Party identification is perhaps the central concept in political science. It has appeared in countless theories and empirical analyses across the political science literature. Party identification was originally conceived as a psychological attachment to the political parties but recent evidence shows that the standard measure for party identification, the NES measure, confounds group identity and group attitude. I show that party social identity, a direct measure of group identity, explains variation in candidate preferences in political primaries where the standard measure of party identification cannot. I also show that machine learning can be used to predict party social identity in surveys that did not directly measure it, and that these predictions can be used to revisit empirical analyses and reevaluate inferences related to party identification. Finally, I show that changes in the NES measure of party identification may be due to changes in either the group attitude or the group identity component and that retrospective evaluations, commonly used to explain changes in party identification, are only associated with changes in the group attitude component of the NES measure. / A Dissertation submitted to the Department of Political Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2018. / July 12, 2018. / Includes bibliographical references. / Brad Gomez, Professor Directing Dissertation; Ashby Plant, University Representative; Matthew Pietryka, Committee Member; Robert Jackson, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_647256 |
| Contributors | Langley, Dennis Franklin (author), Gomez, Brad T., 1970- (professor directing dissertation), Plant, Ashby (university representative), Pietryka, Matthew T. (committee member), Jackson, Robert A., 1966- (committee member), Florida State University (degree granting institution), College of Social Sciences and Public Policy (degree granting college), Department of Political Science (degree granting departmentdgg) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text, doctoral thesis |
| Format | 1 online resource (81 pages), computer, application/pdf |
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