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New methods in genealogical classification of languages and linguistic reconstruction

Abstract

One of the most important issues in modern historical linguistics is that of verifcation of hypotheses of deep level relationship between various linguistic families. Most noncontroversial theories of genetic relationship do not deal with time depths that surpass 5 or 6 thousand years ago, and the classic comparative method is often found insuffcient to reliably justify suggestions of macrofamily level relationship (such as “Nostratic”). It is therefore necessary to supplement the comparative method with additional techniques, particularly based on progress in the area of phylogenetic modeling, as well as with empirical typological evidence on language change that has been accumulated over several decades of intense research. In this short paper, we briefy describe the main goals and perspectives of the project upon which a team of our researchers is currently working at the Laboratory of Oriental Studies and comparative linguistics: (a) integration of signifcant data on the typology of phonetic and semantic change into the procedure of verifcation of language relationship; (b) improvement of the currently employed algorithms for statistical analysis of the basic lexicon; (c) inclusion of the results of our research in the computer software STARLING, originally designed by Sergei Starostin as a basic tool for historical linguistics purposes, and their approbation on linguistic databases for major linguistic families of Eurasia, Africa, and America that are currently being compiled for the related Web project “The Global Lexicostatistical Database”.

About the Authors

A. Kassian
The Russian Presidential Academy of National Economy and Public Administration


G. Starostin
Laboratory of Oriental studies and comparative linguistics, School of Advanced Studies in the Humanities


Review

For citations:


Kassian A., Starostin G. New methods in genealogical classification of languages and linguistic reconstruction. Shagi / Steps. 2015;1(1):206-212. (In Russ.)

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ISSN 2412-9410 (Print)
ISSN 2782-1765 (Online)