This dissertation studies public attitudes toward nuclear weapons. When do people become more willing to endorse a preemptive nuclear strike against a foreign country? Utilizing theoretical insights from international relations, comparative politics, and social psychology and original experimental survey data from Israel and the U.S., this dissertation aims to answer these questions. Influential strands of scholarship argue that both the public and political elites have internalized anti-nuclear norms. The critics, however, assert that the moral nuclear taboo lacks robustness. The dissertation joins this debate by offering a novel theoretical framework informed by terror management theory (TMT) and suggests that people are more likely to support extreme forms of warfare (e.g., nuclear strikes) when reminded of their own mortality. Thus, consequentialist factors, such as perceived utility, and psychological factors, such as moral foundations theory and TMT can be causal mechanism in the support for nuclear weapons. The findings support this argument as respondents who are treated with increased salience of their own mortality are more likely to support the use of nuclear weapons. Further, the results show that political ideology, threat perception, and religion are all significant factors in shaping individuals' attitudes towards the use of nuclear weapons. Lastly, the work suggests that Israelis in particular tend to support hawkish national security options at the aggregate level. There is a positive effect of conflict events on Israelis' support for hawkish policies. Overall, this dissertation makes a substantial contribution to our current understanding of public opinion on the use of nuclear weapons in a first strike and why nuclear weapons disarmament, elimination, and non-proliferation is deeply challenging.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1511 |
| Date | 01 January 2021 |
| Creators | Horschig, Doreen |
| 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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