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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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Мобильность россиян в координатах жизненных шансов и рисков

Экономическая социология. 2022. Т. 23. № 1. С. 39–59.
Slobodenyuk E.

This paper focuses on the issues of social mobility and immobility of Russians in the neo-Weberian stratification hierarchy of Russian society, based on indicators of life chances. Social mobility is interpreted as a transition between three mass strata. Trajectories of mobility (rates and factors) are analyzed using the Russian Longitudinal Monitoring Survey (RLMS) panel data of a six-year interval from 2013 to 2018 and the group-based trajectory modeling (GBTM) method. It is shown that a quarter of Russians moved between strata. Mobility usually occurs over a short distance. Cases of sig- nificant life changes that would lead to transition between polar strata (low and high) are exceptions to the rule. The chances of getting into polar strata depend on the quality of human potential and, as a result, on individuals’ places in the system of industrial relations. Only highly qualified Russians with good health, who also originate from highly educated families, have high chances of getting into positively privileged (high) strata. For these Russians, composite rents work. Risks of moving down to low strata are present for Russians with low education, bad health and parents with low education, mainly due to employment in bad job positions that violate employees’ rights. The paper shows that social background continues to play a significant role in shaping chances of social wellbeing and mobility. It also draws attention to the fact that skills in use of information technology form a new basis for inequality between people.

Research target: Social Sciences
Language: Russian
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Text on another site
Keywords: социальная мобильностьсоциальное благополучиеsocial mobilityсоциальная стратификациясоциальные рискиsocial stratificationсоциальное неблагополучиеsocial well-beingжизненные шансыsocial riskslife chancesimmobilityиммобильность
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