2026-04-30T00:11:38Z https://datacatalogue.cessda.eu/oai-pmh/v0/oai

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DDI study level documentation for study 10.7802/2627 Discursive strategies of political parties in German federalism during Covid-19 Discursive strategies of political parties in German federalism during Covid-19 Discursive strategies of political parties in German federalism during Covid-19 10.7802/262710.7802/262710.7802/262710.7802/2627 Kropp, Sabine Kropp, Sabine Souris, Antonios Souris, Antonios Nguyen, Christoph Nguyen, Christoph [VolkswagenStiftung] GESIS Data Archive for the Social SciencesGESIS Datenarchiv für Sozialwissenschaften politische StrategienParlamentsdebattenCovid-19LandtageBundestagfederalismcontent analysisparty systemmulti-level systemcrisis communicationpolitical behaviorpolitische StrategienParlamentsdebattenCovid-19LandtageBundestagfederalismcontent analysisparty systemmulti-level systemcrisis communicationpolitical behavior The data were collected in the research project "Political cohesion under conditions of fiscal scarcity - German federalism in the time of COVID-19" (funded by VolkswagenStiftung). The data collection consists of two datasets. The first dataset, labeled as "CovDebate", encompasses a total of 3,117 parliamentary proceedings related to Covid-19 that were debated in the German Bundestag and the 16 state parliaments between 1 February 2020 and 26 September 2021. The dataset includes the titles of the proceedings and contextual variables that facilitate a detailed analysis. The second dataset, labeled as "CovFed", comprises 4,610 manually coded statements of political parties that were identified in a qualitative content analysis of 212 key parliamentary debates in the same investigation period. The statements reflect different discursive strategies parties employ in the federal arena. The dataset covers all parties represented in the Bundestag as well as the "Freie Wähler"; all parliaments at both levels of government (Bundestag and 16 state parliaments); and three Covid-19-waves. It contains the statements as well as contextual variables, enabling a detailed analysis of the data. The new dataset is a novel and unique contribution to federalism scholarship because it provides insights into political behavior in the federal arena. It also contains analytical categories which are relevant beyond the German case and in political contexts other than Covid-19.The data were collected in the research project "Political cohesion under conditions of fiscal scarcity - German federalism in the time of COVID-19" (funded by VolkswagenStiftung). The data collection consists of two datasets. The first dataset, labeled as "CovDebate", encompasses a total of 3,117 parliamentary proceedings related to Covid-19 that were debated in the German Bundestag and the 16 state parliaments between 1 February 2020 and 26 September 2021. The dataset includes the titles of the proceedings and contextual variables that facilitate a detailed analysis. The second dataset, labeled as "CovFed", comprises 4,610 manually coded statements of political parties that were identified in a qualitative content analysis of 212 key parliamentary debates in the same investigation period. The statements reflect different discursive strategies parties employ in the federal arena. The dataset covers all parties represented in the Bundestag as well as the "Freie Wähler"; all parliaments at both levels of government (Bundestag and 16 state parliaments); and three Covid-19-waves. It contains the statements as well as contextual variables, enabling a detailed analysis of the data. The new dataset is a novel and unique contribution to federalism scholarship because it provides insights into political behavior in the federal arena. It also contains analytical categories which are relevant beyond the German case and in political contexts other than Covid-19. GermanyGermany Content AnalysisContent Analysis Free access (without registration) - The research data can be downloaded directly by anyone without further limitations.Freier Zugang (ohne Registrierung) - Die Forschungsdaten können von jedem direkt heruntergeladen werden. http://dbkapps.gesis.org/dbkoai/oai.asp oai:dbk.gesis.org:SDN/10.7802_2627 2023-10-25 ddi:codebook:2_5