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Machine Learning as a Model for Cultural Learning: Teaching an Algorithm What it Means to be Fat

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  • Alina Arseniev-Koehler
  • Jacob G. Foster

Abstract

Public culture is a powerful source of cognitive socialization; for example, media language is full of meanings about body weight. Yet it remains unclear how individuals process meanings in public culture. We suggest that schema learning is a core mechanism by which public culture becomes personal culture. We propose that a burgeoning approach in computational text analysis – neural word embeddings – can be interpreted as a formal model for cultural learning. Embeddings allow us to empirically model schema learning and activation from natural language data. We illustrate our approach by extracting four lower-order schemas from news articles: the gender, moral, health, and class meanings of body weight. Using these lower-order schemas we quantify how words about body weight “fill in the blanks†about gender, morality, health, and class. Our findings reinforce ongoing concerns that machine-learning models (e.g., of natural language) can encode and reproduce harmful human biases.

Suggested Citation

  • Alina Arseniev-Koehler & Jacob G. Foster, 2022. "Machine Learning as a Model for Cultural Learning: Teaching an Algorithm What it Means to be Fat," Sociological Methods & Research, , vol. 51(4), pages 1484-1539, November.
  • Handle: RePEc:sae:somere:v:51:y:2022:i:4:p:1484-1539
    DOI: 10.1177/00491241221122603
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    References listed on IDEAS

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    1. Gabriel Grand & Idan Asher Blank & Francisco Pereira & Evelina Fedorenko, 2022. "Semantic projection recovers rich human knowledge of multiple object features from word embeddings," Nature Human Behaviour, Nature, vol. 6(7), pages 975-987, July.
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    3. Puhl, R.M. & Heuer, C.A., 2010. "Obesity stigma: Important considerations for public health," American Journal of Public Health, American Public Health Association, vol. 100(6), pages 1019-1028.
    4. Molly Lewis & Gary Lupyan, 2020. "Gender stereotypes are reflected in the distributional structure of 25 languages," Nature Human Behaviour, Nature, vol. 4(10), pages 1021-1028, October.
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    Cited by:

    1. Pop, Ioana Andreea & Gielens, Erwin & Kottmann, Hannah & Achterberg, Peter, 2024. "Exploring the discourses around microdosing psychedelics within the r/microdosing online community," Social Science & Medicine, Elsevier, vol. 347(C).
    2. Taylor, Marshall A. & Stoltz, Dustin S., 2024. "A Workflow for Analyzing Cultural Schemas in Texts," SocArXiv zvwn2, Center for Open Science.

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