The Mathematical Assessment of Long-Range Linguistic Relationships

Language classification differs from biological cladistics in that monogenesis cannot be assumed. Before a cladogram or family tree can be accepted, linguists must be convinced that the languages are related at all. Morpheme tables, or word lists, provide a good framework for investigating relatedness, but methodologies for quantifying and assessing the data statistically are still being developed. The comparative method furnished a viable statistic, recurrent sound correspondences, but by no means to see whether they exceeded levels expected by chance. Organizing correspondences into contingency tables permitted hypothesis testing, with Monte Carlo resampling methods providing the flexibility to support a wide variety of test statistics, including different ways of computing sound recurrences and phonetic similarity. Thus, techniques from both the comparative method and multilateral comparison can be deployed with rigorous numeric assessment. Experiments seek to increase the power of the tests to explore new hypotheses and verify long-range language relationships. Of the many fascinating things linguists do, one might think that the hoary field of comparative linguistics would be one of the least likely to capture the attention of the rest of the world. Yet the public, or at least the journalists who serve them (e.g. Nova 1997; Wade 2000), are fascinated to learn of prehistoric connections between languages. Perhaps more surprising still, comparative linguistics has caught the attention of scientists in many other fields. Computer scientists, mathematicians, geneticists, and biological taxonomists are now some of the most visible practitioners of comparative linguistics (Forster and Renfrew 2006; McMahon and McMahon 2006). Much of the appeal of comparative linguistics for biologists stems from the fact that a key issue in both disciplines is essentially the same. Given a set of entities ( languages, organisms) known to have evolved from a common ancestor, scientists seek to recover the series of divergences that led to the current state of affairs. Biologists have been at the forefront of the effort to systematize this field, which is now generally called cladistics, and to develop algorithms for performing automatic cladistic analysis.