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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">Russian Language Studies</journal-id><journal-title-group><journal-title xml:lang="en">Russian Language Studies</journal-title><trans-title-group xml:lang="ru"><trans-title>Русистика</trans-title></trans-title-group></journal-title-group><issn publication-format="print">2618-8163</issn><issn publication-format="electronic">2618-8171</issn><publisher><publisher-name xml:lang="en">Peoples’ Friendship University of Russia named after Patrice Lumumba</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">42906</article-id><article-id pub-id-type="doi">10.22363/2618-8163-2024-22-4-518-539</article-id><article-id pub-id-type="edn">APRGCY</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>Key Issues of Russian Language Research</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>Актуальные проблемы исследований русского языка</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">Predicative potential of lexical parameters: text complexity assessment in Russian language textbooks for 5-7 grades</article-title><trans-title-group xml:lang="ru"><trans-title>Предикативная сила лексических параметров: оценка сложности текста в учебниках по русскому языку для 5-7 классов</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-5760-0934</contrib-id><contrib-id contrib-id-type="scopus">57195974758</contrib-id><contrib-id contrib-id-type="researcherid">ABF-7003-2020</contrib-id><contrib-id contrib-id-type="spin">9243-6995</contrib-id><name-alternatives><name xml:lang="en"><surname>Andreeva</surname><given-names>Mariia I.</given-names></name><name xml:lang="ru"><surname>Андреева</surname><given-names>Мария Игоревна</given-names></name></name-alternatives><bio xml:lang="en"><p>PhD in Philology, Associate Professor of the Department of Foreign Languages, Kazan State Medical University; Senior researcher of the research laboratory ‘Multidisciplinary Text Investigation’, Kazan (Volga region) Federal University</p></bio><bio xml:lang="ru"><p>кандидат филологических наук, доцент кафедры иностранных языков, Казанский государственный медицинский университет; старший научный сотрудник НИЛ «Мультидисциплинарные исследования текста», Казанский (Приволжский) федеральный университет</p></bio><email>mariia99andreeva@yandex.ru</email><xref ref-type="aff" rid="aff1"/><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-2692-1698</contrib-id><contrib-id contrib-id-type="scopus">56027359900</contrib-id><contrib-id contrib-id-type="researcherid">M-2174-2013</contrib-id><contrib-id contrib-id-type="spin">4027-8784</contrib-id><name-alternatives><name xml:lang="en"><surname>Zamaletdinov</surname><given-names>Radif R.</given-names></name><name xml:lang="ru"><surname>Замалетдинов</surname><given-names>Радиф Рифкатович</given-names></name></name-alternatives><bio xml:lang="en"><p>Doctor Habil. (Philology), Professor, Director of the Institute of Philology and Intercultural Communication, Head of the Department of General Linguistics and Turkology</p></bio><bio xml:lang="ru"><p>доктор филологических наук, профессор, директор Института филологии и межкультурной коммуникации, заведующий кафедрой общего языкознания и тюркологии</p></bio><email>director.ifmk@gmail.com</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-7395-7028</contrib-id><contrib-id contrib-id-type="scopus">57194527178</contrib-id><contrib-id contrib-id-type="researcherid">AAH-9347-2019</contrib-id><contrib-id contrib-id-type="spin">2332-6093</contrib-id><name-alternatives><name xml:lang="en"><surname>Borisova</surname><given-names>Anna S.</given-names></name><name xml:lang="ru"><surname>Борисова</surname><given-names>Анна Степановна</given-names></name></name-alternatives><bio xml:lang="en"><p>PhD in Philology, Associate Professor of the Department of Foreign Languages, Faculty of Philology</p></bio><bio xml:lang="ru"><p>кандидат филологических наук, доцент кафедры иностранных языков, филологический факультет</p></bio><email>borisova-as@rudn.ru</email><xref ref-type="aff" rid="aff3"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Kazan State Medical University</institution></aff><aff><institution xml:lang="ru">Казанский государственный медицинский университет</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">Kazan (Volga Region) Federal University</institution></aff><aff><institution xml:lang="ru">Казанский (Приволжский) федеральный университет</institution></aff></aff-alternatives><aff-alternatives id="aff3"><aff><institution xml:lang="en">RUDN University</institution></aff><aff><institution xml:lang="ru">Россйский университет дружбы народов</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2024-12-15" publication-format="electronic"><day>15</day><month>12</month><year>2024</year></pub-date><volume>22</volume><issue>4</issue><issue-title xml:lang="en">LINGUISTIC PROFILES OF RUSSIAN TEXTS: GOING FROM FORM TO MEANING</issue-title><issue-title xml:lang="ru">ЛИНГВИСТИЧЕСКОЕ ПРОФИЛИРОВАНИЕ ТЕКСТОВ НА РУССКОМ ЯЗЫКЕ: ОТ ФОРМ К СМЫСЛАМ</issue-title><fpage>518</fpage><lpage>539</lpage><history><date date-type="received" iso-8601-date="2025-02-18"><day>18</day><month>02</month><year>2025</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2024, Andreeva M.I., Zamaletdinov R.R., Borisova A.S.</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2024, Андреева М.И., Замалетдинов Р.Р., Борисова А.С.</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="en">Andreeva M.I., Zamaletdinov R.R., Borisova A.S.</copyright-holder><copyright-holder xml:lang="ru">Андреева М.И., Замалетдинов Р.Р., Борисова А.С.