The article explores the role of ideology in Russian economic education, focusing on the preanalytic cognitive acts (ideal types of ideologies) used by researchers and lecturers in developing educational programs, courses, and textbooks for students. The empirical basis of the study comprises theoretical narratives derived from 35 in-depth interviews and three focus groups with representatives of Russian economic science and education, as well as an analysis of 25 university-level economics textbooks, which were divided into 1942 textual documents. Narrative analysis revealed that the majority of economic researchers and lecturers recognize the presence of ideology in economic education. The respondents noted the close connection between economic education and ideology, emphasizing that educators act as transmitters of ideological contexts through the conveying tacit knowledge. A quantitative analysis of Russian economics textbooks published between 2002 and 2025 indicated the presence of ideological components and value judgments in Russian economic education. These textbooks do not serve as neutral transmitters of knowledge, but rather contribute to the formation of preanalytic cognitive acts, or mental models, that carry an ideological bias. The analysis showed that these textbooks exhibit ideological hybridity, in which the neoliberal paradigm coexists with dirigiste assumptions, socialist ideas, a search for the "special path", and environmental preservation. This creates an eclectic hybridity within the educational space, leading to a fragmented and incorrect understanding of economic reality among students. The paper emphasizes the importance of shaping a constructive multidimensionality of economic education, which aims to foster critical thinking and provide students with a multifaceted understanding of economic processes and phenomena.
The article considers the theoretical basis of the impact of the process of widespread dissemination of artificial intelligence technology on the evolutionary development of the institution of entrepreneurship and the institutional environment surrounding it. The relevance of the present study is determined by the rapid expansion of the application of artificial intelligence in practical economic activity and the related change in the surrounding conditions of entrepreneurial activity. The purpose of the study is to identify and describe the theory of functioning of the mechanism of mutual influence between technological development and the institutional transformation of entrepreneurship. The theoretical basis of the study includes the provisions of institutional economics, the concept of the evolution of institutions, the Schumpeterian approach to the analysis of entrepreneurship and innovation, the theory of transaction costs, the theory of increasing returns, the concept of adaptive rationality, and some other theories. Artificial intelligence is considered in the study as a technological factor, as a separate institution, and as part of the institutional environment. As a result, theoretical approaches suitable for describing the process of the impact of the implementation of artificial intelligence on entrepreneurship were collected and described, and their selection was substantiated. The mechanism of the influence of artificial intelligence on the evolution of institutions is described, where the implementation of the technology transforms existing entrepreneurial practices, creating prerequisites for the subsequent transformation of other institutions. It is noted that institutional changes associated with the development of artificial intelligence are more appropriately analyzed dynamically, while also considering the trajectory of institutional development and path dependence, differences in the degree of adaptability of economic agents, and other features of the processes of institutional change consolidation.
The rapid development of artificial intelligence (AI) technologies is transforming the global economy; however, its impact on social stratification remains a subject of intense debate. Based on panel data for 100 countries over the 2000– 2024 period, a fixed-effects model is employed to estimate the impact of accumulated AI innovation potential (measured by the number of patents) on the Gini index and percentile wealth shares. Empirical results demonstrate that AI adoption does not have a statistically significant effect on the Gini index, yet it drives a substantial concentration of wealth at the top of the distribution, increasing the shares of the top 10% and 1% of the population. The study reveals that the quality of the institutional environment and regulation acts as a significant moderator: effective government policy is capable of mitigating negative distributional shocks and curbing the disproportionate enrichment of technological elites. It is concluded that the market diffusion of AI objectively leads to an increase in extreme inequality, whereas a well-designed institutional policy allows for the redirection of technological dividends to the benefit of broader segments of society.
This article examines the expansion of Chinese pharmaceutical companies into the US domestic market, as well as the protective policies of US regulators. The phenomenon of "technological colonialism" has ceased to be exclusively confined to Western countries in recent years. China, India, and some other developing countries have formed effective international supply chains in a number of industries, including biopharmaceuticals, capable of dominating and displacing companies from developed countries, including from their domestic markets. Technological colonialism is still primarily viewed as "digital" or "data colonialism," but Chinese multinationals are pursuing this technological policy in key areas of the real economy, including pharmaceuticals. An analytical analysis of the dominance of Chinese pharmaceutical companies in the US market is presented. The main protective regulatory measures to ensure US pharmaceutical sovereignty are examined.
The problem of post-exploitation development of mining territories is significant for resource-oriented regional economies. In Russia, the closure of mining enterprises that are city-forming can lead to the creation of socio-economic problems and significant budget expenditures to address them. This is due to the fact that existing approaches aimed at supporting and financing such territories are reactive in nature and do not provide preventive protection tools. The aim of the study is a comparative assessment of the economic efficiency of the traditional budget support model and the proposed preventive model created on the basis of the target Fund for the Development of Resource Territories (RDRT). The study is based on modeling the formation of RDRT according to a scenario of annual deductions in the amount of 1% of the revenue of city-forming mining enterprises. The empirical base consisted of data from three single-industry settlements in Khabarovsk Region with different types of resource specialization (coal, tin, gold) for the period 2015–2025. The research methodology includes a retrospective analysis of demographic and production dynamics, calculation of territorial budget balances, and scenario modeling of fund accumulations. The study established that the preventive support model is superior to the reactive one for the selected types of territories. The scientific novelty of the study lies in the quantitative substantiation of a universal deduction rule as an effective tool for risk mitigation and the transition of territories to financial stability.
