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August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
August 12, 2026
‘I Would Like My Research to Help Make the World a Calmer and Better Place
Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
August 11, 2026
‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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Русскоязычная версия шкалы воспринимаемой девальвации и дискриминации (Perceived Devaluation and Discrimination Scale)

Психиатрия. 2025. Т. 23. № 3. С. 67–74.
Zolotareva A.

Background: the Perceived Devaluation and Discrimination Scale (PDDS) is an important instrument for diagnosing stigmatization in the practice of clinicians and researchers. This study was aimed to adapt the Russian version of the PDDS. Participants and Methods: a total of 1,303 volunteers completed the PDDS and the Mental Health Knowledge Questionnaire (MHKQ). Results: psychometric analysis of the adapted instrument confirms its discriminativeness, reliability and validity. Discrimination has been proven by adequate discrimination indexes. Internal reliability ensures adequate McDonald’s ω coefficient (ω = 0.752). Factor validity was determined by identifying the bifactor structure of an adapted instrument. Convergent validity was confirmed by negative correlations between stigmatization and mental health knowledge. Conclusion: the Russian version of the Perceived Devaluation and Discrimination Scale (PDDS) is psychometrically justified. The prospects of psychometric analysis of the Russian version of the PDS are reduced to its validation in persons with mental disorders and modification for the diagnosis of stigmatization of patients with somatic diseases.

Research target: Psychology
Language: Russian
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Keywords: дискриминацияdiscriminationдевальвациястигматизацияstigmatizationпсихометрический анализdevaluation psychometric properties
Publication based on the results of:
Развитие психосоматических исследований в России (2025)
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