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Language learning, power laws, and sexual selection

Abstract

I discuss the ubiquity of power law distributions in language organisation (and elsewhere), and argue against Miller’s (The mating mind: How sexual choice shaped the evolution of human nature, William Heinemann, London, 2000) argument that large vocabulary size is a consequence of sexual selection. Instead I argue that power law distributions are evidence that languages are best modelled as dynamical systems but raise some issues for models of iterated language learning.

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Notes

  1. 1.

    There have been many attempts to model ‘Zipf Curves’ more accurately beginning with Mandelbrot (1953) and Simon (1955) and continuing more recently with Church and Gale (1995) who use mixtures of Poisson distributions to model word and ngram distributions for applications such as information retrieval and speech recognition. I ignore these here as they are not relevant to the specific goals of this paper.

  2. 2.

    Such effects can be monitored, for example, using the ‘top 20’ on-line dictionary queries published by Cambridge University Press, http://www.dictionary.cambridge.org/top20/top20_0205.asp.

  3. 3.

    http://www.childes.psy.cmu.edu/data/.

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Acknowledgments

I would like to thank the anonymous reviewers for their helpful comments, and Paula Buttery and Anna Korhonen for analysis and plots of data from the Valex lexicon.

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Correspondence to Ted Briscoe.

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Briscoe, T. Language learning, power laws, and sexual selection. Mind & Society 7, 65–76 (2008). https://doi.org/10.1007/s11299-007-0040-8

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Keywords

  • Zipf curve
  • Iterated learning model
  • Small world distribution
  • Evolutionary linguistics
  • Diathesis alternation