Suchergebnisse

The empirical social sciences largely rely on the collection and analysis of research data. In recent years, several recommendations on the more open sharing of research data have been published. These recommendations aim at making science more transparent and replicable. In reality, however, many important research datasets are still not accessible. The project investigates how different factors influence the data sharing behavior of the authors of research papers in sociology and political sciences. It starts with an analysis of journal attributes and the articles published by selected journals to show how authors deal with their data. Second, a survey among the authors is conducted based on the Theory of Planned Behavior. This shows how personal characteristics are related to authors' data sharing behavior.

A newer version of this dataset is available at https://doi.org/10.7802/2284

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The empirical social sciences largely rely on the collection and analysis of research data. In recent years, several recommendations on the more open sharing of research data have been published. These recommendations aim at making science more transparent and replicable. In reality, however, many important research datasets are still not accessible. The project investigates how different factors influence the data sharing behavior of the authors of research papers in sociology and political sciences. It starts with an analysis of journal attributes and the articles published by selected journals to show how authors deal with their data. Second, a survey among the authors is conducted based on the Theory of Planned Behavior. This shows how personal characteristics are related to authors' data sharing behavior.

The quality of methodology sections is the result of interaction between academic cultures of data sharing, effective application of rules, academic excellence and good quality Research Data Management (RDM).This data set is based on the coding of 66 published empirical articles that used data from at least one wave of the European Values Survey (http://dx.doi.org/10.4232/1.11005) and was published at least in pre-print form between 1984 and 2013. It tests for an article describing the methodology of data collection.

Replication in International Relations / Nils Petter Gleditsch, Nicole Janz 361-366. - Preplication, Replication: A Proposal to Efficiently Upgrade Journal Replication Standards / Michael Colaresi 367-378. - Data Policies, Data Management, and the Quality of Academic Writing / Alexia Katsanidou, Laurence Horton, Uwe Jensen 379-391. - Bringing the Gold Standard into the Classroom: Replication in University Teaching You have access / Nicole Janz 392-407. - Replication and the Manufacture of Scientific Inferences: A Formal Approach / Fernando Martel García 408-425. - Grounded Theory Generation: A Tool for Transparent Concept Development / Todd N. Tucker 426-438. - Replication: Why, Where, and How? A Synopsis / Nils B. Weidmann 439-444

English:

The governments' mitigation measures to fight the COVID-19 pandemic are unprecedented in our post-war history. For overcoming this crisis, citizens are expected to act in solidarity in order to control the spread of the virus and keep public health systems functional. At the same time, they are called to cope with confinement, limitations of their freedom (movement, religion etc.) and economic activity. SAFE-19 provides a social sciences perspective on the concept of solidarity which has become a central claim for the fight against COVID-19.



What are the sources and the scope of solidarity when society as a whole is faced with nearly impossible trade-offs? and What are the conditions that enable a political community to act in solidarity and support solidary measures within the nation state and within the EU? Using different trade-offs, the project examines how societal solidarity is addressed, reflected and socially perceived in the different phases of the crisis. The closure of large parts of the retail trade and gastronomy, perceived as a "lock-down", play just as important a role as compliance with the obligation to wear a mask and different attitudes towards vacation trips and their possible follow-up costs.





Deutsch:

Die von der Regierung ergriffenen Maßnahmen im Kampf gegen die COVID-19-Pandemie sind beispiellos in der Geschichte der Bundesrepublik. Um die Kapazitäten des öffentlichen Gesundheitswesens nicht überzustrapazieren und um die Verbreitung des Virus zu kontrollieren, wird von den Bürger_innen solidarisches Handeln erwartet. Gleichzeitig sind sie dazu angehalten, Einschränkungen ihrer Freiheiten, besonders ihrer Bewegungsfreiheit, sowie wirtschaftliche Härten zu akzeptieren. SAFE-19 blickt aus sozialwissenschaftlicher Perspektive auf das Konzept der Solidarität, welches im Kontext dieser außergewöhnlichen Situation eine zentrale Rolle spielt.



