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September 15, 2026
Immunity to Chaos: How Personal Resources Help Us Cope with the Challenges of a Turbulent World
International conflicts, crises and digital overload—the modern world puts our minds to the test every day. Traditional psychology often focuses on the consequences: anxiety, depression, and psychosomatic disorders. But what if we looked at the problem differently—through the lens of the resources that prevent us from breaking down? Psychological immunity is precisely this set of resources. Alena Zolotareva and her group, Psychological Immunity as a Resource for Positive Functioning, are developing an integrative model of this phenomenon, adapting diagnostic tools and preparing for large-scale empirical research. Why do psychologists need to collaborate with medical professionals, and how could their research transform preventive care in clinics and corporations?
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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.

 

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Анализ технической эффективности российских предприятий розничной торговли в 2019–2023 гг.

Прикладная эконометрика. 2026. Т. 82. № 2. С. 26–46.
Besstremyannaya G., Кузнецова Ю.

This paper studies the technical efficiency of Russian retail companies in 2019 to 2023 using  stochastic frontier analysis (SFA) with the Battese and Coelli (1995) model. A translogarithmic production function is employed for estimations. The dependent variable is company revenue, and the production factors are the average number of employees, fixed assets, and assets less fixed assets, along with year-specific dummies. The mean distribution of the inefficiency component is modeled as a function of company age, total assets, and the regional Herfindahl–Hirschman index, calculated using a sample from the SPARK database.

The results of our analysis show that labor makes the largest contribution to revenue growth, with increasing returns to scale, albeit close to constant. Revenue increased annually throughout the period under study. Average technical efficiency in the industry exhibits an inverted-U-shaped relationship with firm age and size. Technical efficiency declined significantly during the pandemic but showed steady growth in subsequent years.

Research target: Economics and Management
Language: Russian
DOI
Text on another site
Keywords: анализ эффективностиefficiency analysisstochastic frontier analysisанализ стохастической границы
Publication based on the results of:
Current Issues of Macroeconomic Dynamics and Macroeconomic Policy in Russia (2025)
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