Research on racism at the University of Bayreuth is firmly anchored, not least through its Cluster of Excellence "Africa Multiple", so the participation of the University of Bayreuth in WinRa is a gain for the entire network. The aim is to investigate the causes and modes of operation of right-wing extremism and racism from a systematic and historical perspective. With the research results and the recommendations for action generated from them, a basis is to be created to counter right-wing extremism and racism appropriately.
Four regional networks are to be established within WinRa: at the University of Bielefeld and the Leuphana University of Lüneburg (Network West), the University of Mannheim and the University of Bayreuth (Network South), the Magdeburg-Stendal University of Applied Sciences and the Humboldt University of Berlin (Network East) as well as the Bucerius Law School in Hamburg and the University of Hamburg (Network North).
"We want to strengthen research on racism in Germany, network it and make it more visible," says Prof. Dr Stefan Ouma, Professor of Economic Geography at the University of Bayreuth, cluster member and co-spokesperson of the WinRa Regional Network South. This also includes intensifying cooperation between research institutions in the field and involving civil society actors, as well as taking into account the expertise of affected communities. The researchers in WinRa have found that there are hardly any research and teaching structures in the field. WinRa aims to identify research gaps and initiate a stronger institutionalisation of racism research. "I am pleased that the network is also dedicated to the topic of statistics and quantitative racism research, especially in the field of economics," says Prof. Dr. Stefan Ouma, "because unfortunately there is still far too little research on this, especially in Germany." The WinRa Regional Network South of the Universities of Bayreuth and Mannheim is primarily committed to bringing together research that wants to make experiences of racism quantitatively visible and understandable.
