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<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.4 20241031//EN" "https://jats.nlm.nih.gov/archiving/1.4/JATS-archive-oasis-article1-4-mathml3.dtd">
<article xmlns:ali="http://www.niso.org/schemas/ali/1.0/" 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" article-type="research-article" xml:lang="ru"><front><journal-meta><issn publication-format="print">2411-1406</issn><issn publication-format="electronic">2411-1406</issn></journal-meta><article-meta><article-id pub-id-type="doi">10.17059/ekon.reg.2025-3-22</article-id><title-group xml:lang="en"><article-title>Traditional and Emerging Chinese Migration in the Labour Market  of Sverdlovsk Oblast (Russia): A Quantitative and Qualitative Analysis</article-title></title-group><title-group xml:lang="ru"><article-title>«Традиционная» и «новая» миграция из Китая на региональном рынке труда: количественный и качественный анализ</article-title></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-7420-7499</contrib-id><name-alternatives><name xml:lang="en"><surname>Bedrina</surname><given-names>Elena B. </given-names></name><name xml:lang="ru"><surname>Бедрина</surname><given-names>Елена Борисовна </given-names></name></name-alternatives><email>bedrina.eb@uiec.ru</email><xref ref-type="aff" rid="aff1"/><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Alay </surname><given-names>Yerlan  </given-names></name><name xml:lang="ru"><surname>Алаи</surname><given-names>Ерлань </given-names></name></name-alternatives><email>Aray.yerlan@inbox.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0448-3519</contrib-id><name-alternatives><name xml:lang="en"><surname>Kozlova </surname><given-names>Olga A. </given-names></name><name xml:lang="ru"><surname>Козлова</surname><given-names>Ольга Анатольевна</given-names></name></name-alternatives><email>kozlova.oa@uiec.ru</email><xref ref-type="aff" rid="aff2"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Ural Federal University named after the first President of Russia B. N. Yeltsin</institution></aff><aff><institution xml:lang="ru">Уральский федеральный университет имени первого Президента России Б. Н. Ельцина</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">Institute of Economics of the Ural Branch of RAS</institution></aff><aff><institution xml:lang="ru">Институт экономики УрО РАН</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2025-06-27" publication-format="electronic"/><volume>21</volume><issue>3</issue><fpage>886</fpage><lpage>901</lpage><history><date date-type="received" iso-8601-date="2025-01-30"/><date date-type="accepted" iso-8601-date="2025-03-19"/></history><permissions><copyright-statement xml:lang="ru">Copyright © 2025  </copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru"> </copyright-holder><ali:free_to_read/><license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/"><ali:license_ref>https://creativecommons.org/licenses/by/4.0/</ali:license_ref></license></permissions><self-uri content-type="html" mimetype="text/html" xlink:title="article webpage" xlink:href="https://www.economyofregions.org/ojs/index.php/er/article/view/1145">https://www.economyofregions.org/ojs/index.php/er/article/view/1145</self-uri><self-uri content-type="pdf" mimetype="application/pdf" xlink:title="article pdf" xlink:href="https://www.economyofregions.org/ojs/index.php/er/article/download/1145/470">https://www.economyofregions.org/ojs/index.php/er/article/download/1145/470</self-uri><abstract xml:lang="en"><p>The expanding cultural and economic ties between Russia and China have increased the influx of Chinese labour migrants into various Russian regions, including Sverdlovsk Oblast. Recently, this region has seen growing migration flows from northeastern Chinese provinces. This study aims to identify the employment characteristics and adaptation strategies of Chinese migrants in the labour market, focusing on Yekaterinburg—the city with the largest number of migrants from distant foreign countries. The methodology combines empirical data from official sources with insights from semi-structured interviews conducted in Chinese among migrants who arrived in September–October 2024 and January 2025. Findings highlight the university’s dual role: as an educational institution training highly skilled personnel and as an employer facilitating migrant adaptation through modern, intellectual employment opportunities. The research distinguishes between two types of Chinese labour migration: “traditional,” consisting primarily of low- and medium-skilled workers concentrated around the urban clothing market, and “new,” composed of young Chinese migrants pursuing or having completed education at Russian universities while actively participating in the labour market. The study identified two main adaptation patterns: “traditional” migrants generally experience segregation, whereas “new” migrants are more inclined toward integration. Both groups demonstrate high adaptive capacity and exhibit entrepreneurial characteristics. These results contribute to a deeper understanding of Chinese migration and may support further development of Russia-China cooperation.</p></abstract><abstract xml:lang="ru"><p>Рост культурно-экономических отношений между Россией и Китаем способствует привлечению китайских трудовых мигрантов в российские регионы. Одним из таких регионов является Свердловская область, в последние годы аккумулирующая миграционные потоки из северо-восточных провинций Китая. Цель исследования состоит в выявлении изменений в адаптационных стратегиях китайских мигрантов на региональном рынке труда на примере г. Екатеринбурга Свердловской области, для которой китайская миграция наиболее многочисленна среди миграции из дальнего зарубежья. Методы исследования основываются на сборе и анализе статистических и эмпирических данных, полученных из официальных источников и дополненных результатами полуструктурированных интервью, проводившихся на китайском языке среди мигрантов в сентябре-октябре 2024 г. и январе 2025 г. Исследование выявило возрастание роли в адаптации китайских мигрантов, с одной стороны, университета как образовательной площадки по подготовке высококвалифицированных кадров и как работодателя, с другой — гибких форм занятости, связанных с интеллектуальным трудом. В ходе исследования определилось разделение современной китайской миграции на «традиционную», формирующуюся преимущественно вокруг вещевого рынка из низко- и среднеквалифицированных трудовых мигрантов и «новую», представленную молодыми китайцами, получившими или продолжающими получать образование в российских вузах, и одновременно являющихся участниками рынка труда. Выделены две основные адаптационные стратегии поведения китайских мигрантов в принимающем сообществе — сегрегация у «традиционных» мигрантов и интеграция — у «новых». Сделан вывод о предпринимательском характере китайской миграции и достаточно высокой адаптационной способности как «традиционных», так и «новых» мигрантов. Полученные результаты вносят вклад в изучение китайской миграции и могут способствовать укреплению сотрудничества между Россией и Китаем.</p></abstract><kwd-group xml:lang="en"><kwd>labour market</kwd><kwd>Chinese labour migrants</kwd><kwd>migrant employment</kwd><kwd>new Chinese migration</kwd><kwd>migrant adaptation strategies</kwd><kwd>Sverdlovsk Oblast</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>рынок труда</kwd><kwd>китайские трудовые мигранты</kwd><kwd>занятость мигрантов</kwd><kwd>новая китайская миграция</kwd><kwd>стратегии адаптации мигрантов</kwd><kwd>Свердловская область</kwd></kwd-group></article-meta></front><body/><back><ack xml:lang="en"><p>This article was prepared as part of the state assignment to the Institute of Economics, Ural Branch of the Russian Academy of Sciences, for 2024–2026 (No. 0327–2024-0009) titled “Mechanisms for Regulating the Economic Behavior of the Population in the Context of Structural Changes.”</p></ack><ack xml:lang="ru"><p>Статья подготовлена в соответствии с планом НИР по гос. заданию Института экономики УрО РАН на 2024–2026 гг. № 0327–2024-0009 «Механизмы регулирования экономического поведения населения в условиях структурных изменений».</p></ack><ref-list><ref id="ref1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Авдашкин, А. 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