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地理空间分布反映了语言特征的温度。

Geospatial distributions reflect temperatures of linguistic features.

作者信息

Kauhanen Henri, Gopal Deepthi, Galla Tobias, Bermúdez-Otero Ricardo

机构信息

Zukunftskolleg, University of Konstanz, Universitätsstraße 10, 78464 Konstanz, Germany.

Department of Theoretical and Applied Linguistics, University of Cambridge, Sidgwick Avenue, Cambridge CB3 9DA, UK.

出版信息

Sci Adv. 2021 Jan 1;7(1). doi: 10.1126/sciadv.abe6540. Print 2021 Jan.

Abstract

Quantifying the speed of linguistic change is challenging because the historical evolution of languages is sparsely documented. Consequently, traditional methods rely on phylogenetic reconstruction. Here, we propose a model-based approach to the problem through the analysis of language change as a stochastic process combining vertical descent, spatial interactions, and mutations in both dimensions. A notion of linguistic temperature emerges naturally from this analysis as a dimensionless measure of the propensity of a linguistic feature to undergo change. We demonstrate how temperatures of linguistic features can be inferred from their present-day geospatial distributions, without recourse to information about their phylogenies. Thus, the evolutionary dynamics of language, operating across thousands of years, leave a measurable geospatial signature. This signature licenses inferences about the historical evolution of languages even in the absence of longitudinal data.

摘要

量化语言变化的速度具有挑战性,因为语言的历史演变记录稀少。因此,传统方法依赖于系统发育重建。在这里,我们通过将语言变化分析为一个结合了垂直传承、空间相互作用和两个维度上的变异的随机过程,提出了一种基于模型的解决该问题的方法。作为语言特征发生变化倾向的无量纲度量,语言温度的概念自然地从这一分析中浮现出来。我们展示了如何从语言特征的当今地理空间分布中推断出其温度,而无需借助其系统发育信息。因此,跨越数千年运作的语言进化动态留下了一个可测量的地理空间特征。即使在没有纵向数据的情况下,这个特征也能为关于语言历史演变的推断提供依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/599e/7775759/8dca7ced7433/abe6540-F1.jpg

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