Pub Date : 2022-09-30DOI: 10.22363/2687-0088-31228
O. Leontovich, N. Kotelnikova
Urban communication studies is a growing field of research aiming to reveal the regularities of human interaction in an urban context. The goal of the present study is to examine the semiotics of a big Chinese city as a complex communicative system and its effect on the social development of urban community. The material includes over 700 units (toponyms, street signs, advertisements, memorials, local foods and souvenirs, mass media, etc.) mostly collected in Tianjin, China’s fourth biggest city with a population of almost 14 million people. The research methodology is based on critical discourse analysis, ethnographic and semiotic methods, and narrative analysis. The study reveals the structure of communication in a big Chinese city and the integration of language into the city landscape. It indicates that urban historical memories are manifested in the form of memorials, symbols, historic and contemporary narratives. The physical context is associated with names of streets and other topological objects. Verbal and visual semiotic signs are used to ensure people’s psychological and physical safety. Social advertising predominantly deals with the propaganda of Chinese governmental policy, traditional values and ‘civilized behaviour’. Chinese urban subcultures, such as ‘ant tribe, ‘pendulums’, ‘shamate’, etc., reflect new social realities. Food and foodways are defined by cultural values and different aspects of social identity. The image of a big Chinese city is also affected by globalization tendencies and the COVID-19 pandemic. The research framework presented in the study provides an opportunity to show a wide panorama of modern urban life. It can be extrapolated to the investigation of other big cities and their linguistic landscapes.
{"title":"A semiotic portrait of a big Chinese city","authors":"O. Leontovich, N. Kotelnikova","doi":"10.22363/2687-0088-31228","DOIUrl":"https://doi.org/10.22363/2687-0088-31228","url":null,"abstract":"Urban communication studies is a growing field of research aiming to reveal the regularities of human interaction in an urban context. The goal of the present study is to examine the semiotics of a big Chinese city as a complex communicative system and its effect on the social development of urban community. The material includes over 700 units (toponyms, street signs, advertisements, memorials, local foods and souvenirs, mass media, etc.) mostly collected in Tianjin, China’s fourth biggest city with a population of almost 14 million people. The research methodology is based on critical discourse analysis, ethnographic and semiotic methods, and narrative analysis. The study reveals the structure of communication in a big Chinese city and the integration of language into the city landscape. It indicates that urban historical memories are manifested in the form of memorials, symbols, historic and contemporary narratives. The physical context is associated with names of streets and other topological objects. Verbal and visual semiotic signs are used to ensure people’s psychological and physical safety. Social advertising predominantly deals with the propaganda of Chinese governmental policy, traditional values and ‘civilized behaviour’. Chinese urban subcultures, such as ‘ant tribe, ‘pendulums’, ‘shamate’, etc., reflect new social realities. Food and foodways are defined by cultural values and different aspects of social identity. The image of a big Chinese city is also affected by globalization tendencies and the COVID-19 pandemic. The research framework presented in the study provides an opportunity to show a wide panorama of modern urban life. It can be extrapolated to the investigation of other big cities and their linguistic landscapes.","PeriodicalId":53426,"journal":{"name":"Russian Journal of Linguistics","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80533769","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}
Pub Date : 2022-06-29DOI: 10.22363/2687-0088-30307
V. Bayrasheva
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-
{"title":"Review of A.Ya. Shajkevich, V.M. Andryushchenko, N.A. Rebeckaya. 2021. Distributive-statistical analysis of the language of Russian prose of the1850-1870s, vol. 3. Publishing House YaSK, Moscow. ISBN 978-5-907290-61-7","authors":"V. Bayrasheva","doi":"10.22363/2687-0088-30307","DOIUrl":"https://doi.org/10.22363/2687-0088-30307","url":null,"abstract":"<jats:p>-</jats:p>","PeriodicalId":53426,"journal":{"name":"Russian Journal of Linguistics","volume":"52 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75953177","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}
Pub Date : 2022-06-29DOI: 10.22363/2687-0088-30171
M. Solnyshkina, D. McNamara, R. Zamaletdinov
