ArticleScience advances2023
Societies of strangers do not speak less complex languages.
Article in Science advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 35 citations in OpenAlex.
- An inverse correlation between structural linguistic and human genetic diversity.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Contact and complexity in English varieties: The influence of speaker numbers on syntheticity and grammaticity.PloS one · 2026Article
- Community size rather than grammatical complexity better predicts Large Language Model accuracy in a novel Wug Test.PloS one · 2026Article
- Agreement Marking May Facilitate Noun Class Learning in Children But Not Adults.Open mind : discoveries in cognitive science · 2026Article
- Assessing the Role of Socio-Demographic Triggers on Kolmogorov-Based Complexity in Spoken English Varieties.Entropy (Basel, Switzerland) · 2025Article
- Macroevolutionary analysis of polysynthesis shows that language complexity is more likely to evolve in small, isolated populations.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- The Relationship Between Community Size and Iconicity in Sign Languages.Cognitive science · 2025Article
- Lexibank 2: pre-computed features for large-scale lexical data.Open research Europe · 2025Article
- Still No Evidence for an Effect of the Proportion of Non-Native Speakers on Natural Language Complexity.Entropy (Basel, Switzerland) · 2024Article
- Islands are engines of language diversity.Nature ecology & evolution · 2024Article
- Human languages with greater information density have higher communication speed but lower conversation breadth.Nature human behaviour · 2024Article
- The evolutionary dynamics of how languages signal who does what to whom.Scientific reports · 2024Article
- Article
- Grammars Across Time Analyzed (GATA): a dataset of 52 languages.Scientific data · 2023Article
- Editorial expression of concern.Science advances · 2023Article
- Languages with more speakers tend to be harder to (machine-)learn.Scientific reports · 2023Article
- A large quantitative analysis of written language challenges the idea that all languages are equally complex.Scientific reports · 2023Article
Corrections and comments
- Expression of concern · 2023-11-08Concerns/Issues about Results and/or Conclusions · Error in Analyses ·
- Erratum issued
- Expression of concern
Authors and funding
9 authors at 6 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many recent proposals claim that languages adapt to their environments. The linguistic niche hypothesis claims that languages with numerous native speakers and substantial proportions of nonnative speakers (societies of strangers) tend to lose grammatical distinctions. In contrast, languages in small, isolated communities should maintain or expand their grammatical markers. Here, we test these claims using a global dataset of grammatical structures, Grambank. We model the impact of the number of native speakers, the proportion of nonnative speakers, the number of linguistic neighbors, and the status of a language on grammatical complexity while controlling for spatial and phylogenetic autocorrelation. We deconstruct "grammatical complexity" into two separate dimensions: how much morphology a language has ("fusion") and the amount of information obligatorily encoded in the grammar ("informativity"). We find several instances of weak positive associations but no inverse correlations between grammatical complexity and sociodemographic factors. Our findings cast doubt on the widespread claim that grammatical complexity is shaped by the sociolinguistic environment.
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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.