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September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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The future of agricultural cooperatives in Russia: Does theory matter?

Russian Peasant Studies. 2024. Vol. 9. No. 4. P. 6–20.
Yanbykh R., Lerman Z.

The article aims at identifying theoretical and practical reasons for the failure of the agricultural cooperation development in Russia. Authors suggest that rural cooperatives in Russia do not develop due to the general features of the formation of social capital in the Russian countryside, the lack of necessary institutional conditions, and the wrong idea that cooperatives based on the classical principles of cooperation can operate successfully in the contemporary economy and society. The first theoretical barrier to cooperation is that in the contemporary high-technology agriculture, hybrid structures (cooperatives) are less efficient than the hierarchical one used by agroholdings. The second theoretical barrier is the inconsistency of seven classical principles of cooperation formulated at the time of Raiffeisen (i.e. outdated) with today’s economic realities and their transformations. The third practical barrier is the rapid degradation of rural areas and the low level of trust and interaction between members of agricultural cooperatives, which is why there are no trends of the bottom-up development of cooperation. The authors conclude that a high level of social capital is the necessary condition for cooperation: at the formation stage, this level is high due to interpersonal relationships developed from the informal social interactions of its members and a high level of trust among members and between members and management, but cooperatives start to lose their social capital as they enlarge — the sense of community, trust and mutual assistance disappears, the atmosphere becomes more business-oriented.

Research target: Economics and Management Sociology (including Demography and Anthropology
Language: English
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Keywords: социальный капиталsocial capitalсельскохозяйственные кооперативыagricultural cooperatives Russia Россия
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