The European Consortium for Political Research (ECPR) Standing Group on Extremism & Democracy, the Centre for Research on Extremism (C-REX), and the Centre on Social Movement Studies (COSMOS) invite applications for the upcoming Summer School on “Concepts and Methods for Research on Far-Right Politics.” The Summer School is open to 15 Master’s and PhD students of different disciplinary backgrounds in the social and political sciences, as well as early career researchers interested in the study of far-right politics, and will be held at the Scuola Normale Superiore in Florence, Italy, June 25-29, 2018.
Applicants should e-mail a curriculum vitae, a one-page letter explaining how their research fits the scope of the Summer School, and a 500-word abstract of a proposed scientific paper to be presented during the school. Application materials are due by March 11, 2018. Visit the ECPR Standing Group on Extremism & Democracy online call for applications for additional program information.
About the Summer School: The school focuses on the study of the far right in its populist, radical, and extremist manifestations. Its aim is to bolster and promote knowledge on the theoretical, empirical, and methodological underpinnings of contemporary far-right politics. The school will focus on how to study and interpret the different manifestations of far-right politics across time, arenas, and national contexts. The school will also introduce students to concepts and theories explaining the conditions affecting far-right mobilization and performance; and methods to tackle this phenomenon empirically. Despite the growing attention received by far-right political parties, social movements, and groups, we still lack a comprehensive conceptual and methodological toolkit to investigate its diverse expressions in the multi-organizational field. The school will thus address young scholars and students, and discuss how to apply established research techniques to the study of far-right politics, and create, retrieve, and manage available data.
