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News
June 3, 2026
Pocket Money, Personal Interest, and Family Practices: What Shapes Students Economic Literacy?
University students' economic literacy depends not only on their field of study but also on their interest in economics, the learning environment, and family financial practices. For example, students who received pocket money irregularly tend to perform better on economic literacy tests than their peers who received financial support on a regular basis. These findings come from a study conducted by HSE University involving more than 1,100 students from five Russian universities. The findings have been published in Cakrawala Pendidikan.
June 3, 2026
Creative Work as a Remedy for Burnout
The creative, supportive atmosphere and innovative methods at the Centre for Sociocultural Research make it appealing to early-career scholars. Over years of working at HSE University, they grow into researchers and lecturers recognised both in Russia and abroad. Chief Research Fellow Zarina Lepshokova and Leading Research Fellow Ekaterina Bushina spoke about their journey at the centre and at HSE, their research, and the role of mentors in their academic success.
June 2, 2026
HSE Study Reveals Imbalance in the Generative AI Market
Researchers at HSE University analysed how effectively the global generative artificial intelligence market converts investment into real revenue, concluding that AI is currently developing faster than it is paying off. The results have been published in the journal Foresight and STI Governance.

 

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Technology Classification for the Purposes of Future Studies

NRU Higher School of Economics , 2018. No. 78/STI/2018.
Kuzminov I., Meissner D., Lavrynenko A. S., E. Tochilina
The paper analyses problems associated with technologies classification for the purposes of futures studies, in order to ensure definitive inclusion of technologies in specific classes/types when conventional approaches to classification are applied. The evolution of classification approaches in the scope of science philosophy is shortly reviewed, together with the latest research on expert-based and computerised (algorithmic) classification and methodological dilemmas related to hierarchical aggregation of technological and production processes are analysed. Common problems with classifying technologies and industries frequently encountered in the age of converging technologies are examined, using the agricultural sector and related industries as an example. A case study of computerised classification of agricultural technologies based on clustering algorithms is presented, with a brief analysis of the potential and limitations of the methodology. For doing so a two-stage approach to classifying technologies is suggested, based on distinguishing between platform (multipurpose) and industry-specific technologies. An adaptive approach to analysing technological structures is proposed, based on many-to-many relationships and fuzzy logic principles.
Research target: Sociology (including Demography and Anthropology
Language: English
Full text
Text on another site
Keywords: форсайтнаучно-техническое развитиеклассификацииfuzzy logicнечеткая логикаtypologytext miningnetwork structuresclassificationtaggingFutures Studiesтэгированиеplanning of science and technology developmenttechnological structuresтехнологический Форсайтindustry structureтекст-майнинг
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