[Ias-public] The Institute for Analytical Sociology Seminar: Laura K. Nelson, October 22, 11:00, Online on Zoom

[Madelene Töpfer]

The Institute for Analytical Sociology Seminar

Venue: Zoom (see Zoom link in the end of the email)


Thursday, October 22 @ 11:00

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Leveraging the Alignment between Machine Learning and Intersectionality:

Using Word Embeddings to Measure Intersectional Experiences of the Nineteenth-Century U.S. South

Laura K. Nelson
Northeastern University


Abstract:
Parametric statistics and intersectionality are two powerful discipline-spanning paradigms with nearly mutually exclusive research agendas. The chasm is a result of their fundamentally incompatible epistemologies. Machine learning, a new paradigm poised to supplant parametric statistics in social science research, is alternatively perfectly aligned with intersectionality, although it is not yet being widely used in this way. I argue that we can better realize the full potential of both machine learning and intersectionality by leveraging the epistemological alignment between the two. I empirically demonstrate this alignment through a word embedding model of first-person narratives of the nineteenth-century U.S. South. Situating social categories in relation to social institutions, I find that the culture, economy, and emotion categories distinguish by race, and the domestic category distinguishes by gender. Even in a corpus over-representing abolitionist sentiment, white identities are afforded a status via culture and a humanity via emotions not allowed Black identities.




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