Open AccessLevel of Repression in Altai Regions between 1935 and 1937: An Attempt at Using Statistical and GIS Methods
Author(s) -
Е.М. Мишина
Publication year - 2021
Publication title -
izvestiâ uralʹskogo federalʹnogo universiteta. seriâ 2. gumanitarnye nauki/izvestiâ uralʹskogo federalʹnogo universiteta. seriâ 2, gumanitarnye nauki
Language(s) - English
Resource type - Journals
eISSN - 2587-6929
pISSN - 2227-2283
DOI - 10.15826/izv2.2021.23.3.047
Subject(s) - typology , lagging , geography , cluster (spacecraft) , economic geography , per capita , population , regional science , economic growth , demography , economics , statistics , sociology , mathematics , archaeology , computer science , programming language
This article focuses on the analysis of the impact of socio-economic development indicators of Altai region and Oyrot autonomous region on the eve of the Great Purge (1935 — first half of 1937) on the regional intensity of repression. Employing statistical methods (regression analysis), the author verifies the hypothesis that in the areas with the highest level of well-being of the population, the level of repression was also higher. It is established that the turnover and expenditures per capita compared with other economic indicators had the greatest influence on repression levels in Altai and Oyrotia regions. Based on the results of the analysis of regional statistics, the author of the article puts forward a theory that the thesis proclaimed by the Bolsheviks to justify the failure of economic development by the actions of the “enemies” in practice seems untenable, since economically lagging regions were characterised by a relatively low level of repression. In the second part of the article, the author presents a typology of districts of Altai and Oyrotia regions based on the results of cluster analysis of various groups of socio-economic development indicators. Additionally, she substantiates the hypothesis about the influence of the spatial factor on the intensity of repression: the groups of regions of each individual cluster consist mainly of adjacent regions.