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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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Роль просоциальной идентичности и предубеждений в готовности помогать пострадавшим от домашнего насилия

Социальная психология и общество. 2024. Т. 15. № 4. С. 207–225.
Ananyeva O. A., Prusova I.

Objective. Analysis of the relationships between prosocial identity, ambivalent prejudice, self-efficacy, and anger in intentions to participate in collective action to help women and men suffered from domestic violence. Theoretical framework of the current study was Dual Chamber Model of Collective Action (modification of Social Identity Model of Collective Action).

Background. Since the decriminalisation of domestic violence in Russia in 2017, researchers have noted various strategies to de-problematize domestic violence in Russian media, public opinion polls demonstrate the low willingness of Russians to help domestic violence victims. A study of predictors of willingness to participate in collective action to help domestic violence victims will help to clarify psychological mechanisms and barriers to the realisation of the prosocial potential of Russians, as well as develop recommendations for social campaigns aimed at helping violence victims.

Study design. The study examined the relationship between prosocial (politicized) identity (i.e. identification with helping groups), ambivalent prejudice towards women and men, self-efficacy to change a situation, anger and the intentions to participate in various forms of collective action to help women and men suffered from domestic violence. Direct and indirects associations were tested using partial least squares structural equation modelling (PLS-SEM).

Participants. Two Russian samples. N1 (intentions to help women) = 323 (54,8% females, 45,2% males) from 18 to 78 years old (M = 36,63; SD = 12,15), N2 (intentions to help men) = 267 (53,2% females, 46,8% males) from 18 to 64 years old (M = 35,46; SD = 10,32).

Measurements. Adapted to Russian scales of the in-group identification developed by C.Leach, the ambivalent sexism and ambivalence towards men inventories by P.Glick and S.Fiske, questions measuring self-efficacy to change situation, anger, and intentions to participate in various forms of collective action to help women and men suffered from domestic violence, adapted from European Social Survey.

Results. Prosocial identity makes a significant positive contribution to the intentions to help women and men suffered from DV, both directly and indirectly through self-efficacy (to help both women and men suffered from DV) and anger (to help men suffered from DV). Hostile sexism and benevolent attitudes (both towards women and men) directly undermine the willingness to engage in certain forms of prosocial collective action.

Conclusions. There are significant associations between prosocial identity, self-efficacy, anger towards the situation of victims, ambivalent prejudice and willingness to participate in various forms of collective action to help women and men suffered from domestic violence.

Research target: Psychology
Language: Russian
DOI
Text on another site
Keywords: идентичностьidentityпомогающее поведениеcollective actionдомашнее насилиеdomestic violenceangerefficacyамбивалентный сексизмhelping behaviourIntimate Partner ViolenceAmbivalent sexismambivalence towards menколлективная активностьамбивалентность по отношению к мужчинам
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