The study presents an overview of discursive complexology, an integral paradigm of linguistics, cognitive studies and computer linguistics aimed at defining discourse complexity. The article comprises three main parts, which successively outline views on the category of linguistic complexity, history of discursive complexology and modern methods of text complexity assessment. Distinguishing the concepts of linguistic complexity, text and discourse complexity, we recognize an absolute nature of text complexity assessment and relative nature of discourse complexity, determined by linguistic and cognitive abilities of a recipient. Founded in the 19th century, text complexity theory is still focused on defining and validating complexity predictors and criteria for text perception difficulty. We briefly characterize the five previous stages of discursive complexology: formative, classical, period of closed tests, constructive-cognitive and period of natural language processing. We also present the theoretical foundations of Coh-Metrix, an automatic analyzer, based on a five-level cognitive model of perception. Computing not only lexical and syntactic parameters, but also text level parameters, situational models and rhetorical structures, Coh-Metrix provides a high level of accuracy of discourse complexity assessment. We also show the benefits of natural language processing models and a wide range of application areas of text profilers and digital platforms such as LEXILE and ReaderBench. We view parametrization and development of complexity matrix of texts of various genres as the nearest prospect for the development of discursive complexology which may enable a higher accuracy of inter- and intra-linguistic contrastive studies, as well as automating selection and modification of texts for various pragmatic purposes.
{"title":"Natural language processing and discourse complexity studies","authors":"M. Solnyshkina, D. McNamara, R. Zamaletdinov","doi":"10.22363/2687-0088-30171","DOIUrl":"https://doi.org/10.22363/2687-0088-30171","url":null,"abstract":"The study presents an overview of discursive complexology, an integral paradigm of linguistics, cognitive studies and computer linguistics aimed at defining discourse complexity. The article comprises three main parts, which successively outline views on the category of linguistic complexity, history of discursive complexology and modern methods of text complexity assessment. Distinguishing the concepts of linguistic complexity, text and discourse complexity, we recognize an absolute nature of text complexity assessment and relative nature of discourse complexity, determined by linguistic and cognitive abilities of a recipient. Founded in the 19th century, text complexity theory is still focused on defining and validating complexity predictors and criteria for text perception difficulty. We briefly characterize the five previous stages of discursive complexology: formative, classical, period of closed tests, constructive-cognitive and period of natural language processing. We also present the theoretical foundations of Coh-Metrix, an automatic analyzer, based on a five-level cognitive model of perception. Computing not only lexical and syntactic parameters, but also text level parameters, situational models and rhetorical structures, Coh-Metrix provides a high level of accuracy of discourse complexity assessment. We also show the benefits of natural language processing models and a wide range of application areas of text profilers and digital platforms such as LEXILE and ReaderBench. We view parametrization and development of complexity matrix of texts of various genres as the nearest prospect for the development of discursive complexology which may enable a higher accuracy of inter- and intra-linguistic contrastive studies, as well as automating selection and modification of texts for various pragmatic purposes.","PeriodicalId":53426,"journal":{"name":"Russian Journal of Linguistics","volume":"27 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86193248","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}
Pub Date : 2022-06-29DOI: 10.22363/2687-0088-31326
V. Solovyev, M. Solnyshkina, D. McNamara
The dramatic expansion of modern linguistic research and enhanced accuracy of linguistic analysis have become a reality due to the ability of artificial neural networks not only to learn and adapt, but also carry out automate linguistic analysis, select, modify and compare texts of various types and genres. The purpose of this article and the journal issue as a whole is to present modern areas of research in computational linguistics and linguistic complexology, as well as to define a solid rationale for the new interdisciplinary field, i.e. discourse complexology. The review of trends in computational linguistics focuses on the following aspects of research: applied problems and methods, computational linguistic resources, contribution of theoretical linguistics to computational linguistics, and the use of deep learning neural networks. The special issue also addresses the problem of objective and relative text complexity and its assessment. We focus on the two main approaches to linguistic complexity assessment: “parametric approach” and machine learning. The findings of the studies published in this special issue indicate a major contribution of computational linguistics to discourse complexology, including new algorithms developed to solve discourse complexology problems. The issue outlines the research areas of linguistic complexology and provides a framework to guide its further development including a design of a complexity matrix for texts of various types and genres, refining the list of complexity predictors, validating new complexity criteria, and expanding databases for natural language.
