Johann-Mattis List, M. Walworth, Simon J. Greenhill, Tiago Tresoldi, Robert Forkel
With increasing amounts of digitally available data from all over the world, manual annotation of cognates in multi-lingual word lists becomes more and more time-consuming in historical linguistics. Using available software packages to pre-process the data prior to manual analysis can drastically speed-up the process of cognate detection. Furthermore, it allows us to get a quick overview on data which have not yet been intensively studied by experts. LingPy is a Python library which provides a large arsenal of routines for sequence comparison in historical linguistics. With LingPy, linguists can not only automatically search for cognates in lexical data, but they can also align the automatically identified words, and output them in various forms, which aim at facilitating manual inspection. In this tutorial, we will briefly introduce the basic concepts behind the algorithms employed by LingPy and then illustrate in concrete workflows how automatic sequence comparison can be applied to multi-lingual word lists. The goal is to provide the readers with all information they need to (1) carry out cognate detection and alignment analyses in LingPy, (2) select the appropriate algorithms for the appropriate task, (3) evaluate how well automatic cognate detection algorithms perform compared to experts, and (4) export their data into various formats useful for additional analyses or data sharing. While basic knowledge of the Python language is useful for all analyses, our tutorial is structured in such a way that scholars with basic knowledge of computing can follow through all steps as well.
{"title":"Sequence comparison in computational historical linguistics","authors":"Johann-Mattis List, M. Walworth, Simon J. Greenhill, Tiago Tresoldi, Robert Forkel","doi":"10.1093/JOLE/LZY006","DOIUrl":"https://doi.org/10.1093/JOLE/LZY006","url":null,"abstract":"With increasing amounts of digitally available data from all over the world, manual annotation of cognates in multi-lingual word lists becomes more and more time-consuming in historical linguistics. Using available software packages to pre-process the data prior to manual analysis can drastically speed-up the process of cognate detection. Furthermore, it allows us to get a quick overview on data which have not yet been intensively studied by experts. LingPy is a Python library which provides a large arsenal of routines for sequence comparison in historical linguistics. With LingPy, linguists can not only automatically search for cognates in lexical data, but they can also align the automatically identified words, and output them in various forms, which aim at facilitating manual inspection. In this tutorial, we will briefly introduce the basic concepts behind the algorithms employed by LingPy and then illustrate in concrete workflows how automatic sequence comparison can be applied to multi-lingual word lists. The goal is to provide the readers with all information they need to (1) carry out cognate detection and alignment analyses in LingPy, (2) select the appropriate algorithms for the appropriate task, (3) evaluate how well automatic cognate detection algorithms perform compared to experts, and (4) export their data into various formats useful for additional analyses or data sharing. While basic knowledge of the Python language is useful for all analyses, our tutorial is structured in such a way that scholars with basic knowledge of computing can follow through all steps as well.","PeriodicalId":37118,"journal":{"name":"Journal of Language Evolution","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/JOLE/LZY006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43239991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The historical connection between the Transeurasian languages, i.e. the Japonic, Koreanic, Tungusic, Mongolic, and Turkic languages, is among the most disputed issues of historical linguistics. Here, we will combine the power of classical historical-comparative linguistics and computational Bayesian phylogenetic methods to infer a phylogeny of the Transeurasian languages. To this end, we will use lexical etymologies supporting the reconstruction of proto-Transeurasian forms with meanings that belong to the Leipzig-Jakarta 200 basic vocabulary list. Our application of Bayesian phylogenetic inference to the classification of the Transeurasian languages is unprecedented. In addition to the methodological implications for Bayesian inference applied to proposed language phyla at relatively deep time depths and with relatively sparse sets of surviving daughter languages, our research has also factual implications for the existing theories of Transeurasian relationships. Our results move the field forward in that they provide a quantitative basis to test various competing hypotheses with regard to the internal structure of the Transeurasian family.
