{"title":"武汉话特殊代词“他”的恢复分析*","authors":"Chen Zhao","doi":"10.1111/stul.12203","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":46179,"journal":{"name":"STUDIA LINGUISTICA","volume":"27 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2022-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ON THE SPECIAL PRONOUN\\n TA\\n IN THE WUHAN DIALECT OF CHINESE: A RESUMPTIVE ANALYSIS\\n *\",\"authors\":\"Chen Zhao\",\"doi\":\"10.1111/stul.12203\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":46179,\"journal\":{\"name\":\"STUDIA LINGUISTICA\",\"volume\":\"27 1\",\"pages\":\"\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2022-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"STUDIA LINGUISTICA\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/stul.12203\",\"RegionNum\":3,\"RegionCategory\":\"文学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"LANGUAGE & LINGUISTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"STUDIA LINGUISTICA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/stul.12203","RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
期刊介绍:
Studia Linguistica is committed to the publication of high quality, original papers and provides an international forum for the discussion of theoretical linguistic research, primarily within the fields of grammar, cognitive semantics and language typology. The principal aim is to open a channel of communication between researchers operating in traditionally diverse fields while continuing to focus on natural language data.