Tracing Climate Policy Linkages using Text-as-Data: New Perspectives

The workshop will initiate a conversation between two evolving research debates around the expansion of climate politics and governance. First, it will integrate and compare perspectives from various sub-disciplines of political science on climate policy linkages on a conceptual and theoretical level. These include concepts of climate policy integration, mainstreaming, and diffusion (or ‘climatization’) and their application to inter- or transnational, domestic and multi-level governance settings (Aykut et al. 2021, Laurens et al. 2022, Tosun & Lang 2017). The workshop will invite contributions providing innovative perspectives on the merit and applicability of extant concepts in this regard and their embedding in broader theoretical approaches. Second, it will stimulate a cross-disciplinary discussion on quantitative text-analysis methods, their main challenges and most recent innovations. A surge of research has applied text-as-data approaches to explore climate policy linkages, using dictionary-based methods, topic modelling, word-embedding analyses and machine learning methods (Macanovic 2022, Grundmann 2022). These contributions cover fields including party politics and political communication, the inclusion of new policy areas into climate action and green finance, legislative politics and newly emerging inter-departmental and inter-agency links. We welcome papers that cover these thematic fields while addressing challenges for methods of text-as-data analysis, including: construction and validation of dictionaries; combination of inductive and deductive approaches for mapping topics, linkages and tonality; recurrent problems of validity and reliability in large-N text bodies; questions of cultural and cross-case transferability; new approaches to including audiovisual material in surveys; and evaluating the qualitative-quantitative boundary in case studies and small-N comparisons.

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1: How are climate policy linkages created and how can they be detected using text data?
2: How can variants of policy linkages be systematized and compared?
3: How can text-as-data approaches cover aspects of scope and density of climate action targets?
4: How can text-as-data approaches be used to model coalitions, agency and political conflict?
5: How can inductive and deductive approaches to quantitative text analysis be combined?

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