The article is devoted to the visualization of the image of a Chinese in the periodical press of the Urals in the 1950s. Using the methodology of critical discourse analysis, the authors identify several target groups that form the image, describe their characteristic features and highlight the general and the special characteristics. The source base was made up of materials from the Ural periodical press. During “Great friendship” the Chinese who took part in labor training at enterprises and universities in the USSR became an object of attention of the Ural periodical press from the moment of their appearance in the region in 1954 and up to the almost complete return to their homeland. Periodical publications formed and broadcast to readers a positive image of the Chinese, using some lasting methods of description: putting in an industrial environment, displaying a certain hierarchy in the relationship “diligent” student – “wise” mentor, ‘humanizing’ the character, describing a “typical” and “correct” biography showing positive changes in China after its transition to the socialist path of development.
In the article, the author examines documents from the State Archive of the Russian Federation, United State Archive of the Chelyabinsk Region, State Archive of the Perm Krai, and State Archive of the Sverdlovsk Region concerning migration from China to the Urals in the 20th-21st centuries. This chronological period covers the main milestones of the Chinese stay in Russia, and in the Urals on particular. In order to conduct historical research on the topic of Chinese migration within the territorial framework of the Urals, it is necessary to generalize these sources, to assess their potential and cognitive limitations. The most significant array of archival documents dates back to the early 20th century. It was during the First World War that severe labor shortage forced Russian officials to approve engaging workers from China to fulfill a large-scale defense order. Thus, a rather voluminous layer of documentation for 1915–17 was formed at the local level, characterizing the practice of recruiting the Chinese to the Ural factories, mines, and logging, the features of their life, and specifics of their social organization. Working with these documents allows the researcher to get a full picture of placement and use of the “yellow” labour in the Urals before the revolution. The available archival files indicate that the efficiency of the Chinese often left much to be desired, but their large numbers, low cost of transportation and maintenance were an undoubted advantage. Some archival fonds of the Soviet authorities give an idea of the socio-demographic composition of the Chinese who remained to live in the USSR in the 1920s-1930s. The next voluminous collection of documents on the topic was formed during the years of the Soviet-Chinese friendship in the 1950s. During these years, the Chinese took a significant part in the construction of industrial enterprises and infrastructure facilities. In the Urals, the Chinese concentrated mainly on the construction of the Molotovstroy facilities. The last layer of archival data dates back to the post-Soviet period and does not seem as informative as the fonds deposited in the late imperial and Soviet periods. To date, relatively few sources have been found in the archives to characterize the migration from the PRC to Russia after the collapse of the USSR. The most reliable data from archival documents permit to trace the number of the Chinese labor migrants in Russia in the first two decades of the 21st century and to establish the main areas of their concentration in the Urals and other regions of the country.
After the collapse of the USSR, the contours of the new state borders crossed the areas of settlement of ethnic groups, making the issue of the nature of the frontier actual. In the Russian-Kazakh sector, this was clearly manifested in the discrepancy between the areas of settlement of the Russian-speaking population and the very line of the state border. The challenges generated by the Kazakhization policy and the difficulties of post-socialist transit stimulated the outflow of the population from the northern regions of Kazakhstan to Russia. The purpose of the article is to reconstruct the migration of the Russian-speaking population in the Russian-Kazakh border area using the example of the South Urals. The source database was made up of archival documents, information from the regional statistics committee on migration, and materials from interviews with Russian-speaking migrants from Kazakhstan. The basis of Central Asian migration to the region was the Russian-speaking population of the border regions of Kazakhstan (Russians, Tatars, Ukrainians, Germans). Two waves of migration stand out clearly: “forced” in the 1990s., and more “pragmatic” in 2000-2019 allowed to significantly compensate for the demographic losses, contributed to the influx of a young and economically active population into the region. The main areas of their exodus were Kostanay and Rudny (Kostanay region). The developed practices of cross-border cooperation and the presence of previously established communities allowed the newcomers to maintain strong ties with their “homeland”, to facilitate the recruitment of new migrants. In the course of the study, the author identified the quantitative and qualitative parameters of migration from Kazakhstan, and determined the role of the frontier in the migration processes to the South Urals.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.