, it will explain the different and fragmented responses of the World Health Organization, the European Union and the International Monetary Fund/World Bank. With the aim of understanding the old and new problems that these international organizations are trying to solve, this article argues that the level of autonomy vis-a-vis the member states is crucial for understanding the politics of crisis management. <br /> Points for practitioners <br /> As intergovernmental bodies, international organizations require authorization by their member states. Since they also need funding for their operations, different degrees of autonomy also matter for reacting to emerging challenges, such as the COVID-19 pandemic. The potential for international organizations is limited, though through proactive and bold initiatives, they can seize the opportunity of the crisis and partly overcome institutional and political constraints.
Using a novel agent-based model, we study how US withdrawal might influence the political process established by the Paris Agreement, and hence the prospects for reaching the collective goal to limit warming below 2 degrees C. Our model enables us to analyze to what extent reaching this goal despite US withdrawal would place more stringent requirements on other core elements of the Paris cooperation process. We find, first, that the effect of a US withdrawal depends critically on the extent to which member countries reciprocate others' promises and contributions. Second, while the 2 degrees C goal will likely be reached only under a very small set of conditions in any event, even temporary US withdrawal will further narrow this set significantly. Reaching this goal will then require other countries to step up their ambition at the first opportunity and to comply nearly 100% with their pledges, while maintaining high confidence in the Paris Agreements institutions. Third, although a US withdrawal will first primarily affect the United States' own emissions, it will eventually prove even more detrimental to other countries' emissions.
Dieser Beitrag in der Zeitschrift GIO schlägt eine äquivalenzfunktionalistische Perspektive auf postbürokratische Reformen vor, die Teile der Unsicherheitsabsorption von Organisationen in Interaktionssysteme verlagern. Postbürokratie versucht, organisationale und gesellschaftliche Entwicklungen in der zweiten Hälfte des 20. Jahrhunderts auf den Begriff zu bringen. Auch aktuelle agile Managementkonzepte lassen sich der Postbürokratie zuordnen und zeichnen sich unter anderem durch eine Multiplikation von Interaktionen aus. Mithilfe der Theorie sozialer Systeme untersuchen wir wie neue Unsicherheiten in Organisationen durch postbürokratische Reformen entstehen und von agilen Managementkonzepten bearbeitet werden. An den agilen Konzepten Scrum und Holacracy wird gezeigt, dass diese Verlagerung neuen Formalisierungsbedarf produziert. Im Fokus stehen dabei die Zentrierungen kommunikativer Interdependenzen in Interaktionen in der Sach‑, Zeit- und Sozialdimension. Der Beitrag plädiert für eine äquivalenzfunktionalistische Perspektive auf Postbürokratie, die den Zusammenhang von Formalisierungsverzicht in Organisationen und neuen Formalisierungsbedarfen als funktionalen Leistungszusammenhang begreift.
Organisation und Algorithmus
(2021)
Der vorliegende Beitrag analysiert, wie Organisationen Algorithmen, die wir als digitale Beobachtungsformate verstehen, mit Handlungsfähigkeit ausstatten und damit actionable machen. Das zentrale Argument lautet, dass die soziale Relevanz digitaler Beobachtungsformate sich daraus ergibt, dass und wie sie in organisationale Entscheidungsarchitekturen eingebettet sind. Diesen Zusammenhang illustrieren wir am Beispiel des österreichischen Arbeitsmarktservice (AMS), der 2018 einen Algorithmus einführte, um die Integrationschancen arbeitsuchender Personen zu bewerten. Der AMS steht dabei stellvertretend für aktuelle Bestrebungen vieler Organisationen, algorithmische Systeme einzusetzen, um knappe öffentliche Ressourcen vermeintlich effizienter zu distribuieren. Um zu rekonstruieren, wie dies geschieht, zeigen wir, welche Operationen des Kategorisierens, Vergleichens und Bewertens das algorithmische Modell vollzieht. Darauf aufbauend demonstrieren wir, wie das algorithmische Modell in die organisationale Entscheidungsarchitektur eingebunden ist. Erst durch diese Einbindung – die Möglichkeit, Unterschiede für andere, relativ stabil erzeugte Entscheidungen zu machen – entfaltet das digitale Beobachtungsformat soziale Relevanz. Abschließend argumentieren wir, dass algorithmische Modelle, wie sie am Fall des AMS beobachtet werden können, dazu tendieren, sich in Organisationen zu stabilisieren. Dies begründen wir damit, dass die organisationalen Lernchancen im Umgang mit dem Algorithmus dadurch reduziert sind, dass dieser in einem Bereich zum Einsatz kommt, der durch Technologiedefizit und koproduktive Leistungserstellung geprägt ist.