{"title":"Computational linguistics and discourse complexology: Paradigms and research methods","authors":"V. Solovyev, M. Solnyshkina, D. McNamara","doi":"10.22363/2687-0088-31326","DOIUrl":"https://doi.org/10.22363/2687-0088-31326","url":null,"abstract":"The dramatic expansion of modern linguistic research and enhanced accuracy of linguistic analysis have become a reality due to the ability of artificial neural networks not only to learn and adapt, but also carry out automate linguistic analysis, select, modify and compare texts of various types and genres. The purpose of this article and the journal issue as a whole is to present modern areas of research in computational linguistics and linguistic complexology, as well as to define a solid rationale for the new interdisciplinary field, i.e. discourse complexology. The review of trends in computational linguistics focuses on the following aspects of research: applied problems and methods, computational linguistic resources, contribution of theoretical linguistics to computational linguistics, and the use of deep learning neural networks. The special issue also addresses the problem of objective and relative text complexity and its assessment. We focus on the two main approaches to linguistic complexity assessment: “parametric approach” and machine learning. The findings of the studies published in this special issue indicate a major contribution of computational linguistics to discourse complexology, including new algorithms developed to solve discourse complexology problems. The issue outlines the research areas of linguistic complexology and provides a framework to guide its further development including a design of a complexity matrix for texts of various types and genres, refining the list of complexity predictors, validating new complexity criteria, and expanding databases for natural language.","PeriodicalId":53426,"journal":{"name":"Russian Journal of Linguistics","volume":"4 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72903542","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}
Pub Date : 2022-06-29DOI: 10.22363/2687-0088-30084
A. Laposhina, M. Lebedeva, Alexandra Berlin Khenis
Although word frequency is often associated with the cognitive load on the reader and is widely used for automated text complexity assessment, to date, no eye-tracking data have been obtained on the effectiveness of this parameter for text complexity prediction for the Russian primary school readers. Besides, the optimal ways for taking into account the frequency of individual words to assess an entire text complexity have not yet been precisely determined. This article aims to fill these gaps. The study was conducted on a sample of 53 children of primary school age. As a stimulus material, we used 6 texts that differ in the classical Flesch readability formula and data on the frequency of words in texts. As sources of the frequency data, we used the common frequency dictionary based on the material of the Russian National Corpus and DetCorpus - the corpus of literature addressed to children. The speed of reading the text aloud in words per minute averaged over the grades was employed as a measure of the text complexity. The best predictive results of the relative reading time were obtained using the lemma frequency data from the DetCorpus. At the text level, the highest correlation with the reading speed was shown by the text coverage with a list of 5,000 most frequent words, while both sources of the lists - Russian National Corpus and DetCorpus - showed almost the same correlation values. For a more detailed analysis, we also calculated the correlation of the frequency parameters of specific word forms and lemmas with three parameters of oculomotor activity: the dwell time, fixations count, and the average duration of fixations. At the word-by-word level, the lemma frequency by DetCorpus demonstrated the highest correlation with the relative reading time. The results we obtained confirm the feasibility of using frequency data in the text complexity assessment task for primary school children and demonstrate the optimal ways to calculate frequency data.
