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September 25, 2026
AI Users Earn Up to 41.8% More Than Non-Users
Research conducted by economists at HSE University has revealed a significant correlation between the regular use of GenAI in the workplace and higher pay among Russian employees. The study found that individuals who frequently use GenAI in their professional activities earn notably more than those who reject these new tools or resort to them occasionally. The salary premium for highly qualified specialists reaches 41.8%. The article was published in the Voprosy Ekonomiki journal.
September 24, 2026
‘Feedback and Constructive Criticism Are Essential in Our Profession
Vincent Fardeau, Associate Professor at HSE ICEF, has reached a major career milestone: he recently published his paper ‘Asymmetric Thin Markets’ in the Journal of Financial Economics, successfully passed his major academic review, and received tenure. In this interview, Vincent discusses the story behind the paper, explains the concept of asymmetric thin markets, and shares his advice for young scholars aiming to publish in top-tier journals.
September 22, 2026
Personal Interest in Doctoral Thesis Topic Most Important for Confidence in Successful Defence
A researcher at HSE University analysed data on 1,539 doctoral students from 161 Russian universities to identify which features of a thesis topic are associated with academic success and engagement. The most important factor was found to be personal interest in the research topic, which was associated with almost all key aspects of doctoral programme experience—from engaging with the academic supervisor to research activity and confidence about successfully defending the thesis. The findings have been published in Higher Education.

 

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Network psychometric-based identification and structural analysis of a set of evolved human motives

Personality and Individual Differences. 2025. Vol. 233. Article 112921.
Aunger R., Gallyamova A., Grigoryev D.

Establishing a limited set of motives characteristic of the human species has been a goal in psychology since the beginning of the discipline. This paper uses a network-based analysis of previously published psychometric data to establish the existence of a pre-defined set of human motives. The set was derived by using evolutionary theory to identify what sorts of goals humans need to achieve to survive and reproduce in the niche our species evolved to fill. The analysis reported here is based on responses obtained from an on-line sample of 510 representative residents of the United Kingdom to 150 items. Analysis shows that all fifteen of the identified motives can be isolated, that they show expected relationships to one another (based on common functionality), and that differences in attentiveness to motives by gender reflect traditional gender-based role-play during human evolution, while differences by age are consistent with expectations from life history theory. The reduced set of 45 items identified by a genetic algorithm-based analysis could form the basis of a psychometric scale. Knowing the set of motives behind goal-directed behavior should prove a significant boon to a wide variety of psychological applications, including human relations, educational strategies, marketing and behavior change.

Research target: Psychology Social Sciences
Language: English
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Keywords: motivationindividual differences evolutionary psychologyhuman motivesnetwork psychometricslife history theoryhuman behavioural ecology
Publication based on the results of:
Адаптивные основы культуры: к пониманию культурных ориентаций через призму компромиссов истории жизни (2024)
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