{"title":"Bayesian phylolinguistics reveals the internal structure of the Transeurasian family","authors":"Martine Robbeets, R. Bouckaert","doi":"10.1093/JOLE/LZY007","DOIUrl":"https://doi.org/10.1093/JOLE/LZY007","url":null,"abstract":"The historical connection between the Transeurasian languages, i.e. the Japonic, Koreanic, Tungusic, Mongolic, and Turkic languages, is among the most disputed issues of historical linguistics. Here, we will combine the power of classical historical-comparative linguistics and computational Bayesian phylogenetic methods to infer a phylogeny of the Transeurasian languages. To this end, we will use lexical etymologies supporting the reconstruction of proto-Transeurasian forms with meanings that belong to the Leipzig-Jakarta 200 basic vocabulary list. Our application of Bayesian phylogenetic inference to the classification of the Transeurasian languages is unprecedented. In addition to the methodological implications for Bayesian inference applied to proposed language phyla at relatively deep time depths and with relatively sparse sets of surviving daughter languages, our research has also factual implications for the existing theories of Transeurasian relationships. Our results move the field forward in that they provide a quantitative basis to test various competing hypotheses with regard to the internal structure of the Transeurasian family.","PeriodicalId":37118,"journal":{"name":"Journal of Language Evolution","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/JOLE/LZY007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46719537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tanmoy Bhattacharya, Nancy Retzlaff, Damián E. Blasi, W. Bruce Croft, Michael Cysouw, D. Hruschka, I. Maddieson, Lydia Müller, E. Smith, P. Stadler, George Starostin, Hyejin Youn
The increasing availability of large digital corpora of cross-linguistic data is revolutionizing many branches of linguistics. Overall, it has triggered a shift of attention from detailed questions about individual features to more global patterns amenable to rigorous, but statistical, analyses. This engenders an approach based on successive approximations where models with simplified assumptions result in frameworks that can then be systematically refined, always keeping explicit the methodological commitments and the assumed prior knowledge. Therefore, they can resolve disputes between competing frameworks quantitatively by separating the support provided by the data from the underlying assumptions. These methods, though, often appear as a ‘black box’ to traditional practitioners. In fact, the switch to a statistical view complicates comparison of the results from these newer methods with traditional understanding, sometimes leading to misinterpretation and overly broad claims. We describe here this evolving methodological shift, attributed to the advent of big, but often incomplete and poorly curated data, emphasizing the underlying similarity of the newer quantitative to the traditional comparative methods and discussing when and to what extent the former have advantages over the latter. In this review, we cover briefly both randomization tests for detecting patterns in a largely model-independent fashion and phylolinguistic methods for a more model-based analysis of these patterns. We foresee a fruitful division of labor between the ability to computationally process large volumes of data and the trained linguistic insight identifying worthy prior commitments and interesting hypotheses in need of comparison.
