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News
May 13, 2026
Immersion in Second Language Environment Influences Bilinguals Perception of Emotions
Researchers at the Cognitive Health and Intelligence Centre at the HSE Institute for Cognitive Neuroscience have discovered how bilingual individuals process emotional words in their native (first) and non-native (second) languages. It was found that the link between word meaning and bodily sensations is weaker in a second language than in a first language. However, the more a person is immersed in a language environment, the smaller this difference becomes. The article has been published in Language, Cognition and Neuroscience.
May 12, 2026
‘Any Real-Economy Company Can Use Our Products
The HSE Centre for Financial Research and Data Analytics combines fundamental and applied work, including in areas unique to Russia such as the connection between sentiment in the media and social networks and financial markets. The HSE News Service spoke with the centre’s director, Professor Tamara Teplova, about its work.
May 7, 2026
Researchers Find More Effective Approach to Revealing Majorana Zero Modes in Superconductors
An international team of researchers, including physicists from HSE MIEM, has demonstrated that nonmagnetic impurities can help more accurately reveal Majorana zero modes—quantum states considered promising building blocks for quantum computing. The researchers found that these impurities shift the energy levels that typically obscure the Majorana signal, while leaving the mode itself largely unaffected, thereby making its spectral peak more distinct. The study has been published in Research.

 

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?

Семейные паттерны (не)занятости

С. 326–365.
Lukyanova A.

The paper studies the evolution of individual- and household-based non-employment rates in Russia using data from the RLMS HSE for 1994–2016. Following [Gregg and Wadsworth, 2008], I estimate disparities between individual- and household-level measures and compare actual household workless rates with counterfactuals based on a random distribution of work. I find that the Russian labor market is characterized by a low, albeit growing, rate of household joblessness: about 6% of the working-age population live in households where no other adults work. Inequality in the distribution of work is also low and declining. Generally, work is distributed equally among households and in some years more (!) equally than if it were distributed randomly. Equality is achieved primarily due to very high employment rates among two-adult households. Conditioning on characteristics, we distinguish several types of households that face “excessive” non-employment, i.e. for these types of households actual non-employment rate is higher than the counterfactual prediction based on their socio-demographic characteristics. These are households without university graduates, couples without children in which one of the spouses is above official retirement age, working-age couples living with adult children, and working-age single adults without children. The paper assesses various underlying driving factors for the dynamics of household nonemployment. The decomposition results reveal that there are a number of factors at play. Demographic shifts – reduction of average household size and expanding share of single-adult households – were identified as the main driver of growing household joblessness. Labour market factors – changes in individual employment rates, especially deterioration of permanent jobs – also exerted a sizable effect. These trends were partly offset by improvements in the distribution of work among households.

Language: Russian
Text on another site
Keywords: поляризацияinequalityнеравенстводекомпозицияdecompositionнезанятостьjob polarizationdistribution of workfamily labor supplyраспределение занятостисемейное предложение труда joblessness

In book

Российский рынок труда через призму демографии
Российский рынок труда через призму демографии
Sharunina A., Chernina E., Travkin P., Oshchepkov A. Y., Lukyanova A., Zudina A. A., Денисова И. А., Vishnevskaya N., Kapeliushnikov R., Gimpelson V. E. М.: Издательский дом НИУ ВШЭ, 2020.
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