{"title":"Word frequency and text complexity: an eye-tracking study of young Russian readers","authors":"A. Laposhina, M. Lebedeva, Alexandra Berlin Khenis","doi":"10.22363/2687-0088-30084","DOIUrl":"https://doi.org/10.22363/2687-0088-30084","url":null,"abstract":"Although word frequency is often associated with the cognitive load on the reader and is widely used for automated text complexity assessment, to date, no eye-tracking data have been obtained on the effectiveness of this parameter for text complexity prediction for the Russian primary school readers. Besides, the optimal ways for taking into account the frequency of individual words to assess an entire text complexity have not yet been precisely determined. This article aims to fill these gaps. The study was conducted on a sample of 53 children of primary school age. As a stimulus material, we used 6 texts that differ in the classical Flesch readability formula and data on the frequency of words in texts. As sources of the frequency data, we used the common frequency dictionary based on the material of the Russian National Corpus and DetCorpus - the corpus of literature addressed to children. The speed of reading the text aloud in words per minute averaged over the grades was employed as a measure of the text complexity. The best predictive results of the relative reading time were obtained using the lemma frequency data from the DetCorpus. At the text level, the highest correlation with the reading speed was shown by the text coverage with a list of 5,000 most frequent words, while both sources of the lists - Russian National Corpus and DetCorpus - showed almost the same correlation values. For a more detailed analysis, we also calculated the correlation of the frequency parameters of specific word forms and lemmas with three parameters of oculomotor activity: the dwell time, fixations count, and the average duration of fixations. At the word-by-word level, the lemma frequency by DetCorpus demonstrated the highest correlation with the relative reading time. The results we obtained confirm the feasibility of using frequency data in the text complexity assessment task for primary school children and demonstrate the optimal ways to calculate frequency data.","PeriodicalId":53426,"journal":{"name":"Russian Journal of Linguistics","volume":"8 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73633836","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}
Pub Date : 2022-06-29DOI: 10.22363/2687-0088-30118
A. Abramov, Vladimir Ivanov
Estimating word complexity with binary or continuous scores is a challenging task that has been studied for several domains and natural languages. Commonly this task is referred to as Complex Word Identification (CWI) or Lexical Complexity Prediction (LCP). Correct evaluation of word complexity can be an important step in many Lexical Simplification pipelines. Earlier works have usually presented methodologies of lexical complexity estimation with several restrictions: hand-crafted features correlated with word complexity, performed feature engineering to describe target words with features such as number of hypernyms, count of consonants, Named Entity tag, and evaluations with carefully selected target audiences. Modern works investigated the use of transforner-based models that afford extracting features from surrounding context as well. However, the majority of papers have been devoted to pipelines for the English language and few translated them to other languages such as German, French, and Spanish. In this paper we present a dataset of lexical complexity in context based on the Russian Synodal Bible collected using a crowdsourcing platform. We describe a methodology for collecting the data using a 5-point Likert scale for annotation, present descriptive statistics and compare results with analogous work for the English language. We evaluate a linear regression model as a baseline for predicting word complexity on handcrafted features, fastText and ELMo embeddings of target words. The result is a corpus consisting of 931 distinct words that used in 3,364 different contexts.
