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Updated: Jul 4, 2025

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
Published on: May 10, 2019
America's racial framework of superiority and Americanness embedded in natural language
Messi H J Lee1, Jacob M Montgomery2, Calvin K Lai3
1Division of Computational and Data Sciences, Washington University in St. Louis, St. Louis, MO 63130-4899, USA.
Abstract:
America's racial framework can be summarized using two distinct dimensions: superiority/inferiority and Americanness/foreignness. We investigated America's racial framework in a corpus of spoken and written language using word embeddings. Word embeddings place words on a low-dimensional space where words with similar meanings are proximate, allowing researchers to test whether the positions of group and attribute words in a semantic space reflect stereotypes. We trained a word embedding model on the Corpus of Contemporary American English-a corpus of 1 billion words that span 30 years and 8 text categories-and compared the positions of racial/ethnic groups with respect to superiority and Americanness. We found that America's racial framework is embedded in American English. We also captured an additional nuance: Asian people were stereotyped as more American than Hispanic people. These results are empirical evidence that America's racial framework is embedded in American English.
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