Partisan Prejudice: Origins, Consequences and Remedies in European Multiparty Democracies

Partisan prejudice exists when citizens hold negative attitudes towards party supporters.

Such prejudice is widespread: many people have stereotypical views of and dislike the supporters of certain parties, sometimes amounting to outright partisan hostility.Partisan prejudice is a challenge for liberal democracy.

It deepens societal rifts, lowers social trust, weakens the acceptance of elite compromise and leads to discrimination and social ostracism. This challenge is urgent at a time of political division and democratic backsliding.

Yet, partisan prejudice is barely studied, particularly in Europe.PARTISAN will provide a novel theoretical framework and rigorous empirical evidence for understanding partisan prejudice, with the ambition of fundamentally altering how voters and parties are studied in multiparty systems.

The theoretical framework posits that objective characteristics of party supporters form the basis of partisan stereotypes, but that these linkages are filtered through individual perceptions and moderated by party- and country-level characteristics.Based on this framework, this project will provide ground-breaking evidence on the prevalence and origins of partisan prejudice and assess its political and societal consequences, including for political participation, discrimination and social cohesion.

PARTISAN will also provide political and societal actors with evidence on three ways to reduce partisan prejudice: interparty contact, recategorization and social norms.PARTISAN will implement new measurement tools in a new twelve-country survey and in experiments conducted in population-based surveys and in the field.

Innovative experimental designs will be used to rigorously assess the origins and consequences of partisan prejudice, as well as potential remedies.Studying a little-studied phenomenon using diverse methods, PARTISAN will significantly extend our knowledge of partisan prejudice, what effects it has and how its impact can be minimized.