{"title":"Studying language evolution in the age of big data","authors":"Tanmoy Bhattacharya, Nancy Retzlaff, Damián E. Blasi, W. Bruce Croft, Michael Cysouw, D. Hruschka, I. Maddieson, Lydia Müller, E. Smith, P. Stadler, George Starostin, Hyejin Youn","doi":"10.1093/JOLE/LZY004","DOIUrl":"https://doi.org/10.1093/JOLE/LZY004","url":null,"abstract":"\u0000 The increasing availability of large digital corpora of cross-linguistic data is revolutionizing many branches of linguistics. Overall, it has triggered a shift of attention from detailed questions about individual features to more global patterns amenable to rigorous, but statistical, analyses. This engenders an approach based on successive approximations where models with simplified assumptions result in frameworks that can then be systematically refined, always keeping explicit the methodological commitments and the assumed prior knowledge. Therefore, they can resolve disputes between competing frameworks quantitatively by separating the support provided by the data from the underlying assumptions. These methods, though, often appear as a ‘black box’ to traditional practitioners. In fact, the switch to a statistical view complicates comparison of the results from these newer methods with traditional understanding, sometimes leading to misinterpretation and overly broad claims. We describe here this evolving methodological shift, attributed to the advent of big, but often incomplete and poorly curated data, emphasizing the underlying similarity of the newer quantitative to the traditional comparative methods and discussing when and to what extent the former have advantages over the latter. In this review, we cover briefly both randomization tests for detecting patterns in a largely model-independent fashion and phylolinguistic methods for a more model-based analysis of these patterns. We foresee a fruitful division of labor between the ability to computationally process large volumes of data and the trained linguistic insight identifying worthy prior commitments and interesting hypotheses in need of comparison.","PeriodicalId":37118,"journal":{"name":"Journal of Language Evolution","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2018-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/JOLE/LZY004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46793628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
O. Morin, James Winters, Thomas F. Müller, T. Morisseau, Christian Etter, Simon J. Greenhill
Unlike a standard online experiment, a gaming app lets participants interact freely with a vast number of partners, as many times as they wish. The gain is not merely one of statistical power. Cultural evolutionists can use gaming apps to allow large numbers of participants to communicate synchronously; to build realistic transmission chains that avoid the losses of information that occurs in linear chains; to study the effects of partner choice as well as partner control in social interactions. We are releasing an app designed to take advantage of these opportunities and generate realistic language evolution dynamics.
{"title":"What smartphone apps may contribute to language evolution research","authors":"O. Morin, James Winters, Thomas F. Müller, T. Morisseau, Christian Etter, Simon J. Greenhill","doi":"10.1093/JOLE/LZY005","DOIUrl":"https://doi.org/10.1093/JOLE/LZY005","url":null,"abstract":"Unlike a standard online experiment, a gaming app lets participants interact freely with a vast number of partners, as many times as they wish. The gain is not merely one of statistical power. Cultural evolutionists can use gaming apps to allow large numbers of participants to communicate synchronously; to build realistic transmission chains that avoid the losses of information that occurs in linear chains; to study the effects of partner choice as well as partner control in social interactions. We are releasing an app designed to take advantage of these opportunities and generate realistic language evolution dynamics.","PeriodicalId":37118,"journal":{"name":"Journal of Language Evolution","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2018-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/JOLE/LZY005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49286723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Of Tongues and Men: A Review of Morphological Evidence for the Evolution of Language","authors":"Lou Albessard-Ball, A. Balzeau","doi":"10.1093/JOLE/LZY001","DOIUrl":"https://doi.org/10.1093/JOLE/LZY001","url":null,"abstract":"","PeriodicalId":37118,"journal":{"name":"Journal of Language Evolution","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/JOLE/LZY001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61538806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
