• The Transformation of Gender in English-Language Fiction

    Author(s):
    David Bamman, Sabrina Lee, Ted Underwood (see profile)
    Date:
    2018
    Group(s):
    Digital Humanists, Linguistics, Sociology, Victorian Studies
    Subject(s):
    Fiction, Characters, Machine learning, Gender, Digital humanities, Natural language processing, 19th century, 20th century
    Item Type:
    Article
    Tag(s):
    Cultural analytics
    Permanent URL:
    http://dx.doi.org/10.17613/M6SC36
    Abstract:
    Preprint to appear in a special issue of Cultural Analytics on "Identity." The article explores the paradox that the representation of gender in fiction became more flexible while the sheer balance of attention between fictional men and women was growing more unequal. We measure the rigidity of gendered roles by asking how easy it is to infer grammatical gender from ostensibly ungendered words used in characterization. In the nineteenth century, roles are so predictable that the inference is easy; it becomes harder as we move toward the present. But the diminishing power of stereotypes does not parallel progress toward equality of representation. On the contrary, by the middle of the twentieth century, women have lost almost half the space they occupied in nineteenth-century fiction. The tension between growing flexibility and growing inequality of representation presents literary historians with a striking paradox; a few potential explanations are considered.
    Notes:
    This is a preprint of an article to appear in Cultural Analytics (February 2018). Data and code supporting this argument are available at https://github.com/tedunderwood/character. By March 2018, code and data will also be archived more permanently in the Cultural Analytics Dataverse (https://dataverse.harvard.edu/dataverse.xhtml?alias=culturalanalytics).
    Metadata:
    Status:
    Published
    Last Updated:
    9 months ago
    License:
    All-Rights-Granted
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