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语言结构中的系统发育信号与进化变化速率。

Phylogenetic signal and rate of evolutionary change in language structures.

作者信息

Hübler Nataliia

机构信息

Department of Linguistic and Cultural Evolution, Max Planck Institute for the Science of Human History, Kahlaische Str. 10, Jena 07745, Germany.

Department of Linguistic and Cultural Evolution, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, Leipzig 04103.

出版信息

R Soc Open Sci. 2022 Mar 30;9(3):211252. doi: 10.1098/rsos.211252. eCollection 2022 Mar.

Abstract

Within linguistics, there is an ongoing debate about whether some language structures remain stable over time, which structures these are and whether they can be used to uncover the relationships between languages. However, there is no consensus on the definition of the term 'stability'. I define 'stability' as a high phylogenetic signal and a low rate of change. I use metric to measure the phylogenetic signal and Hidden Markov Model to calculate the evolutionary rate for 171 structural features coded for 12 Japonic, 2 Koreanic, 14 Mongolic, 11 Tungusic and 21 Turkic languages. To more deeply investigate the differences in evolutionary dynamics of structural features across areas of grammar, I divide the features into 4 language domains, 13 functional categories and 9 parts of speech. My results suggest that there is a correlation between the phylogenetic signal and evolutionary rate and that, overall, two-thirds of the features have a high phylogenetic signal and over a half of the features evolve at a slow rate. Specifically, argument marking (flagging and indexing), derivation and valency appear to be the most stable functional categories, pronouns and nouns the most stable parts of speech, and phonological and morphological levels the most stable language domains.

摘要

在语言学领域,关于某些语言结构是否随时间保持稳定、这些结构具体是什么以及它们是否可用于揭示语言之间的关系,一直存在着争论。然而,对于“稳定性”这一术语的定义尚无共识。我将“稳定性”定义为高系统发生信号和低变化率。我使用度量来衡量系统发生信号,并使用隐马尔可夫模型计算12种日本语、2种朝鲜语、14种蒙古语、11种通古斯语和21种突厥语编码的171个结构特征的进化速率。为了更深入地研究语法领域中结构特征进化动态的差异,我将这些特征分为4个语言域、13个功能类别和9个词性。我的研究结果表明,系统发生信号与进化速率之间存在相关性,总体而言,三分之二的特征具有高系统发生信号,超过一半的特征进化速率缓慢。具体来说,论元标记(标记和索引)、派生和配价似乎是最稳定的功能类别,代词和名词是最稳定的词性,语音和形态层面是最稳定的语言域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9191/8965403/cae82ac0702c/rsos211252f01.jpg

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