Bayesian methods for ancestral state reconstruction in morphosyntax: Exploring the history of argument marking strategies in a large language family

IF 2.1 N/A LANGUAGE & LINGUISTICS Journal of Language Evolution Pub Date : 2022-05-28 DOI:10.1093/jole/lzac002
Joshua L. Phillips, Claire Bowern
{"title":"Bayesian methods for ancestral state reconstruction in morphosyntax: Exploring the history of argument marking strategies in a large language family","authors":"Joshua L. Phillips, Claire Bowern","doi":"10.1093/jole/lzac002","DOIUrl":null,"url":null,"abstract":"\n Bayesian phylogenetic methods have been gaining traction and currency in historical linguistics, as their potential for uncovering elements of language change is increasingly understood. Here, we demonstrate a proof of concept for using ancestral state reconstruction methods to reconstruct changes in morphology. We use a simple Brownian motion model of character evolution to test how splits in ergative marking evolve across Pama-Nyungan, a large family of Australian languages. We are able to recover linguistically plausible paths of change, as well as rejecting implausible paths. The results of these analyses elucidate constraints on changes that have led to extensive synchronic variation in an interlocking morphological system. They further provide evidence of an ergative–accusative split traceable to Proto-Pama-Nyungan.","PeriodicalId":37118,"journal":{"name":"Journal of Language Evolution","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Language Evolution","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/jole/lzac002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"N/A","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
引用次数: 2

Abstract

Bayesian phylogenetic methods have been gaining traction and currency in historical linguistics, as their potential for uncovering elements of language change is increasingly understood. Here, we demonstrate a proof of concept for using ancestral state reconstruction methods to reconstruct changes in morphology. We use a simple Brownian motion model of character evolution to test how splits in ergative marking evolve across Pama-Nyungan, a large family of Australian languages. We are able to recover linguistically plausible paths of change, as well as rejecting implausible paths. The results of these analyses elucidate constraints on changes that have led to extensive synchronic variation in an interlocking morphological system. They further provide evidence of an ergative–accusative split traceable to Proto-Pama-Nyungan.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
形态句法中祖先状态重建的贝叶斯方法:在一个大语系中探讨论点标记策略的历史
贝叶斯系统发育方法在历史语言学中越来越受欢迎,因为人们越来越了解它们揭示语言变化要素的潜力。在这里,我们展示了使用祖先状态重建方法来重建形态学变化的概念证明。我们使用一个简单的字符进化的布朗运动模型来测试作格标记中的分裂是如何在澳大利亚语言大家族Pama Nyungan中进化的。我们能够恢复语言上看似合理的变化路径,也能够拒绝看似不合理的路径。这些分析的结果阐明了对变化的限制,这些变化导致了连锁形态系统中广泛的同步变化。它们进一步提供了可追溯到Proto Pama Nyungan的作格-宾格分裂的证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Language Evolution
Journal of Language Evolution Social Sciences-Linguistics and Language
CiteScore
4.50
自引率
7.70%
发文量
8
期刊最新文献
Derivational morphology and suffixing bias on linguistic and nonlinguistic material Bayesian phylogenetic analysis of pitch-accent systems based on accentual class merger: a new method applied to Japanese dialects The evolution of evolutionary linguistics Evolutionary pathways of complexity in gender systems Correction to: The scientometric landscape of Evolang: A comprehensive database of the Evolang conference
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1