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  • Представления о лояльности населения престолу и особенности верноподданнической риторики в жандармских донесениях 1820-1830-х годов (по материалам 2-го округа Корпуса жандармов)
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May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Представления о лояльности населения престолу и особенности верноподданнической риторики в жандармских донесениях 1820-1830-х годов (по материалам 2-го округа Корпуса жандармов)

Вестник Томского государственного университета. История. 2025. № 94. С. 38–47.
Ivanova M.

This article is devoted to the reconstruction of the gendarme officers’ collective perceptions about the Russian Empire’s territory on the materials about the 2nd gendarme district. The study examined the records of the high police, which reflected the gendarme officers’ ideas about the people’s political loyalty and loyalist sentiments. The study is based on archival documents from the funds of the State Archive of the Russian Federation (GA RF), as well as published sources. The author suggests that during this period the gendarmerie officers’ collective ideas about the 2nd gendarme district were stable and this territory was perceived as a completely loyal region. An analysis of the gendarmerie reports’ rhetoric revealed several stable emotional categories (positive and negative), which were perceived by the III Department as a manifestation of the population’s loyalty to the throne. Positive emotions were expressed through the words: joy, delight, jubilation, tenderness, and while negative emotions through such words as: despondency, grief and sadness. Both emotional categories were also accompanied by tears of joy and grief. In addition, the documents clearly articulate the connection between the manifestation of certain emotions and confirmation of loyalty to the throne. It might be assumed that within the framework of this “emotional regime” there was no room for silence. In other words, events directly connected with the monarch figure invariably required a certain emotional background. The evaluative categories for the emotional narrative used, as well as a certain metaphorical nature of the language, are characteristic features of these gendarme reports. There were characterized by an indication of the degree of reliability, as well as generalization and extrapolation of ideas about loyalty to the broad masses of the Russian population.

Research target: Humanities History and Archeology
Language: Russian
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DOI
Text on another site
Keywords: лояльностьcollective representationsloyaltyhistory of emotionsистория эмоцийколлективные представлениякорпус жандармовCentral RussiaЦентральная РоссияCorps of gendarmes
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