ArticleScience advances2022
Based on billions of words on the internet, people = men.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Natural language reveals that political partisans are more affectively aligned over political issues than partisan identities.Communications psychology · 2026Article
- Artificial Intelligence Is Stereotypically Linked More with Socially Dominant Groups in Natural Language.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Article
- Evaluation and Bias Analysis of Large Language Models in Generating Synthetic Electronic Health Records: Comparative Study.Journal of medical Internet research · 2025Article
- "Kids and Girls": Parents convey a male default in child-directed speech.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Multi-region investigation of 'man' as default in attitudes.PloS one · 2025Article
- Dreams are more "predictable" than you think.Frontiers in sleep · 2025Article
- Directionality and representativeness are differentiable components of stereotypes in large language models.PNAS nexus · 2024Article
- Online images amplify gender bias.Nature · 2024Article
- Nature is resource, playground, and gift: What artificial intelligence reveals about human-Nature relationships.PloS one · 2024Article
- Gender stereotypes embedded in natural language are stronger in more economically developed and individualistic countries.PNAS nexus · 2023Article
- Propagation of societal gender inequality by internet search algorithms.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.