{"title":"Mapping Eurolects","authors":"Laura Mori, Benedikt Szmrecsanyi","doi":"10.1075/lic.19017.mor","DOIUrl":null,"url":null,"abstract":"\n Based on the description of EU legislative varieties covering EU directives and their national laws of\n implementation in 11 languages, we are interested in the extent to which Eurolects are similar to each other, above and beyond\n trivial genealogical similarities. We thus utilise a variation-oriented aggregative analysis technique to address these questions:\n (a) What is the precise extent to which Eurolects are similar to each other? (b) Are similarities predicted by extra-linguistic\n affinities? (c) Do factors such as EU accession dates and language policy play a role in shaping the Eurolect clusters? Our\n methodology starts out from a meticulously catalogued list of corpus-based and corpus-driven lexical and grammatical features. Through the observed\n presence or absence of these features, we calculate in a second step the aggregate linguistic distances between all of the\n Eurolects. Finally, in step three, we use a well-established technique, Multidimensional Scaling, to visualize and interpret the\n Eurolect landscape.","PeriodicalId":43502,"journal":{"name":"Languages in Contrast","volume":"9 1","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Languages in Contrast","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1075/lic.19017.mor","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
引用次数: 1
Abstract
Based on the description of EU legislative varieties covering EU directives and their national laws of
implementation in 11 languages, we are interested in the extent to which Eurolects are similar to each other, above and beyond
trivial genealogical similarities. We thus utilise a variation-oriented aggregative analysis technique to address these questions:
(a) What is the precise extent to which Eurolects are similar to each other? (b) Are similarities predicted by extra-linguistic
affinities? (c) Do factors such as EU accession dates and language policy play a role in shaping the Eurolect clusters? Our
methodology starts out from a meticulously catalogued list of corpus-based and corpus-driven lexical and grammatical features. Through the observed
presence or absence of these features, we calculate in a second step the aggregate linguistic distances between all of the
Eurolects. Finally, in step three, we use a well-established technique, Multidimensional Scaling, to visualize and interpret the
Eurolect landscape.
期刊介绍:
Languages in Contrast aims to publish contrastive studies of two or more languages. Any aspect of language may be covered, including vocabulary, phonology, morphology, syntax, semantics, pragmatics, text and discourse, stylistics, sociolinguistics and psycholinguistics. Languages in Contrast welcomes interdisciplinary studies, particularly those that make links between contrastive linguistics and translation, lexicography, computational linguistics, language teaching, literary and linguistic computing, literary studies and cultural studies.