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News
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.
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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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Building New Markets: A Comparison between Russian and American Credit Card Markets

Socio-Economic Review. 2005. Т. 3. С. 437–466.
Guseva Alya

Based, in part, on original fieldwork in Moscow, Russia, in 1998, 1999 and 2004, this paper focuses on two markets at their conception points-the American credit card market of the late 1950s and 1960s and the Russian credit card market of the 1990s. Emerging credit card markets need to solve two problems: the problem of uncertainty inherent in lending and the complementarity problem of simultaneously attracting merchants and cardholders. American banks jump-started the market by mailing unsolicited cards to thousands of unsuspecting and unscreened individuals. This resulted in staggering losses, but helped to attract merchants. American banks eventually solved the uncertainty problem through formal institutional means: they shared account information with third parties (credit bureaus) and based pre-screening on the calculation of risk, which made bank-customer relationships completely impersonal. The dominant way to disseminate cards in Russia is through payroll agreements with enterprises, whereby the employees are issued cards secured by their salaries directly deposited to the bank. Not only does the rapid increase of cardholders attract merchants, but payroll projects also solve the uncertainty problem through two-stage embeddedness: banks rely on employing organizations to mediate their relations with cardholders. As a result of dissimilar solutions to the uncertainty and complementarity problems, the structures of Russian and American credit card markets differ as well. 

Research target: Sociology (including Demography and Anthropology Economics and Management
Language: Russian
Text on another site
Keywords: uncertaintycredit cardsNew markets
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