How technological innovations in meat substitutes feed back in the politics of meat system transformation

Today’s food production and consumption patterns are associated with serious threats to the environment and human health. Especially, the current meat system contributes to manifold sustainability crises. Here, we ask to what extent (policy) narratives and policy actor coalitions regarding meat consumption and production have changed in Germany and the US over the last 10 years. Particularly, we are interested in the role that technological innovations (especially the rise of meat substitutes) played in driving these changes. In a mixed-method comparative study, we test the hypothesis that technological innovations in meat substitutes can lead to new policy narratives that eventually create new actor coalitions and feed back into relevant political processes for transforming the meat system (e.g., adoption of meat taxes). We combine qualitative process-tracing and novel natural language-processing methods with discourse network analysis to test our hypothesis. Empirical analysis of narratives has faced the challenge that the objects under scrutiny consist of extensive collections of unstructured text. Measuring the relevant content of these texts (not to mention using it in a causal analysis) requires the adoption of new tools outside the standard social science kit. We draw upon a number of recently developed natural language processing techniques, namely semantic role labeling and phrase embedding, to extract narratives from text. We apply the narrative embedding pipeline to newspapers in Germany and the US. The resulting longitudinal dataset on the evolution of respective actor networks around policy narratives and instruments can be used to conduct discourse network analyses over time. In conjunction with qualitative process-tracing methods, we then test to what extent the rise of novel technologies (especially meat substitutes) has affected policy narratives and actor coalitions around transformative food policies.