Epistemic communities like the Intergovernmental Panel on Climate Change (IPCC) are international knowledge-based expert networks with a policy advice mandate. Beside their achievements, epistemic communities are often criticized for biased findings and group think. In this context, it would be important to know how epistemic communities recruit new expert members in the first place -- by merit and academic excellence or rather by liking, visibility, or personal networks. The project analyzes survey data about such recruitment processes in the Millennium Ecosystem Assessment (MA), an epistemic community with 1360 experts from 95 countries. One of the project members collected survey data on whom the experts nominated as new members and by whom they were nominated. Up to now, this dataset has not been analyzed systematically because statistical network analysis methods for networks with missing data were only invented more recently. We posit that membership nominations follow a self-reinforcing networking and homophily logicspan.
