Summary information

Study title

Discursive strategies of political parties in German federalism during Covid-19

Creator

Kropp, Sabine ( Freie Universität Berlin)
Souris, Antonios ( Freie Universität Berlin)
Nguyen, Christoph ( Freie Universität Berlin)

Study number / PID

10.7802/2627 (GESIS)

10.7802/2627 (DOI)

Data access

Information not available

Series

Not available

Abstract

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.

Topics

Not available

Methodology

Data collection period

01/02/2020 - 01/09/2021

Country

Germany

Time dimension

Not available

Analysis unit

Not available

Universe

Sampling procedure

Not available

Kind of data

Not available

Data collection mode

Content Analysis

Access

Publisher

GESIS Data Archive for the Social Sciences

Publication year

2023

Terms of data access

Free access (without registration) - The research data can be downloaded directly by anyone without further limitations.

Related publications

Not available