Was sind die Grundlagen und das Ausmaß der Solidarität, wenn die Gesellschaft als Ganzes mit der Abwägung zwischen gleichermaßen folgeschweren Alternativen konfrontiert wird? Welche Umstände ermöglichen es einer politischen Gemeinschaft, in Solidarität zu handeln und Solidaritätsmaßnahmen im eigenen Land und innerhalb der EU zu unterstützen? Anhand unterschiedlicher Güterabwägungen (Trade-offs) untersucht das Projekt, wie gesellschaftliche Solidarität in den unterschiedlichen Phasen der Krise adressiert, reflektiert und gesellschaftlich perzipiert wird. Die als "Lock-down" empfundene Schließung von großen Teilen des Einzelhandels und der Gastronomie spielen dabei ebenso eine Rolle wie die Befolgung der Maskentragepflicht und unterschiedlicher Einstellungen zu Urlaubsreisen und deren eventuellen Folgekosten.

Societal transformations are necessary to address critical global challenges, such as mitigation of anthropogenic climate change and reaching UN sustainable development goals. Recently, social tipping processes have received increased attention, as they present a form of social change whereby a small change can shift a sensitive social system into a qualitatively different state due to strongly self-amplifying (mathematically positive) feedback mechanisms. Social tipping processes with respect to technological and energy systems, political mobilization, financial markets and sociocultural norms and behaviors have been suggested as potential key drivers towards climate action. Drawing from expert insights and comprehensive literature review, we develop a framework to identify and characterize social tipping processes critical to facilitating rapid social transformations. We find that social tipping processes are distinguishable from those of already more widely studied climate and ecological tipping dynamics. In particular, we identify human agency, social-institutional network structures, different spatial and temporal scales and increased complexity as key distinctive features underlying social tipping processes. Building on these characteristics, we propose a formal definition for social tipping processes and filtering criteria for those processes that could be decisive for future trajectories towards climate action. We illustrate this definition with the European political system as an example of potential social tipping processes, highlighting the prospective role of the FridaysForFuture movement. Accordingly, this conceptual framework for social tipping processes can be utilized to illuminate mechanisms for necessary transformative climate change mitigation policies and actions.

Balancing speed and quality during crises pose challenges for ensuring the value and utility of data in social science research. The COVID-19 pandemic in particular underscores the need for high-quality data and rapid dissemination. Given the importance of behavioral measures and compliance with measures to contain the pandemic, social science research has played a key role for policymaking during this global crisis.

This study addresses two key research questions: How FAIR (findable, accessible, interoperable, and reusable) are social science data on the COVID-19 pandemic? Which study features are related to the level of FAIRness scores of datasets? We assess the FAIRness of n=1,131 articles, retrieved through a keyword search in the Web of Science database, employing both automated and manual coding methods. Our study inclusion criteria encompass empirical studies on the COVID-19 pandemic published between 2019-2023 with a social science focus and explicit reference to the underlying dataset(s). Our analysis of n=45 datasets reveals substantial differences in FAIRness for different types of research on the COVID-19 pandemic. The overall FAIRness of data is acceptable, although particularly Reusability scores fall short, in both the manual and the automatic assessment. Further, articles explicitly linked to the Social Science concept in the OpenAlex database exhibit a higher mean overall FAIRness value. Based on these results, we derive recommendations for balancing ethical obligations and the potential tradeoff between speed and data (sharing) quality in social-scientific crisis research.

The replication data contains the manual and automatic coded values for FAIR criteria and the complete code to re-produce the results for the article.

Die vom Bundesministerium für Bildung und Forschung geförderte Studie wird gemeinsam von GESIS - Leibniz-Institut für Sozialwissenschaften, der Universität Heidelberg und dem Wissenschaftszentrum Berlin für Sozialforschung im Rahmen des Projekts Solikris durchgeführt. Solikris untersucht die Auswirkungen von Krisen auf die Solidaritätsdynamik in Gesellschaft und Politik. Zu diesem Zweck werden Daten zu alltäglichen, sozialen und politischen Themen in Deutschland und Europa im Jahr 2020 erhoben. Der Fokus liegt dabei vor allem auf den Auswirkungen der COVID-19-Pandemie auf die Meinungen und Gefühle der befragten Bürgerinnen und Bürger zum Alltag und zur politischen Situation in ihren jeweiligen Ländern.