About a year or so ago, prompted by what seemed (and still does) to be a flood of new methods and findings stemming from the extraction, analysis and interpretation of more and more ancient genomes, both from archaic (Neanderthals and Denisovans) and modern (but long dead) humans, we thought that it is becoming necessary to have a collection of papers looking into the implications for language origins and evolution. Thus, the idea of a special issue on ancient DNA emerged, we dully contacted groups and individual scientists working on these issues, and we soon had an impressive lineup of contributors and contributions. However, due to the extremely dynamic nature of the field and the multiple constraints to which our contributors have to face, we decided to rather have a continuously running series of ‘special sections’ containing contributions touching upon these issues as they arrive, instead of waiting for all contributions to be assembled into a dedicated ‘special issue’. The first four contributions follow, ranging from setting the wider background to focusing on specific genes, and touching not only on ancient DNA but also on genetic data from living humans and even on the archeological and paleoanthropological record. The papers originate from well-known groups and scientists and, despite their diversity, they contribute to setting the foundations for the proper, contextualized, and nuanced interpretation of the new findings that are bound to continue coming, as well as suggesting new methods, data sources and interpretative frameworks that should help our field advance. We begin with Hayley Susan Mountford and Dianne Newbury, geneticists with long-term interests in language at Oxford Brookes University in the UK, whose ‘The Genomic Landscape of Language Disorders: Insights into Evolution’ provides the necessary background for discussing the genetic foundations of language and speech and the interpretation of data from ancient genomes. Their conclusion that ‘[w]e are only just beginning to unravel the highly complex developmental processes that underlie speech in modern humans, and should be extremely cautious in extrapolating any findings into hominins’, far from being pessimistic, must instead form the backbone for any attempts at linking genetics (not only ancient) to theories of language origins and evolution. In ‘What aDNA can (and cannot) tell us about the emergence of language and speech’, Rob DeSalle and Ian Tattersall, a molecular systematics/comparative genomics expert and a palaeoanthropologist with a long history of work on language origins with the American Museum of Natural History in New York, join forces to discuss the questions that ancient DNA may (and may not) answer when it comes to language origins and evolution, to militate for properly placing such findings against the background provided by paleoanthropology and archeology, and to propose an actual method for identifying genes that may be involved in the evolution o
大约一年前，由于对越来越多的古人类(尼安德特人和丹尼索瓦人)和现代人(但早已死亡)的基因组进行提取、分析和解释，似乎(现在仍然如此)涌现出了大量新方法和新发现，我们认为有必要收集一些研究语言起源和进化含义的论文。因此，关于古代DNA的特刊的想法出现了，我们沉闷地联系了研究这些问题的团体和个人科学家，很快我们就有了一个令人印象深刻的贡献者和贡献。然而，由于该领域的极端动态性质和我们的贡献者必须面对的多重限制，我们决定宁愿有一个持续运行的系列“特殊部分”，其中包含涉及这些问题的贡献，而不是等待所有的贡献被集合成一个专门的“特殊问题”。接下来是前四项贡献，从设定更广泛的背景到关注特定基因，不仅涉及古代DNA，还涉及活人的遗传数据，甚至涉及考古和古人类学记录。这些论文来自知名的团体和科学家，尽管它们的多样性，但它们为对新发现的适当的、情境化的和细致入微的解释奠定了基础，这些新发现必然会继续出现，同时也提出了新的方法、数据来源和解释框架，这些建议应该有助于我们的领域发展。我们从Hayley Susan Mountford和Dianne Newbury开始，他们是英国牛津布鲁克斯大学对语言有长期兴趣的遗传学家，他们的“语言障碍的基因组景观:洞察进化”为讨论语言和语音的遗传基础以及对古代基因组数据的解释提供了必要的背景。他们的结论是“我们才刚刚开始揭示现代人类语言背后高度复杂的发展过程，在将任何发现推断为古人类时都应该非常谨慎”，这绝不是悲观，而是必须成为任何将遗传学(不仅仅是古代)与语言起源和进化理论联系起来的尝试的支柱。在“关于语言和言语的出现，aDNA能(和不能)告诉我们什么”中，Rob DeSalle和Ian Tattersall，一位分子系统学/比较基因组学专家和一位在纽约美国自然历史博物馆长期从事语言起源研究的古人类学家，联手讨论了古代DNA在语言起源和进化方面可能(也可能不能)回答的问题。为了将这些发现与古人类学和考古学提供的背景相结合，并提出一种实际的方法来识别可能参与语言和言语进化的基因。《SRGAP2和现代人类语言能力的逐渐进化》是由巴塞罗那大学的语言学家和认知科学团队撰写的，他们对语言进化做出了重要贡献。该团队专注于一个特定的基因，SRGAP2，并基于多种证据，包括其进化史和它所参与的分子途径，认为它可能在声音的进化中发挥了作用
{"title":"Ancient DNA and language evolution: A special section","authors":"A. Benítez‐Burraco, D. Dediu","doi":"10.1093/JOLE/LZX024","DOIUrl":"https://doi.org/10.1093/JOLE/LZX024","url":null,"abstract":"About a year or so ago, prompted by what seemed (and still does) to be a flood of new methods and findings stemming from the extraction, analysis and interpretation of more and more ancient genomes, both from archaic (Neanderthals and Denisovans) and modern (but long dead) humans, we thought that it is becoming necessary to have a collection of papers looking into the implications for language origins and evolution. Thus, the idea of a special issue on ancient DNA emerged, we dully contacted groups and individual scientists working on these issues, and we soon had an impressive lineup of contributors and contributions. However, due to the extremely dynamic nature of the field and the multiple constraints to which our contributors have to face, we decided to rather have a continuously running series of ‘special sections’ containing contributions touching upon these issues as they arrive, instead of waiting for all contributions to be assembled into a dedicated ‘special issue’. The first four contributions follow, ranging from setting the wider background to focusing on specific genes, and touching not only on ancient DNA but also on genetic data from living humans and even on the archeological and paleoanthropological record. The papers originate from well-known groups and scientists and, despite their diversity, they contribute to setting the foundations for the proper, contextualized, and nuanced interpretation of the new findings that are bound to continue coming, as well as suggesting new methods, data sources and interpretative frameworks that should help our field advance. We begin with Hayley Susan Mountford and Dianne Newbury, geneticists with