Doctoral dissertations

This page includes doctoral dissertations based on data from DIGSSCORE. This includes both analyses using data from DIGSSCORE as well as related research on methods and methodology.

Eelco Harteveld. 2016. “Daring to Vote Right.” Amsterdam Institute for Social Science Research (Aissr). Download from University of AmsterdamAbstract
By now, research has painted a coherent picture of the characteristics and motivations of the citizens supporting Radical Right parties. Nevertheless, one of the most consistent and universal characteristics of the Radical Right electorate has remained puzzling: the considerable overrepresentation of men among these parties’ voters in virtually all countries and at all elections. This ‘gender gap’ – which can substantially constrain parties’ electoral success – could only be partially explained by typical models of Radical Right voting. This suggests that conventional accounts do not fully grasp all aspects of electoral behavior.This dissertation systematically investigates the causes of the overrepresentation of men in the Radical Right electorate, in a range of European countries, from the point of view of various models of voting behavior. It shows that men’s and women’s differing socio-economic conditions play a role in shaping the gap, but mainly so among socio-economically more left-wing Radical Right parties. No evidence was found that suggests that men are more likely to agree with the Radical Right’s ideology. New data collection does show, however, that men are less likely than women to be deterred by both the social stigma and the ongoing association with prejudice that surround many Radical Right parties. Indeed, the last chapter shows that men are systematically more likely to vote for extreme or stigmatized parties of any political color. This dissertation proposes we can better comprehend gendered voting patterns and further increase our understanding of the Radical Right electorate by combining socio-structural, attitudinal and socio-psychological models.