1,720,974 research outputs found
Risk management against indirect risks from disasters: A multi-model and participatory governance framework applied to flood risk in Austria
Full text linkIndirect effects resulting from natural disasters, such as the follow-on consequences of initial destruction, are attracting growing attention. This is because economic losses in the aftermath of disaster events have escalated in recent years and are expected to continue to rise in the future. Despite this, the primary focus of most countries’ disaster risk management approaches remains centered on mitigating the direct effects of such events, with little attention being paid to strategies aimed explicitly at reducing indirect effects. As a result, there are limited practical solutions available for reducing these indirect damages. Most efforts remain theoretical, lacking real-world testing of frameworks specifically designed to reduce indirect risks. To address this gap, this paper aims to illuminate the issue by proposing and empirically testing how existing risk management frameworks designed for direct risks could be expanded to encompass indirect effects as well. In doing so, we create and use a framework to manage indirect risks in a collaborative process for dealing with major flood risk in Austria. We test specific challenges and explore ways to integrate the management of these indirect risks in a complex real-world scenario. Our findings suggest that linking indirect and direct risk management can be achieved with relatively modest effort. A precise systems definition proves particularly beneficial in this regard, as it can link disaster risk related dimensions with non-disaster related targets. This approach thereby opens up the possibility to explicitly include multiple dividends in the decision-making process about indirect risk management strategie
Economic and labour market impacts of migration in Austria: an agent-based modelling approach
Full text linkThis study examines the potential economic and labour market impacts of a hypothetical but plausible migration scenario of 250,000 new migrants inspired by Austria’s experience in 2015. Using the agent-based macroeconomic model developed by Poledna et al. (Eur Econ Rev, 151:104306, 2023. 10.1016/j.euroecorev.2022.104306, the study explores the detailed labour market outcomes for different groups in Austria’s population and the macroeconomic effects of the migration scenario. The analysis suggests that Austria’s economy and labour market have the potential to be resilient to the simulated migration influx. The results indicate a positive impact on GDP due to increased aggregate consumption and investment. The labour market experiences an increase in the unemployment rates of natives and previous migrants. In some industries, the increase in the unemployment rates is more significant, potentially indicating competition among different groups of migrants. This research provides insights for policymakers and stakeholders in Austria and other countries that may face the challenge of managing large-scale migration in the near future
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Understanding systemic risk in financial networks by methods from statistical mechanics
No full textSystemisches Risiko ist ein allgemeines Merkmal vieler komplexer Systeme. Die Wissenschaft Komplexer Systeme ist ein Forschungsgebiet, das generalisierten Wechselwirkungen zwischen Objekten, die von ihren Zuständen gekennzeichnet sind, untersucht. Typischerweise werden diese generalisierten Wechselwirkungen auf Netzwerkstrukturen vermittelt und führen zu einer extrem reichen Phasenstruktur, die oft komplizierter ist als die von physikalischen Systemen. Systemisches Risiko tritt in einer Vielzahl von natürlichen und vom Menschen geschaffenen komplexen Systemen als Konsequenz dieser Phasenstruktur auf. Es ist das Risiko, dass ein System global ausfällt, seine Funktion nicht mehr ausführen kann und mit möglicherweise dramatischen Folgen für das Gesamtsystem und seine Einzelteile kollabiert. Eines der wichtigsten Beispiele von systemischen Risiko ist heute das der Finanznetzwerke. Das Unvermögen systemisches Risiko zu quantifizieren birgt eine immense Gefahr für die Gesellschaft, und das Versäumnis systemische Risiken zu managen hat sich als äußerst kostspielig erwiesen. Systemisches Risiko hat sich zu einem Schwerpunkt der jüngsten wissenschaftlichen Forschung entwickelt, nicht nur wegen der gesellschaftlichen Bedeutung, sondern auch wegen der hochpräzisen Datenverfügbarkeit und der Tatsache, dass das Finanzsystem vom Menschen geschaffen wurde und im Prinzip verändert und verbessert werden kann. In dieser Arbeit entwickeln wir eine Reihe von praktischen neuen Methoden zur Quantifizierung und schließlich zum Management von systemischem Risiko. Um das Verständnis von systemischem Risiko voranzubringen, untersuchen wir Fortpflanzung, Diffusion und Synchronisationsmechanismen von systemischem Risiko nicht nur in einem einzelnen Finanznetzwerk, sondern auch in einer Überlagerung von Netzwerken, in so genannten Multiplex-Netzwerken. Wir präsentieren eine empirische Studie eines Finanz-Multiplex-Netzwerks, das nach unserer Kenntnis auf dem detailliertesten und umfassendsten Datensatz von einem Finanzmarkt basiert, der aktuell verfügbar ist. Die hier vorgestellten Verfahren sind die ersten objektiven datenbasierenden Quantifizierungsverfahren von systemischem Risiko auf nationaler Ebene. Durch die Untersuchung der zugrunde liegenden Mechanismen der dynamischen Netzwerkbildung in komplexen Finanznetzwerken schlagen wir neue Methoden vor, die Finanzsysteme auf eine selbstorganisierte kritische Weise sicherer machen. Diese Arbeit liefert den ersten praktischen Ansatz für das Management von systemischen Risiken durch Umstrukturierung der Topologie eines Finanznetzwerkes. Wir stützen unsere Untersuchungen sowohl auf hochwertige Daten von Zentralbanken, als auch auf agentenbasierte Modelle, die im Rahmen dieser Arbeit entwickelt wurden.Systemic risk is a general feature of many complex systems. The science of complex systems is a field of research that studies generalized interactions between objects that are characterized by states. Typically, the generalized interactions are mediated on networks and lead to an extremely rich phase structure, which is often more complex than that of physical systems. Systemic risk occurs in a wide variety of natural and human-made complex systems as a consequence of this phase structure. It is the risk that a large part of the system ceases to function, and collapses with potentially dramatic consequences for the system and its parts. One of the most important examples of systemic risk today is that of financial networks. The inability to see and quantify financial systemic risk poses an immense risk to society and failure to manage it has been proven to be extremely costly. It has become a focus of recent academic research, not only because of societal importance, but also for its high-precision data availability, and the situation that the financial system is human-made, and can in principle be changed and engineered to improve it. We develop a number of practical novel methods to quantify and eventually manage systemic risk. To advance the understanding of system risk, we study propagation, diffusion and synchronization mechanisms of systemic risk in not only a single layer of financial networks but on a superposition of networks, a so-called multiplex network. We present an empirical study of a financial multiplex network, which to our knowledge is based on the most detailed and comprehensive financial data currently available. The methods presented here are the first objective data-driven quantifications of systemic risk on national scales that reveal its true levels. By studying the underlying dynamical mechanisms driving the link-formation process in complex financial networks, we propose novel methods that help make financial systems safer in a self-organized critical manner. This work provides the first practical approach for management of systemic risk by re-structuring the topology of financial networks. We base our studies on both high quality data from central banks and agent-based models that were developed during this thesis
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