Literature DB >> 35363515

Based on billions of words on the internet, people = men.

April H Bailey1, Adina Williams2, Andrei Cimpian1.   

Abstract

Recent advances have made it possible to precisely measure the extent to which any two words are used in similar contexts. In turn, this measure of similarity in linguistic context also captures the extent to which the concepts being denoted are similar. When extracted from massive corpora of text written by millions of individuals, this measure of linguistic similarity can provide insight into the collective concepts of a linguistic community, concepts that both reflect and reinforce widespread ways of thinking. Using this approach, we investigated the collective concept person/people, which forms the basis for nearly all societal decision- and policy-making. In three studies and three preregistered replications with similarity metrics extracted from a corpus of over 630 billion English words, we found that the collective concept person/people is not gender-neutral but rather prioritizes men over women-a fundamental bias in our species' collective view of itself.

Entities:  

Year:  2022        PMID: 35363515     DOI: 10.1126/sciadv.abm2463

Source DB:  PubMed          Journal:  Sci Adv        ISSN: 2375-2548            Impact factor:   14.136


  1 in total

1.  Propagation of societal gender inequality by internet search algorithms.

Authors:  Madalina Vlasceanu; David M Amodio
Journal:  Proc Natl Acad Sci U S A       Date:  2022-07-12       Impact factor: 12.779

  1 in total

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