</copyright-holder><ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/><license><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">https://creativecommons.org/licenses/by-nc/4.0</ali:license_ref></license></permissions><self-uri xlink:href="https://journals.rudn.ru/russian-language-studies/article/view/42906">https://journals.rudn.ru/russian-language-studies/article/view/42906</self-uri><abstract xml:lang="en"><p>This study addresses the urgent issue of assessing the influence of lexical parameters on text complexity. The research has been conducted on the material of a specialized linguistic corpus, which includes texts of 15 modern Russian language textbooks for 5-7 grades, with a total size of 811911 words. The study is aimed at identifying the scale and dynamics of changes in vocabulary of Russian textbooks for 5-7 grades. The research algorithm included the following stages: (a) identifying the size and content of vocabulary in modern Russian textbooks for 5-7 grades, (b) assessing the share of linguistic terms in their vocabulary, and (c) identifying complexity predictors, i.e. parameters demonstrating a statistically significant correlation with readability. The analytical part of the study was preceded by a meta-description of the corpus, its tokenization, lemmatization, segmentation into fragments of approximately 1000 words. Text parameters were calculated using the text profiler RuLingva, and the correlation strength was assessed with STATISTIKA. To ensure the research results reliability, co-dependencies of lexical parameters and text readability were analyzed at two levels: at the textbook level (with average indicators for 15 textbooks for 5-7 grades) and at the level of 1000-word fragments. We revealed a slightly lower readability index, which was expected to be 1.0-1.5 levels higher. The latter may be a characteristic of Russian language textbook as a genre and indicate eclecticism of academic texts, including fragments of research discourse (rules and theory), fiction (exercises), and instructional discourse (texts of tasks). The research demonstrated that the share of linguistic terms does not exceed 2 % in the textbook vocabulary, but their share in the texts rises to 13 %. The statistical analysis indicates that the indices of ‘lexical density’, cohesion (global and local overlaps of nouns and arguments), ‘descriptiveness’ (ratio between adjectives and nouns), ‘narrativity’ (ratio between verbs and nouns), and the share of nouns in the genitive case are text complexity predictors. The prospects for the research include studying verbs and pronouns as complexity predictors in Russian language textbooks.</p></abstract><trans-abstract xml:lang="ru"><p>Рассмотрена оценка влияния лексических параметров на сложность текста и реализована на материале специализированного лингвистического корпуса, в состав которого вошли тексты 15 действующих учебников по русскому языку для 5-7 классов общим объемом 811911 слов. Исследование нацелено на определение объема и динамики изменения лексического состава учебников для 5-7 классов современных линеек учебников по русскому языку. Алгоритм исследования: (а) выявление объема и состава лексики в текстах учебников; (б) оценка доли лингвистических терминов в их составе; (в) идентификация предикторов сложности, т.е. параметров, демонстрирующих статистически значимую корреляцию с читабельностью. Осуществлению аналитической части исследования предшествовали метаописание корпуса, его токенизация, лемматизация, сегментирование на отрывки приблизительно по 1000 слов. Расчеты параметров текста производились при помощи текстового профайлера RuLingva, оценка силы корреляционных зависимостей выполнялась при помощи программы STATISTIKA. Для достоверности результатов исследования анализ влияния лексиче ских параметров на читабельность текста проведен на двух уровнях: учебники (рассчитывались средние показатели по 15 учебникам 5-7 классов), 1000-словные сегменты текста. Выявлен несколько сниженный (в среднем на 1.0-1.5. уровней) от ожидаемого индекс читабельности изученных текстов, который может служить характеристикой текста учебника по русскому языку как жанра и свидетельствует об эклектичности учебного текста, включающего фрагменты научного стиля (правила), художественного (упражнения) и делового (инструкции и задания к упражнениям). Установлено, что доля терминов не превышает 2 % в словарном составе учебников, но их доля в тексте поднимается до 13 %. Доказано, что предиктивной силой роста сложности текста обладают индексы «лексической плотности», связности (локальный и глобальный повторы существительного и аргумента), «дескриптивность» (отношение прилагательных к существительным), «нарративность» (отношение глаголов к существительным), а также доля имен существительных в родительном падеже. Перспектива исследования видится в изучении роли глаголов и местоимений в текстах учебников по русскому языку как предикторов сложности.</p></trans-abstract><kwd-group xml:lang="en"><kwd>educational text</kwd><kwd>corpus of language</kwd><kwd>educational text readability</kwd><kwd>word frequency</kwd><kwd>linguistic terminology</kwd><kwd>lexical density</kwd><kwd>cohesion</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>учебный текст</kwd><kwd>корпус языка</kwd><kwd>сложность учебного текста</kwd><kwd>частотная лексика</kwd><kwd>лингвистическая терминология</kwd><kwd>лексическая плотность</kwd><kwd>связность</kwd></kwd-group><funding-group><funding-statement xml:lang="en">This article has been supported by the Kazan Federal University Strategic Academic Leadership Program (PRIORITY-2030). This publication has been supported by the RUDN University Scientific Projects Grant System, project no. 050738-0-000.</funding-statement><funding-statement xml:lang="ru">Работа выполнена за счет средств Программы стратегического академического лидерства Казанского (Приволжского) федерального университета (ПРИОРИТЕТ–2030). Работа выполнена в рамках проекта № 050738-0-000 системы грантовой поддержки научных проектов РУДН.</funding-statement></funding-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Andreeva, M., Solnyshkina M., Bukach, O., Zaikin, A., &amp; Zamaletdinov, R. (2020). Assessment of comparative abstractness: Quantitative approach. In CEUR Workshop Proceedings (pp. 132-144). Kazan.</mixed-citation></ref><ref id="B2"><label>2.</label><mixed-citation>Biber, D. (2006). University Language: A Corpus-Based Study of Spoken and Written Registers. 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