Queens of Antiquity
Female rule has often been viewed as a threat to the stability of male-dominated governance, but it has also opened up the possibility of new forms of leadership and challenged existing social structures. This course will focus on four case studies: Cleopatra, Queen of Egypt; Dido, Queen of Carthage; Elizabeth I of England; and Queen Anne of English. It will investigate the historical traces of their reigns, their representation in classical epic, and revisions of that representation in the Renaissance and Restoration, with some attention to contemporary versions of these figures in film, art, fiction, and poetry. While the first part of the course will consider the iconography of famous queens, the second will investigate representations of queenship by women writers. We will consider questions of sexuality, ideas of race, national and indigenous identity, the construction of femininity, and the theory of sovereignty, as well as theatrical history and the nature of epic as a genre.
Understanding how to generate, analyze, and work with datasets in the humanities is often a difficult task without learning how to code or program. In humanities centered courses, we often privilege close reading or qualitative analysis over other methods of knowing, but by learning some new quantitative techniques we better prepare the students to tackle new forms of reading. This class will work with the data from the HathiTrust to develop ideas for thinking about how large groups and different discourse communities thought of queens of antiquity like Cleopatra and Dido.
Grant Glass taught this Data Expedition activity to students in ENGL 290, a spring 2019 course aimed at undergraduates. This experience exemplified that by introducing simple “distant reading” or qualitative concepts in a humanities undergraduate classroom, students would be able to use these tools to drive new types of research questions and think about how reading can include qualitative analysis.
My goals were to give students an introduction to “distant reading,” show how data and collections are created, what algorithms we can apply to those collections, and what types of analysis we can do from the results.
Over the course of two, 1.5-hour class sessions, 10 undergraduates were given the opportunity to create their own datasets and explore the results. For the end product, students created posts to discuss how the visualizations created from their collections helped them better understand
- What visualization is the most useful? Why?
- What does the visualization help you understand about the corpus? What does it obscure?
- What research questions can you generate from the visualization?