ERIC Number: EJ1358501
Record Type: Journal
Publication Date: 2022-Nov
Pages: 56
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0049-1241
EISSN: EISSN-1552-8294
Machine Learning as a Model for Cultural Learning: Teaching an Algorithm What It Means to Be Fat
Sociological Methods & Research, v51 n4 p1484-1539 Nov 2022
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.
Descriptors: Artificial Intelligence, Cultural Influences, Body Weight, Gender Differences, Moral Values, Health, Social Class, Social Bias, Schemata (Cognition), Obesity, Socialization, Socioeconomic Status, Vocabulary
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: National Library of Medicine (DHHS/NIH); National Science Foundation (NSF), Division of Graduate Education (DGE)
Authoring Institution: N/A
Grant or Contract Numbers: T15LM011271; DGE1650604