In the popular CW superhero series Arrow, vigilante Sara Lance is revealed to be a queer character when she is shown kissing Nyssa al Ghul, her assassin ex-girlfriend. Later in the same episode, Sara is shown kissing Oliver Queen, the show's male protagonist. Throughout her character development in both Arrow and in her later, central role in DC's Legends of Tomorrow, Sara has been portrayed as being a sexually fluid character, with a variety of love interests both male and female. During a crossover episode with The Flash, the character acknowledges her sexuality directly, stating that "… I like men, and I like women." This makes Sara, as a representation of bisexuality in modern media and as a central character in a popular superhero television series, a particularly interesting point of investigation. Overall, this research closely investigates the world-building surrounding Sara's character in both Arrow and DC's Legends of Tomorrow, how Sara emerged as a queer character in these universes, and how surrounding characters and plotlines in the shows have been impacted by her presence. More specifically, this thesis seeks to explore the following questions: How does Sara's bisexuality function in the world of Arrow? How do the worlds of Arrow and Legends characterize her emergence as a queer character? What impact do these worlds of Arrow and Legends have on her sexuality's function? What role does Sara's bisexuality have in larger conversations about representations of sexuality in fan spaces? These questions were investigated by performing a close textual analysis of the two shows and interpreting key scenes, utilizing Michel Foucault's concept of "surfaces of emergence" from Archeology of Knowledge as a theoretical framework, as well as through an analysis of fan activity on the social media website Tumblr relating to the character and her sexuality.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1251 |
| Date | 01 January 2020 |
| Creators | Marks, Rachel |
| 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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