Averaging Americans : literature, statistics, and inequality

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Averaging Americans: Literature, Statistics, and Inequality was sparked by a computational discovery I made in a corpus of more than 18,000 works of US fiction: statistical words such as average, normal, and typical distinguish postbellum fiction from its antecedents quantitatively and qualitatively. Averaging Americans explores how authors of the long nineteenth century used statistical thinking to rewrite American identity in ways that were both reactionary and radically egalitarian. This increasing dependence on statistical concepts at the same time that US fiction becomes polemically invested in realist representation is less a coincidence than an understudied fact of US literary history. I reveal how claims to representativeness take on aesthetic and political urgency amid struggles over citizenship, the biopolitics of population management, and the inequalities that define Reconstruction, the Gilded Age, and the Progressive Era. Critiquing claims to representativeness reveals how that concept is both central to yet undertheorized by literary studies. The average American may well be the long nineteenth century's most important fictional character.


Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2021; ©2021
Publication date 2021; 2021
Issuance monographic
Language English


Author Fredner, Erik
Degree supervisor Jones, Gavin Roger, 1968-
Thesis advisor Jones, Gavin Roger, 1968-
Thesis advisor Algee-Hewitt, Mark
Thesis advisor McGurl, Mark, 1966-
Thesis advisor Moya, Paula M. L
Degree committee member Algee-Hewitt, Mark
Degree committee member McGurl, Mark, 1966-
Degree committee member Moya, Paula M. L
Associated with Stanford University, English Department


Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Erik Christopher Fredner.
Note Submitted to the English Department.
Thesis Thesis Ph.D. Stanford University 2021.
Location https://purl.stanford.edu/rp802rv5947

Access conditions

© 2021 by Erik Fredner
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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