Areal pressure in grammatical evolution

Abstract

This article investigates the evolutionary and spatial dynamics of typological characters in 117 Indo-European languages. We partition types of change (i.e., gain or loss) for each variant according to whether they bring about a simplification in morphosyntactic patterns that must be learned, whether they are neutral (i.e., neither simplifying nor introducing complexity) or whether they introduce a more complex pattern. We find that changes which introduce complexity show significantly less areal signal (according to a metric we devise) than changes which simplify and neutral changes, but we find no significant differences between the latter two groups. This result is compatible with a scenario where certain types of parallel change are more likely to be mediated by advergence and contact between proximate speech communities, while other developments are due purely to drift and are largely independent of intercultural contact.

Diachronic Atlas of Comparative Linguistics (DiACL)—A database for ancient language typology

“…This we may identify for a number of combinations of interdependent variants, such as ‘a language cannot have both full and no A agreement’ ( S2 Appendix , 276–277), which can be tested against the data. We tabulate illicit value combinations for these sets of variants ( S3 Appendix , both from [ 61 ]), and find that for a majority of our postulated sets, illicit combinations are found only in 10% of the character mapping simulations. However, in other of our postulated illicit combinations, the results are not compatible with our assumptions, with 50–60% occurrence of dependencies in the data [ 61 ], indicating that (with the exception of case first and case last, S4 Appendix , 12 and S2 Appendix , 260–261), none of our postulated illicit combinations are actually completely absent in our data, and are therefore not logical dependencies in this sense.…”

Testing methods of linguistic homeland detection using synthetic data

“…1, encoded as in the output for the language family simulation program. 2 Using one and the same phylogeny, we produce 1000 diffusion scenarios. Since these take place in real-life geography they will be sensitive to natural boundaries such as mountains, deserts, and bodies of water.…”

Automated methods for the investigation of language contact, with a focus on lexical borrowing

“…That character mapping techniques are not only applicable to wordlists, but also to structural data, is shown in the recent work by Cathcard, Carling, Larson, Johansson, and Round () in which the authors use a Bayesian likelihood framework for character mapping to identify areally transmitted traits from structural data among Indo‐European languages.…”

“…That character mapping techniques are not only applicable to wordlists, but also to structural data, is shown in the recent work by Cathcard, Carling, Larson, Johansson, and Round (2018) in which the authors use a Bayesian likelihood framework for character mapping to identify areally transmitted traits from structural data among Indo-European languages. Table 1 provides a summary of the four different methods compared so far, including the data to which they were applied, the methods employed, the literature in which they were applied, and information on code availability.…”