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<doi_batch xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.crossref.org/schema/5.3.1" xmlns:jats="http://www.ncbi.nlm.nih.gov/JATS1" xmlns:fr="http://www.crossref.org/fundref.xsd" xmlns:ai="http://www.crossref.org/AccessIndicators.xsd" version="5.3.1"><head><doi_batch_id>NONE</doi_batch_id><timestamp>20260602005908653</timestamp><depositor><depositor_name>Immanuel Kant Baltic Federal University</depositor_name><email_address>no-reply@balticregion.kantiana.ru</email_address></depositor><registrant>Immanuel Kant Baltic Federal University</registrant></head><body><journal><journal_metadata><full_title>Baltic Region</full_title><issn media_type="print">2079-8555</issn><issn media_type="electronic">2310-0524</issn></journal_metadata><journal_issue><publication_date media_type="print"><month>06</month><day>02</day><year>2026</year></publication_date><journal_volume><volume>16</volume></journal_volume><issue>2</issue></journal_issue><journal_article publication_type="full_text"><titles><title>Exclavity of the Kaliningrad region: experience of explication</title><original_language_title>Эксклавность Калининградской области: опыт экспликации</original_language_title></titles><contributors><person_name sequence="first" contributor_role="author"><given_name>A. P.</given_name><surname>Klemeshev</surname><ORCID>https://orcid.org/0000-0002-6343-3263</ORCID></person_name><person_name sequence="additional" contributor_role="author"><given_name>Ya. A.</given_name><surname>Vorozheina</surname><ORCID>https://orcid.org/0000-0003-4777-2051</ORCID></person_name></contributors><jats:abstract><jats:p>The article explores the concept of exclavity using the Kaliningrad region as an example. The authors analyse the concept of exclavity, identify its key attributes and the degree of their relevance, describe indicators of exclavity as well as factors influencing it. The main attributes of the Kaliningrad region’s exclavity are geographical separation and remoteness. The authors distinguish two types of exclavity, absolute (attributive) and relative (functional), identify strategies for overcoming absolute exclavity and offer functional solutions to the ‘access problem’. Among these solutions are extraterritorial corridors and transit regimes. 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Ye.</given_name><surname>Sazonova</surname><ORCID>https://orcid.org/0000-0002-3456-1223</ORCID></person_name><person_name sequence="additional" contributor_role="author"><given_name>O. Ye.</given_name><surname>Vasilieva</surname><ORCID>https://orcid.org/0000-0002-7779-8861</ORCID></person_name><person_name sequence="additional" contributor_role="author"><given_name>I. M.</given_name><surname>Grekov</surname><ORCID>https://orcid.org/0000-0003-0358-3144</ORCID></person_name><person_name sequence="additional" contributor_role="author"><given_name>N. V.</given_name><surname>Sokolova</surname><ORCID>https://orcid.org/0000-0002-8516-0462</ORCID></person_name></contributors><jats:abstract><jats:p>The suburban area of St. Petersburg stands out as Russia’s most complex in terms of spatial structure, encompassing districts ranging from the suburban imperial residences of the 18th century to low-rise residential zones and modern multi-storey developments of the 21st century. 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To this end, an Innovation System Development Index (ISDI) comprising 46 indicators was developed. The authors employed the macro-clustering method, as well as aggregation and combination techniques for parameters and sub-indices. Additionally, complete-linkage and K-means methods were used to group the countries. Kalinsky-Kharabaz and Duda-Hart indices, as well as dendrograms, were found to be the most effective techniques for producing the novel classification proposed in this contribution. It was demonstrated using the former method that national innovation systems exhibit qualitatively different cluster characteristics and follow different development trends. According to the findings, Estonia ranks first on the index among the study countries with (ISDI = 0.77), while the South Caucasus states form two subgroups. Armenia (ISDI = 0.50) and Georgia (ISDI = 0.53) comprise a relatively developed subgroup, whereas Azerbaijan (ISDI = 0.44) constitutes a separate unit, delivering a less remarkable performance. The latter method revealed that the Baltic States form the most developed cluster group, with Estonia once again at the top of the index (ISDI = 0.85). The Baltic States and the South Caucasus states comprised two separate groups. Except for the patent activity sub-index, Estonia outperforms the other study countries on all sub-indices. Armenia and Georgia rank relatively high on the patent activity sub-index, whereas Azerbaijan performs well on the innovation activity and infrastructural development sub-indices. These findings would allow the South Caucasus countries to draw on the experience of the Baltic states in identifying challenges to the development of their national innovation systems. 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E.</given_name><surname>Kurilo</surname><ORCID>https://orcid.org/0000-0002-7222-7832</ORCID></person_name><person_name sequence="additional" contributor_role="author"><given_name>O. V.</given_name><surname>Gubina</surname><ORCID>https://orcid.org/0000-0002-3678-3911</ORCID></person_name><person_name sequence="additional" contributor_role="author"><given_name>E. A.</given_name><surname>Shlapeko</surname><ORCID>https://orcid.org/0000-0003-3518-4543</ORCID></person_name></contributors><jats:abstract><jats:p>With digital communication becoming a quotidian practice, social media has emerged as a common channel for personal and business communication, utilised by authorities among other actors. This article proposes an approach for measuring a territory’s digitalisation by quantifying local governments’ presence on social media. The work aims to identify digital underperformers among municipalities of Russia’s Northwestern Federal District, drawing on data from the Vkontakte social network. The empirical part of the research utilised data gathered from 2011 to 2022 on the socioeconomic performance and municipal heads of 1,083 settlements and 199 districts. Significant factors influencing municipalities’ presence on social media were determined using binary logistic regression, with two clustering results compared to identify the underperforming municipalities. It was concluded that population size, municipal revenues and expenditures, fiscal capacity and average salary are directly proportional to municipal social media presence, and the distance to the regional centre and the status of a district centre are inversely proportional to the study parameter. Age, place of residence and the method of nomination for elections affect the likelihood of a municipal head having a social media account. 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