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October 14, 2026
At HSE University–St Petersburg, Experts Discuss How AI Changes Tourist Routes and Cultural Heritage
Neural networks are no longer simple travel assistants; now they decide what to include on the route and what to skip. Artificial intelligence changes how people perceive a place and shapes the image of tourist centres. At the II International Scientific and Practical Conference ’Information Technologies in the Preservation and Promotion of Cultural Heritage,’ researchers discussed who controls algorithmic solutions and in what ways, and whether authentic traditions get lost in them.
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October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.

 

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Dialect loss in the Russian North: modeling change across variables

Language Variation and Change. 2019. Vol. 31. No. 3. P. 353–376.
Daniel M., von Waldenfels R., Ter-Avanesova A., Kazakova P., Schurov I., Gerasimenko E., Игнатенко Д. И., Махлина Е. Н., Tsfasman M., Verhees S., Vinyar A., Zhigulskaya V., Ovsjannikova M., Say S., Dobrushina N.

We analyze the dynamics of dialect loss in a cluster of villages in rural northern Russia based on a corpus of transcribed interviews, the Ustja River Basin Corpus. Eleven phonological and morphological variables are analyzed across 33 speakers born between 1922 and 1996 in a series of logistic regression models. We propose three characteristics for a comparison of the rate of loss of different variables: initial level, steepness, and turning point. We show that the dynamics of loss differs significantly across variables and discuss possible reasons for such differences, including perceptual salience, initial variation in the dialect, and convergence with regionally or socially defined varieties of Russian. In conclusion, we discuss the pros and cons of logistic regression as an approach to quantitative modelling of dialect loss. Our paper contributes to the study and documentation of Russian dialects, most of which are on the verge of extinction.

Research target: Philology and Linguistics
Priority areas: humanitarian
Language: English
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Keywords: русский языклогистическая регрессиядиалектыкорпусная лингвистикаlogistic regressioncorpus linguisticslanguage changeязыковая вариативностьlanguage variationnorthern Russian dialects
Publication based on the results of:
Processes of convergence as a factor of language evolution (2020)
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