{"title":"Collection and evaluation of lexical complexity data for Russian language using crowdsourcing","authors":"A. Abramov, Vladimir Ivanov","doi":"10.22363/2687-0088-30118","DOIUrl":"https://doi.org/10.22363/2687-0088-30118","url":null,"abstract":"Estimating word complexity with binary or continuous scores is a challenging task that has been studied for several domains and natural languages. Commonly this task is referred to as Complex Word Identification (CWI) or Lexical Complexity Prediction (LCP). Correct evaluation of word complexity can be an important step in many Lexical Simplification pipelines. Earlier works have usually presented methodologies of lexical complexity estimation with several restrictions: hand-crafted features correlated with word complexity, performed feature engineering to describe target words with features such as number of hypernyms, count of consonants, Named Entity tag, and evaluations with carefully selected target audiences. Modern works investigated the use of transforner-based models that afford extracting features from surrounding context as well. However, the majority of papers have been devoted to pipelines for the English language and few translated them to other languages such as German, French, and Spanish. In this paper we present a dataset of lexical complexity in context based on the Russian Synodal Bible collected using a crowdsourcing platform. We describe a methodology for collecting the data using a 5-point Likert scale for annotation, present descriptive statistics and compare results with analogous work for the English language. We evaluate a linear regression model as a baseline for predicting word complexity on handcrafted features, fastText and ELMo embeddings of target words. The result is a corpus consisting of 931 distinct words that used in 3,364 different contexts.","PeriodicalId":53426,"journal":{"name":"Russian Journal of Linguistics","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80817390","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}
Pub Date : 2022-06-29DOI: 10.22363/2687-0088-30122
Robert Joshua Reynolds, L. Janda, T. Nesset
In this paper, we apply usage-based linguistic analysis to systematize the inventory of orthographic errors observed in the writing of non-native users of Russian. The data comes from a longitudinal corpus (560K tokens) of non-native academic writing. Traditional spellcheckers mark errors and suggest corrections, but do not attempt to model why errors are made. Our approach makes it possible to recognize not only the errors themselves, but also the conceptual causes of these errors, which lie in misunderstandings of Russian phonotactics and morphophonology and the way they are represented by orthographic conventions. With this linguistically-based system in place, we can propose targeted grammar explanations that improve users’ command of Russian morphophonology rather than merely correcting errors. Based on errors attested in the non-native academic writing corpus, we introduce a taxonomy of errors, organized by pedagogical domains. Then, on the basis of this taxonomy, we create a set of mal-rules to expand an existing finite-state analyzer of Russian. The resulting morphological analyzer tags wordforms that fit our taxonomy with specific error tags. For each error tag, we also develop an accompanying grammar explanation to help users understand why and how to correct the diagnosed errors. Using our augmented analyzer, we build a webapp to allow users to type or paste a text and receive detailed feedback and correction on common Russian morphophonological and orthographic errors.
{"title":"A cognitive linguistic approach to analysis and correction of orthographic errors","authors":"Robert Joshua Reynolds, L. Janda, T. Nesset","doi":"10.22363/2687-0088-30122","DOIUrl":"https://doi.org/10.22363/2687-0088-30122","url":null,"abstract":"In this paper, we apply usage-based linguistic analysis to systematize the inventory of orthographic errors observed in the writing of non-native users of Russian. The data comes from a longitudinal corpus (560K tokens) of non-native academic writing. Traditional spellcheckers mark errors and suggest corrections, but do not attempt to model why errors are made. Our approach makes it possible to recognize not only the errors themselves, but also the conceptual causes of these errors, which lie in misunderstandings of Russian phonotactics and morphophonology and the way they are represented by orthographic conventions. With this linguistically-based system in place, we can propose targeted grammar explanations that improve users’ command of Russian morphophonology rather than merely correcting errors. Based on errors attested in the non-native academic writing corpus, we introduce a taxonomy of errors, organized by pedagogical domains. Then, on the basis of this taxonomy, we create a set of mal-rules to expand an existing finite-state analyzer of Russian. The resulting morphological analyzer tags wordforms that fit our taxonomy with specific error tags. For each error tag, we also develop an accompanying grammar explanation to help users understand why and how to correct the diagnosed errors. Using our augmented analyzer, we build a webapp to allow users to type or paste a text and receive detailed feedback and correction on common Russian morphophonological and orthographic errors.","PeriodicalId":53426,"journal":{"name":"Russian Journal of Linguistics","volume":"31 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91023182","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}
Pub Date : 2022-06-29DOI: 10.22363/2687-0088-31187
O. Lyashevskaya, Julia Vyacheslavovna Pyzhak, Olga Vinogradova
This article explores the word-formation dimension of learner text complexity which indicates how skilful the non-native speakers are in using more and less complex - and varied - derivational constructions. In order to analyse the association between complexity and writing accuracy in word formation as well as interactive effects of task type, text register, and native language background, we examine the materials of the REALEC corpus of English essays written by university students with Russian L1. We present an approach to measure derivational complexity based on the classification of suffixes offered in Bauer and Nation (1993) and then compare the complexity results and the number of word formation errors annotated in the texts. Starting with the hypothesis that with increasing complexity the number of errors will decrease, we apply statistical analysis to examine the association between complexity and accuracy. We found, first, that the use of more advanced word-formation suffixes affects the number of errors in texts. Second, different levels of suffixes in the hierarchy affect derivation accuracy in different ways. In particular, the use of irregular derivational models is positively associated with the number of errors. Third, the type of examination task and expected format and register of writing should be taken into consideration. The hypothesis holds true for regular but infrequent advanced suffixal models used in more formal descriptive essays associated with an academic register. However, for less formal texts with lower academic register requirements, the hypothesis needs to be amended.