long-term interests in language at Oxford Brookes University in the UK, whose ‘The Genomic Landscape of Language Disorders: Insights into Evolution’ provides the necessary background for discussing the genetic foundations of language and speech and the interpretation of data from ancient genomes. Their conclusion that ‘[w]e are only just beginning to unravel the highly complex developmental processes that underlie speech in modern humans, and should be extremely cautious in extrapolating any findings into hominins’, far from being pessimistic, must instead form the backbone for any attempts at linking genetics (not only ancient) to theories of language origins and evolution. In ‘What aDNA can (and cannot) tell us about the emergence of language and speech’, Rob DeSalle and Ian Tattersall, a molecular systematics/comparative genomics expert and a palaeoanthropologist with a long history of work on language origins with the American Museum of Natural History in New York, join forces to discuss the questions that ancient DNA may (and may not) answer when it comes to language origins and evolution, to militate for properly placing such findings against the background provided by paleoanthropology and archeology, and to propose an actual method for identifying genes that may be involved in the evolution o","PeriodicalId":37118,"journal":{"name":"Journal of Language Evolution","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/JOLE/LZX024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61537412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Studies of severe, monogenic forms of language disorders have revealed important insights into the mechanisms that underpin language development and evolution. It is clear that monogenic mutations in genes such as FOXP2 and CNTNAP2 only account for a small proportion of language disorders seen in children, and the genetic basis of language in modern humans is highly complex and poorly understood. In this review, we examine why we understand so little of the genetic landscape of language disorders, and how the genetic background of an individual greatly affects the way in which a genetic change is expressed. We discuss how the underlying genetics of language disorders has informed our understanding of language evolution, and how recent advances may obtain a clearer picture of language capacity in ancient hominins.
{"title":"The genomic landscape of language: Insights into evolution","authors":"H. Mountford, D. Newbury","doi":"10.1093/JOLE/LZX019","DOIUrl":"https://doi.org/10.1093/JOLE/LZX019","url":null,"abstract":"Studies of severe, monogenic forms of language disorders have revealed important insights into the mechanisms that underpin language development and evolution. It is clear that monogenic mutations in genes such as FOXP2 and CNTNAP2 only account for a small proportion of language disorders seen in children, and the genetic basis of language in modern humans is highly complex and poorly understood. In this review, we examine why we understand so little of the genetic landscape of language disorders, and how the genetic background of an individual greatly affects the way in which a genetic change is expressed. We discuss how the underlying genetics of language disorders has informed our understanding of language evolution, and how recent advances may obtain a clearer picture of language capacity in ancient hominins.","PeriodicalId":37118,"journal":{"name":"Journal of Language Evolution","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/JOLE/LZX019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61534615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The role of pantomime in gestural language evolution, its cognitive bases and an alternative","authors":"E. Abramova","doi":"10.1093/JOLE/LZX021","DOIUrl":"https://doi.org/10.1093/JOLE/LZX021","url":null,"abstract":"","PeriodicalId":37118,"journal":{"name":"Journal of Language Evolution","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/JOLE/LZX021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61535511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A major pursuit within the study of language evolution is to advance understanding of the historical behavior of typological features. Previous studies have identified at least three factors that determine the typological similarity of a pair of languages: (1) vertical stability, (2) horizontal diffusibility, and (3) uni-versality. Of these factors, the first two are of particular interest. Although observed data are affected by all three factors to a greater or lesser degree, previous studies have not jointly modeled them in a straightforward manner. Here, we propose a solution that is derived from the field of cultural anthropology. We present a simple and extensible Bayesian autologistic model to jointly infer the three factors from observed data. Although a large number of missing values in the dataset pose serious difficulties for statistical modeling, the proposed model can robustly estimate these parameters as well as missing values. Applying missing value imputation to indirectly evaluate the estimated parameters, we quantitatively demonstrated that they were meaningful. In conclusion, we briefly compare our findings with those of previous studies and discuss future directions.
