MONITORING AND ASSESSING REGIONAL LABOR MARKET DIFFERENTIATION IN THE RUSSIAN ARCTIC

. The Arctic is increasingly becoming a region of strategic importance. Due to its geopolitical and geoeconomic position, it holds significant interest for Russia. The sustainable development of the region depends directly on the effective functioning of its labor market. Territorial differentiation in the labor market is influenced by a variety of factors, including natural and climatic conditions, demographic trends, industrial and transport infrastructure, industry characteristics, and government policies favoring specific Russian regions. Amid labor market transformations—such as digitalization and economic sovereignty initiatives—combined with depopulation and migration outflows, there is a pressing need for monitoring, assessing, and analyzing the state of the labor market to support competitive regional functioning. The main objective of this study is the development and testing of a methodology for assessing regional labor market differentiation using data from regions that are fully or partially within the Russian Arctic. The research employs an integrated methodology, combining quantitative and qualitative approaches, to provide a comprehensive analysis of the issue. The scientific novelty lies in the creation of an algorithm for assessing regional labor market differentiation using multidimensional comparative analysis, index and integral methods, and expert evaluation techniques, as well as in introducing the concept of the indicator of variation in the level of regional labor market differentiation. The results position the regions of the Russian Arctic according to this indicator, offering a tool for informed management decisions in regional economic development and labor market monitoring. Future research will focus on examining sectoral labor market differentiation, expanding the set of indicators, testing the methodology across additional Arctic regions, and comparing results to identify territorial specificities and rank regions accordingly.