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Measuring Memberships in Collectives in Light of Developments in Cognitive Science and Natural-Language Processing

Michael T. Hannan

Sociological Science December 16, 2022
10.15195/v9.a19


Which individuals and corporate actors belong in a collective, and who decides? Sociology has not had good analytical tools for addressing these questions. Recent work that adapts probabilistic representations of concepts and probabilistic categorization to sociological research opens opportunities for making progress on the measurement of memberships. It turns out that the probabilistic cognitive-based reformulation reveals unexpected connections to language models and natural-language processing. In particular, the leading probabilistic classifier BERT provides new and powerful ways to measure core concepts.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Michael T. Hannan: Graduate School of Business, Stanford University
E-mail: hannan@stanford.edu

Acknowledgments: I have drawn liberally from joint work with Glenn Carroll, Greta Hsu, Balázs Kovács, Gaël Le Mens, Giacomo Negro, Lászlo Pólos, Elizabeth Pontikes, and Amanda Sharkey. I thank them and Susan Olzak for their comments. They are not, of course, responsible for how I use their work here.

  • Citation: Hannan, Michael T. 2022. “Measuring Memberships in Collectives in Light of Developments in Cognitive Science and Natural-Language Processing.” Sociological Science 9:473-492.
  • Received: August 8, 2022
  • Accepted: September 28, 2022
  • Editors: Ari Adut, Ray Reagans
  • DOI: 10.15195/v9.a19


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