Scott Caddy PhD Defense: 'The Significance of Literary Outliers in Nineteenth-Century British Fiction: A Stylometric Analysis'

Committee: Devoney Looser (chair), George Justice, Annika Mann, Michael Simeone.  ::  ABSTRACT: This dissertation looks at two nineteenth-century works of fiction that are considered outliers: Sir Walter Scott's Saint Ronan's Well (1824) and George Eliot's "The Lifted Veil" (1859). Saint Ronan's Well , a work of domestic fiction, has long been described as unusual for Scott because it is unlike his signature historical novels. "The Lifted Veil,” a Gothic novella, is generally understood as different in kind from Eliot’s realist and social problem fiction. I describe both texts as outliers because they have been described as atypical (in the case of Eliot) or less worthy of study (in the case of Scott) by scholars, for myriad reasons. My work uses both computational methods and tools and traditional literary close readings to test and assess these outlier works. I use stylometry, a computational tool that reads and compares texts to determine authorship attribution, to determine if both texts are indeed outliers for these authors. In addition, I use stylometric methods to analyze claims made by initial reviewers and contemporary critics about comparative authors and genres for Saint Ronan's Well and "The Lifted Veil." I examine statistical or stylistic evidence to test whether those longstanding claims of literary difference are supported with computational evidence. My dissertation reaches three conclusions, based on the results of stylometric tests, described across its four chapters. First, I find that, although Saint Ronan's Well is written in a unique subgenre for Scott, it is statistically and stylistically similar to his other novels. Second, I argue that "The Lifted Veil" is both an outlier for Eliot and an outlier among canonical work of the period in general, as indicated by the results of several stylometric tests. Finally, I argue that focusing on literary outliers is a necessary and productive step forward for traditional and computational literary studies. Computational methods have transformed literary studies in the past decade, especially with the rise of digital humanities as an academic field. Studies by Matthew Jockers (Macroanalytics) and Ben Blatt (Nabokov's Favorite Word is Mauve) show that computational methods and tools, often referred to as distant reading, can reveal overarching trends in genre, word choice, and style in literary history across thousands of texts. However, these computational methods have been met with resistance, specifically by Nan Z. Da, who argues that these methods only reveal the "robust obviousness" found in close reading. My work shows the value of both computational literary studies and traditional literary studies being used in conjunction, particularly in assessing literary outliers. My work seeks to serve as a model for studying literary outliers as significant points of focus, by using stylometry, data analysis, and literary analysis in tandem.

This is a virtual event:

Sheila Luna
Monday, Apr. 12, 2021, 12 p.m.

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