Today, the issue of gender plays a larger role in our social discussions than in the past. Over the last decade, new and groundbreaking television shows and movies that showcase gender nonconforming characters and plots that challenge traditional gender roles have become more common. The aim of the present study was to examine the potential effects of gender-neutral representations in media programming and particularly whether different representations of gender might influence audience attitudes toward characters and overall enjoyment of the media. Affective Disposition Theory and Moral Foundations Theory were used as a framework for understanding people's perceptions of gender-neutral media characters. The project involved a pretest/posttest experimental method with random assignment of participants to one of three conditions. Participants completed a pretest including measures of moral modules and trait empathy among other characteristics during week one. The next week, they were assigned to read one of three versions of a dramatic plot synopsis in which the gender of the main character was male, female or ambiguous. After reading the assigned synopsis, participants reported their disposition toward the main character in the stimulus and their enjoyment of the synopsis. Results indicated that depictions of gender that don't activate traditional male and female gender schemas can have a negative influence on the participants' initial dispositions toward the character. The gender representation in the stimulus was not related to reported enjoyment of the plot. Intrinsic moral modules appeared to influence participants' dispositions toward the main character and their enjoyment. However, different modules were important to each of the different outcomes. Implications of the findings are discussed.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-7290 |
| Date | 01 May 2019 |
| Creators | Higley, Diana |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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