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<article article-type="research-article" dtd-version="1.2" xml:lang="ru" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><front><journal-meta><journal-id journal-id-type="issn">2313-8912</journal-id><journal-title-group><journal-title>Research Result. Theoretical and Applied Linguistics</journal-title></journal-title-group><issn pub-type="epub">2313-8912</issn></journal-meta><article-meta><article-id pub-id-type="doi">10.18413/2313-8912-2025-11-3-0-4</article-id><article-id pub-id-type="publisher-id">3878</article-id><article-categories><subj-group subj-group-type="heading"><subject>APPLIED LINGUISTICS</subject></subj-group></article-categories><title-group><article-title>&lt;strong&gt;Cultural code in academic discourse: corpus and parametric approaches&lt;/strong&gt;</article-title><trans-title-group xml:lang="en"><trans-title>&lt;strong&gt;Cultural code in academic discourse: corpus and parametric approaches&lt;/strong&gt;</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Dontsov</surname><given-names>Maksim A.</given-names></name><name xml:lang="en"><surname>Dontsov</surname><given-names>Maksim A.</given-names></name></name-alternatives><email>maksimdontzoff@yandex.ru</email><xref ref-type="aff" rid="aff1" /></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Solnyshkina</surname><given-names>Marina I.</given-names></name><name xml:lang="en"><surname>Solnyshkina</surname><given-names>Marina I.</given-names></name></name-alternatives><email>mesoln@yandex.ru</email><xref ref-type="aff" rid="aff2" /></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Shelestova</surname><given-names>Olga V.</given-names></name><name xml:lang="en"><surname>Shelestova</surname><given-names>Olga V.</given-names></name></name-alternatives><email>olgashelest2015@yandex.ru</email><xref ref-type="aff" rid="aff3" /></contrib></contrib-group><aff id="aff2"><institution>Kazan Federal University, Russia</institution></aff><aff id="aff1"><institution>Federal State Budgetary Educational Institution of Higher Education “Kazan State Institute of Culture”, Kazan, Russia.</institution></aff><aff id="aff3"><institution>Казанский (Приволжский) федеральный университет, Казань, Россия</institution></aff><pub-date pub-type="epub"><year>2025</year></pub-date><volume>11</volume><issue>3</issue><fpage>0</fpage><lpage>0</lpage><self-uri content-type="pdf" xlink:href="/media/linguistics/2025/3/Лингвистика_11_3-64-85.pdf" /><abstract xml:lang="ru"><p>The study presents a corpus and parametric analysis of 785 nominations of Russian cultural code referents in academic discourse. The dataset amounting 1.5 mln. tokens comprises a collection of 30 textbooks used in the 5th - 9th grades of general secondary schools in Russia to teach Russian, Literature and History. The nominations of cultural code referents were sourced from validated linguistic, cultural and sociological studies, and were classified into thirteen thematic groups, including: &amp;nbsp;History, State and Social Structures, Literature, Geography, Religion, Traditional Life, Nature, Science, Russian Language, Art, Proverbs and Sayings, Calendar and Holidays, Units of Measurement. The research revealed systematicity and thematic homogeneity of the cultural code nominations employed in the textbooks: the most representative in each of the grade collections are the following thematic groups: &amp;quot;History&amp;quot;, &amp;quot;Art&amp;quot;, &amp;quot;Literature&amp;quot; and &amp;quot;Geography (space)&amp;quot;. The share of nominations of Russian cultural code referents in textbooks varies from 1.8%&amp;nbsp; to 5.04% (in tokens): the smallest number of instances is registered in the textbooks of Russian, the highest &amp;ndash; in Literature textbooks. The frequency of Russian cultural code referents nomination increases across grades predominantly due to the growth in groups &amp;quot;History&amp;quot;, &amp;quot;Literature&amp;quot;, and &amp;quot;State structures&amp;quot;. The revealed empirical data and ranges of the NRCC frequency can be used to improve algorithms for automated assessment of the language of educational texts and modeling linguistic worldview in texts of various genres.</p></abstract><trans-abstract xml:lang="en"><p>The study presents a corpus and parametric analysis of 785 nominations of Russian cultural code referents in academic discourse. The dataset amounting 1.5 mln. tokens comprises a collection of 30 textbooks used in the 5th - 9th grades of general secondary schools in Russia to teach Russian, Literature and History. The nominations of cultural code referents were sourced from validated linguistic, cultural and sociological studies, and were classified into thirteen thematic groups, including: &amp;nbsp;History, State and Social Structures, Literature, Geography, Religion, Traditional Life, Nature, Science, Russian Language, Art, Proverbs and Sayings, Calendar and Holidays, Units of Measurement. The research revealed systematicity and thematic homogeneity of the cultural code nominations employed in the textbooks: the most representative in each of the grade collections are the following thematic groups: &amp;quot;History&amp;quot;, &amp;quot;Art&amp;quot;, &amp;quot;Literature&amp;quot; and &amp;quot;Geography (space)&amp;quot;. The share of nominations of Russian cultural code referents in textbooks varies from 1.8%&amp;nbsp; to 5.04% (in tokens): the smallest number of instances is registered in the textbooks of Russian, the highest &amp;ndash; in Literature textbooks. The frequency of Russian cultural code referents nomination increases across grades predominantly due to the growth in groups &amp;quot;History&amp;quot;, &amp;quot;Literature&amp;quot;, and &amp;quot;State structures&amp;quot;. The revealed empirical data and ranges of the NRCC frequency can be used to improve algorithms for automated assessment of the language of educational texts and modeling linguistic worldview in texts of various genres.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>Cultural code</kwd><kwd>Academic discourse</kwd><kwd>Corpus and Parametric approaches</kwd><kwd>Consistency</kwd><kwd>Homogeneity</kwd><kwd>Frequency</kwd></kwd-group><kwd-group xml:lang="en"><kwd>Cultural code</kwd><kwd>Academic discourse</kwd><kwd>Corpus and Parametric approaches</kwd><kwd>Consistency</kwd><kwd>Homogeneity</kwd><kwd>Frequency</kwd></kwd-group></article-meta></front><back><ack><p>The research was supported by the RSF grant 24-28-01355 &amp;quot;Genre-discourse characteristics of the text as a function of lexical range&amp;quot;.</p></ack><ref-list><title>Список литературы</title><ref id="B1"><mixed-citation>Andreeva,&amp;nbsp;M.&amp;nbsp;I., Solnyshkina,&amp;nbsp;M.&amp;nbsp;I. and Mufazalova,&amp;nbsp;N.&amp;nbsp;I. 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