{"title":"Word-formation complexity: a learner corpus-based study","authors":"O. Lyashevskaya, Julia Vyacheslavovna Pyzhak, Olga Vinogradova","doi":"10.22363/2687-0088-31187","DOIUrl":"https://doi.org/10.22363/2687-0088-31187","url":null,"abstract":"This article explores the word-formation dimension of learner text complexity which indicates how skilful the non-native speakers are in using more and less complex - and varied - derivational constructions. In order to analyse the association between complexity and writing accuracy in word formation as well as interactive effects of task type, text register, and native language background, we examine the materials of the REALEC corpus of English essays written by university students with Russian L1. We present an approach to measure derivational complexity based on the classification of suffixes offered in Bauer and Nation (1993) and then compare the complexity results and the number of word formation errors annotated in the texts. Starting with the hypothesis that with increasing complexity the number of errors will decrease, we apply statistical analysis to examine the association between complexity and accuracy. We found, first, that the use of more advanced word-formation suffixes affects the number of errors in texts. Second, different levels of suffixes in the hierarchy affect derivation accuracy in different ways. In particular, the use of irregular derivational models is positively associated with the number of errors. Third, the type of examination task and expected format and register of writing should be taken into consideration. The hypothesis holds true for regular but infrequent advanced suffixal models used in more formal descriptive essays associated with an academic register. However, for less formal texts with lower academic register requirements, the hypothesis needs to be amended.","PeriodicalId":53426,"journal":{"name":"Russian Journal of Linguistics","volume":"32 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78381427","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}
Pub Date : 2022-03-30DOI: 10.22363/2687-0088-27620
Emna Fendri, Mounir Triki
Writing at a postgraduate level is not only meant to obtain a degree in a specific field but also, and more importantly, to secure that ones research is published nationally as well as internationally. In other words, conducting research is first and foremost about making ones distinctive voice heard. Using Martin and Whites (2005) appraisal framework, the present study examines the way Tunisian MA and PhD EFL researchers in applied linguistics establish a dialogue with the reader as a persuasive tool in their texts. The comparison is meant to unveil cross-generic differences in authorial voice manifestation that distinguish postgraduate writers at different degrees. A corpus of 20 Literature Review and 20 Discussion sections taken from 10 MA and 10 PhD dissertations written in English by Tunisian EFL writers is qualitatively and quantitatively explored. Linguistic markers denoting the writers stance are identified in the corpus and are qualitatively studied using the engagement subsystem to qualify the utterance as dialogically contractive or expansive. A quantitative analysis then compares how dialogicality is manifested across the degrees and sections using SPSS. The results show that the negotiation of voice seems to be more problematic for MA researchers in both sections in comparison to PhD writers. Dialogic contraction in the MA subcorpus conveys a limited authorial positioning in the Literature Review section and a failure to stress personal contribution in the Discussion section. PhD researchers frequent reliance on expansion in both sections displays their academic maturity. The critical evaluation of previous works in the Literature Review and the claim for authorial ownership in the Discussion section distinguish them from MA writers. The comparison not only stresses the strengths that distinguish PhD writers but also points out problematic instances in establishing a dialogue with the audience in postgraduate writings. The study findings can be used to consider EFL researchers production in pedagogical contexts in terms of identity manifestation and stance-taking strategies across the different sections of the dissertation.
