Evidence map›Paper›PMID 29073028›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2017

Evolutionary dynamics of language systems.

Simon J Greenhill, Chieh-Hsi Wu, Xia Hua, Michael Dunn, Stephen C Levinson, Russell D Gray

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

  1. Article
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  4. Genetic and linguistic comparisons reveal complex sex-biased transmission of language features.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  5. Article
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  15. The uses and abuses of tree thinking in cultural evolution.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Formal Syntax and Deep History.Frontiers in psychology · 2020
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Simon J GreenhillARC Centre of Excellence for the Dynamics of Language, Australian National University, Canberra, ACT 0200, Australia; simon.greenhill@anu.edu.au.ORCID 0000-0001-7832-6156
Chieh-Hsi WuDepartment of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom.
Xia HuaMacroevolution and Macroecology, Division of Ecology, Evolution, and Genetics, Research School of Biology, Australian National University, Canberra, ACT 0200 Australia.
Michael DunnDepartment of Linguistics and Philology, Uppsala University, 75238 Uppsala, Sweden.
Stephen C LevinsonMax Planck Institute for Psycholinguistics, 6525 XD, Nijmegen, The Netherlands.
Russell D GrayDepartment of Linguistic and Cultural Evolution, Max Planck Institute for the Science of Human History, 07745 Jena, Germany.

Funding

Cancer Research UK ANR00310Medical Research Council
6 · The paper itself

Abstract

Understanding how and why language subsystems differ in their evolutionary dynamics is a fundamental question for historical and comparative linguistics. One key dynamic is the rate of language change. While it is commonly thought that the rapid rate of change hampers the reconstruction of deep language relationships beyond 6,000-10,000 y, there are suggestions that grammatical structures might retain more signal over time than other subsystems, such as basic vocabulary. In this study, we use a Dirichlet process mixture model to infer the rates of change in lexical and grammatical data from 81 Austronesian languages. We show that, on average, most grammatical features actually change faster than items of basic vocabulary. The grammatical data show less schismogenesis, higher rates of homoplasy, and more bursts of contact-induced change than the basic vocabulary data. However, there is a core of grammatical and lexical features that are highly stable. These findings suggest that different subsystems of language have differing dynamics and that careful, nuanced models of language change will be needed to extract deeper signal from the noise of parallel evolution, areal readaptation, and contact.

Indexed as

Biological EvolutionLanguageBayes TheoremDatabases, FactualHumansLinguisticsMonte Carlo MethodOceaniaPapua New GuineaPhylogenyVocabularylanguage dynamicslanguage evolutionlanguage phylogenieslinguisticstypology

Identifiers

PMID29073028
PMCPMC5651730

What OpenQuestion holds

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Registered trials

None linked

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.