Wood, Lauren (2019) Figuring Female Agency in the Victorian Ghost Story. Masters thesis, University of Huddersfield.

This dissertation investigates three highly regarded Victorian writers, Elizabeth Gaskell, M.R. James and Charlotte Perkins Gilman, exploring their vastly different experiences in life. The manner in which each approaches the idea of female agency differs considerably, particularly in regards to the way they chose to figure it within the uncanny elements of the ghost story itself. Gaskell used the figure of the ghost to highlight the lack of agency that women were afforded within their daily lives, focusing on the lingering and often punishing presence of the past.

James, meanwhile, predominantly wrote from the point of view of male characters and has developed a reputation for the lack of female presence in his stories. However, James’s hesitancy to write complex female characters does not mean that there is nothing to explore in relation to female agency. On the contrary, this thesis will argue that James used the animism in objects to represent more than just a ghostly possession, but also his anxieties over change, including the rise of the “New Woman” as a figure of female agency. As for Gilman, this thesis will focus solely on her short story “The Yellow Wallpaper” – a text that, for some, would not be counted amongst the ghost story genre at all.

This thesis will seek to interrogate the manner in which she used elements of the ghost story, including the gothic setting, the narrator’s relationship with her husband and the ghostly figure existing behind the wallpaper, ultimately as vehicles for exploring the liberation for women’s agency. By studying each author’s individual approach to figuring female agency, this dissertation will expose the ways that society dealt with cultural anxieties through literature, considering the manner in which the ghost story allowed writers to push boundaries and confront concerns that were not always easy to express in reality.

FINAL THESIS - LAUREN WOOD.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (442kB) | Preview


Downloads per month over past year

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email