This dissertation examines three research questions related to Muslim minorities in Western Europe. The first chapter explores the question why some countries in Western Europe suffered terrorist attacks perpetrated by Islamist extremists whereas others did not. I argue that there is a positive association between level of discrimination towards Muslim minorities and number of terrorist attacks: the presence of cultural and religious networks in discriminated communities can enhance the socialization of grievances, resulting in the radicalization of a small portion of the community. I conduct a comparative analysis of the cases of Italy, France, and the U.K. In the second chapter, I examine factors that contribute to discriminatory laws against Muslims in Europe (laws like the hijab ban). I argue that more secular countries are more likely to pass such laws as they aim at a more comprehensive separation of the state from religion. On the other hand, less secular countries are less likely to approve this kind of legislation, because in doing so they might open the door to the regulation of the country's "favored" religion (or the majority religion, depending on the institutional architecture of the country). I use a multimethod approach consisting of quantitative and qualitative analyses. Lastly, the third chapter explores two questions; it seeks the effects of (1) geographical proximity of voters to terrorist attacks and (2) number of Muslim immigrants in a geographical area, on the vote share of far-right parties. I use a statistical model that incorporates alternative explanations and focus on the 2017 French Presidential elections. The findings of this dissertation yield relevant policy implications related to integration of Muslim minorities in the European host countries and makes a substantial contribution to the literature in this area of research.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1996 |
| Date | 01 January 2022 |
| Creators | Dell'isola, Davide |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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