{"title":"A statistical model for the joint inference of vertical stability and horizontal diffusibility of typological features","authors":"Yugo Murawaki, Kenji Yamauchi","doi":"10.1093/JOLE/LZX022","DOIUrl":"https://doi.org/10.1093/JOLE/LZX022","url":null,"abstract":"A major pursuit within the study of language evolution is to advance understanding of the historical behavior of typological features. Previous studies have identified at least three factors that determine the typological similarity of a pair of languages: (1) vertical stability, (2) horizontal diffusibility, and (3) uni-versality. Of these factors, the first two are of particular interest. Although observed data are affected by all three factors to a greater or lesser degree, previous studies have not jointly modeled them in a straightforward manner. Here, we propose a solution that is derived from the field of cultural anthropology. We present a simple and extensible Bayesian autologistic model to jointly infer the three factors from observed data. Although a large number of missing values in the dataset pose serious difficulties for statistical modeling, the proposed model can robustly estimate these parameters as well as missing values. Applying missing value imputation to indirectly evaluate the estimated parameters, we quantitatively demonstrated that they were meaningful. In conclusion, we briefly compare our findings with those of previous studies and discuss future directions.","PeriodicalId":37118,"journal":{"name":"Journal of Language Evolution","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/JOLE/LZX022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61536499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I thank Ekaterina Abramova (2018) for using my Mirror System Hypothesis (MSH) of ‘how the brain got language’ as the grounding for her thoughtful critique of pantomime. In her abstract, she asserts that ‘the notion of a pantomime [in MSH] presupposes two sophisticated abilities that themselves are left unexplained: symbolization and intentional communication’. She offers ontogenetic ritualization (OR) as ‘an alternative mechanism that can lead to a suitably complex language precursor while avoiding pantomime altogether’ (emphasis added). I will defend the merits of pantomime while showing that OR is better regarded as a complement to pantomime than as a plausible replacement.
{"title":"In support of the role of pantomime in language evolution","authors":"M. Arbib","doi":"10.1093/JOLE/LZX023","DOIUrl":"https://doi.org/10.1093/JOLE/LZX023","url":null,"abstract":"I thank Ekaterina Abramova (2018) for using my Mirror System Hypothesis (MSH) of ‘how the brain got language’ as the grounding for her thoughtful critique of pantomime. In her abstract, she asserts that ‘the notion of a pantomime [in MSH] presupposes two sophisticated abilities that themselves are left unexplained: symbolization and intentional communication’. She offers ontogenetic ritualization (OR) as ‘an alternative mechanism that can lead to a suitably complex language precursor while avoiding pantomime altogether’ (emphasis added). I will defend the merits of pantomime while showing that OR is better regarded as a complement to pantomime than as a plausible replacement.","PeriodicalId":37118,"journal":{"name":"Journal of Language Evolution","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/JOLE/LZX023","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61537869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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