NormTransform - Erfassung der sozialen Kippdynamik von Werbung, die klimarelevante Normen und Werte formt und spiegelt

The per capita meat consumption in Austria is decreasing, it is far above the EU average. At the same time, Austria aims to be climate neutral by 2040, thus a decade before the EU-wide target. Despite decreasing emissions in the agricultural sector in Austria, agri-food systems are transforming far too slowly to support the EU’s progress towards climate neutrality. Consequentially, measures that help to trigger a far-reaching change in agri-food systems in the upcoming years are needed. As a response, our project proposes research on an intervention that can (i) jointly address the supply- and demand side and (ii) be quickly implemented to accelerate transformation processes toward carbon neutrality. We, thus, first used the social tipping points (STP) as a theoretical framework to identify its most relevant elements for the agri-food system transformation. We recognized norm- and value systems as suitable, given that (a) eating meat is culturally strongly embedded in Austria, and ( c) diets as a habitual behavior that does not easily change even if intentions do. To transform norms, STP proposes interventions to foster the recognition of the immorality of fossil fuels or even the overall emission of greenhouse gases. Recent findings show the visibility or invisibility of climate change in media influences the advocacy for or against fossil fuel exploitation. Our project thus proposes investigating advertisements as an intervention to transform norms based on (i) their visibility in media, (ii) their recent use as a proxy for norms, (iii) their function to induce a (consumption) behavior, (iv). They are quick to implement and stand at the interface of demand and supply. We study the social tipping dynamics of advertisements, norms, and behaviors to foster climate neutrality in agri-food systems using a complementary methodological approach consisting of quantitative experiments, agent-based models, and warm data labs, a transdisciplinary conversation practice.