ArticleScientific reports2024
Cultural evolution creates the statistical structure of language.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Language-like statistical structure arises in learned signaling: evidence from birdsong.Science advances · 2026Article
- Language-like properties in the vocal behavior of animals.Current opinion in neurobiology · 2026Review
- Zebra finches transform manipulated songs with shuffled syllables to exhibit linguistic laws.Animal cognition · 2026Article
- Large-Scale Social Feedback and Language Usage: a Distributional Analysis.Computational brain & behavior · 2025Article
- Cultural Transmission Promotes the Emergence of Statistical Properties That Support Language Learning.Cognitive science · 2025Article
- Linguistic Rule Generalisation Creates the Same Distributional Structure That Feeds It.Open mind : discoveries in cognitive science · 2025Article
- A psycholinguistic study of intergroup bias and its cultural propagation.Scientific reports · 2024Article
- Language-like efficiency and structure in house finch song.Proceedings. Biological sciences · 2024Article
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2 authors.
Funding
Abstract
Human language is unique in its structure: language is made up of parts that can be recombined in a productive way. The parts are not given but have to be discovered by learners exposed to unsegmented wholes. Across languages, the frequency distribution of those parts follows a power law. Both statistical properties-having parts and having them follow a particular distribution-facilitate learning, yet their origin is still poorly understood. Where do the parts come from and why do they follow a particular frequency distribution? Here, we show how these two core properties emerge from the process of cultural evolution with whole-to-part learning. We use an experimental analog of cultural transmission in which participants copy sets of non-linguistic sequences produced by a previous participant: This design allows us to ask if parts will emerge purely under pressure for the system to be learnable, even without meanings to convey. We show that parts emerge from initially unsegmented sequences, that their distribution becomes closer to a power law over generations, and, importantly, that these properties make the sets of sequences more learnable. We argue that these two core statistical properties of language emerge culturally both as a cause and effect of greater learnability.
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