{"title":"The negotiation of authorial persona in dissertations literature review and discussion sections","authors":"Emna Fendri, Mounir Triki","doi":"10.22363/2687-0088-27620","DOIUrl":"https://doi.org/10.22363/2687-0088-27620","url":null,"abstract":"Writing at a postgraduate level is not only meant to obtain a degree in a specific field but also, and more importantly, to secure that ones research is published nationally as well as internationally. In other words, conducting research is first and foremost about making ones distinctive voice heard. Using Martin and Whites (2005) appraisal framework, the present study examines the way Tunisian MA and PhD EFL researchers in applied linguistics establish a dialogue with the reader as a persuasive tool in their texts. The comparison is meant to unveil cross-generic differences in authorial voice manifestation that distinguish postgraduate writers at different degrees. A corpus of 20 Literature Review and 20 Discussion sections taken from 10 MA and 10 PhD dissertations written in English by Tunisian EFL writers is qualitatively and quantitatively explored. Linguistic markers denoting the writers stance are identified in the corpus and are qualitatively studied using the engagement subsystem to qualify the utterance as dialogically contractive or expansive. A quantitative analysis then compares how dialogicality is manifested across the degrees and sections using SPSS. The results show that the negotiation of voice seems to be more problematic for MA researchers in both sections in comparison to PhD writers. Dialogic contraction in the MA subcorpus conveys a limited authorial positioning in the Literature Review section and a failure to stress personal contribution in the Discussion section. PhD researchers frequent reliance on expansion in both sections displays their academic maturity. The critical evaluation of previous works in the Literature Review and the claim for authorial ownership in the Discussion section distinguish them from MA writers. The comparison not only stresses the strengths that distinguish PhD writers but also points out problematic instances in establishing a dialogue with the audience in postgraduate writings. The study findings can be used to consider EFL researchers production in pedagogical contexts in terms of identity manifestation and stance-taking strategies across the different sections of the dissertation.","PeriodicalId":53426,"journal":{"name":"Russian Journal of Linguistics","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86729385","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}
Pub Date : 2022-03-30DOI: 10.22363/2687-0088-26443
N. Lavrova, Alexandr O. Kozmin
The main aim of the research is to analyze the degree of isomorphism and allomorphy (congruence) of set expressions in three languages - Bulgarian, Russian and English, and to highlight the main factors that have a bearing on the typological affinity of set expressions in these languages. The procedure of the research was two-fold. At the first stage, 4000 idioms were selected from Russian, Bulgarian and English idiomatic dictionaries through the method of random sampling (1334 idioms were selected from each language). For the sake of convenience and comparison, the selected idioms were divided into 5 thematic groups. At the second stage, 850 idioms were further selected for each group through stratified and quota sampling with the aim of subsequent quantification of recurrent keywords in each group. In order to quantify the number of the most frequent keywords in each group and to measure the prevalence of assonance and alliteration, the SPSS software was utilized. The results of the research revealed that the main factors that determine isomorphism and allomorphy among idioms from Bulgarian, Russian and English are (1) typological affinity between Bulgarian and English, (2) genetic kinship, (3) borrowings from English into Russian and Bulgarian and (4) from Russian into Bulgarian, (5) shared idiomatic stock and (6) such extralinguistic factors as the universal makeup of objects and entities, for instance, the same number of functional parts. The research results are relevant for comparative phraseology, areal and contrastive typology as well and for contactology.
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