Objective: to eliminate terminological and institutional uncertainty in the understanding of the equity economy, namely: to clarify its concept through a structural triad (network nature of interaction, business model of shared consumption, availability of excess resources); to develop a classification of private, club and public goods in the Russian context; to empirically assess what types of goods are actually present in civil initiatives on the digital platforms.

Methods: bibliometric analysis, qualitative classification of goods according to of P. Samuelson – J. Buchanan criteria (exclusivity, competitiveness, compatibility), and content analysis of 44 decisions taken with public voting on the “Russian Public Initiative” (RPI) Internet resource since 2013.

Results: the study clarified two key concepts: “Shared economy” (shared use of products, assets and excess resources based on networking with minimal cost of coercion) and “excess resource” (available in volumes excessing the demand, which is under collective management). The author proposed a country-by-country classification of benefits with examples from Russian practice and, for the first time, revealed an asymmetry based on empirical RPI data: among the 20 positive decisions, there are no initiatives related to club benefits (0 out of 20), while public benefits accounted for 17, and private – for 3 decisions. This confirms the institutional gap in the mechanisms of collective but limited access to consumption in the Russian economy, as well as the dominance of the infrastructure and distribution model over the market and the SONPO model.

Scientific novelty: the work clarified the concept of “club benefit” as a hybrid form at the intersection of private and public benefits provided to the “club” members on a temporary basis with minimal coercion costs. The author developed and tested a matrix for analyzing civil initiatives in the “scope of implementation – type of benefit – result of voting” format, which can be applied to other government digital platforms. For the first time, a shortage of club benefits in the Russian digital space was empirically recorded based on RPI data.

Practical significance: the results can help to design interdisciplinary solutions in social policy and creative industries, as well as to create institutional conditions for the effective use of excess resources at the federal, regional and municipal levels.

Objective: to empirically assess the potential of digital social indexing – an institutional mechanism that aggregates data on socio-economic activity for the differentiated provision of preferences – as a tool to stimulate inclusive economic growth in the Russian regions.

Methods: the main component method for constructing integral inclusive growth indices based on GRP per capita, poverty level, Gini coefficient and life expectancy; k-means cluster analysis for typologizing 14 regions of the Volga Federal District; panel regression with fixed effects (FE) to assess the impact of factors; counterfactual modeling to assess the potential effect of digital social indexing (DSI).

Results: The inclusive growth index explains 72.2 % of the baseline indicators variance. Cluster analysis revealed two stable groups of the Volga Federal District regions: “leaders” (five regions, average index 1.55) and “others” (nine regions, average index -0.56). Panel regression showed that engagement (proxy DSI) has a positive and significant effect on the inclusive growth index only in the leaders group (β = 0.794, p < 0.01); in other regions, only the investment factor is significant, while digitalization per se is not significant in any cluster. Counterfactual modeling showed that an increase in engagement by 0.5 standard deviation in the leading regions is equivalent to an increase in investment by 35.9 thousand rubles/person, while in other regions the effect was statistically insignificant.

Scientific novelty: for the first time, based on Russian regional data, it was empirically proven that involvement (proxy DSI) significantly affects inclusive growth, but only in the presence of a favorable institutional and infrastructural environment (in the leading regions). An original methodological package was proposed that allowed quantitatively comparing the “soft” factors’ effect (involvement) with traditional investments. Differentiated recommendations were developed based on the cluster structure.

Practical significance: the results can be used by government authorities to elaborate strategies for socio-economic development, national projects and a system for evaluating the effectiveness of senior officials of the Russian subjects. The proposed toolkit allows applying a targeted regional policy aimed at reducing inequality, developing human capital and unlocking the potential of citizens through engagement mechanisms.

Objective: to theoretically rethink the “global competitiveness of the region” category and to develop its new conceptual model, adequate to the realities of the emerging boundedly open economy.

Methods: theoretical analysis using the historical and genetic method; comparative analysis and conceptual modeling. The research is based on an analysis of classical and modern works on regional economics.

Results: the author revealed inconsistency of traditional paradigms of global competitiveness, which focus on maximum integration into global value chains, and their key theoretical contradictions under sanctions and the global market fragmentation. The essential characteristics of the boundedly open economy were defined (strategic selectivity, active government regulation, priority of security over net benefit, technological sovereignty, and constant search for balance). The author developed a theoretical model that defines the global competitiveness of a region as the ability to ensure sustainable development through managing a balance between three components: diversification of foreign economic links (with an increasing share of BRICS+ countries and non-primary exports), reduction of critical import dependence (development of technological sovereignty), and formation of adaptive human capital to increase the economic complexity of the region. The work proved that simply replacing a Western partner with an Asian one without changing the depth of dependence does not increase competitiveness, but reproduces risk.

Scientific novelty: for the first time, a holistic concept of global competitiveness was proposed, in which the system-forming principle is the polarity “reliance on regional potential – global selectivity”. For the first time, the following provisions were systematically substantiated: a paradigmatic shift from competitiveness as an integration function to competitiveness as a vulnerability management function; the polarity “reliance on regional potential – global selectivity” as a system-forming principle of competitiveness under bounded openness. The work showed that traditional theories (including concepts of clusters, global value chains, and smart specialization) require fundamental correction under bounded openness.

Practical significance: the developed model can serve as a theoretical basis for assessing the ability of regions to adapt to sanctions shocks; for distinguishing between a real increase in competitiveness and imitation through a change of partners; and for developing specific regional policy tools in the field of import substitution, export diversification, and human capital development.

Objective: to determine the impact of changes in sales volumes on the technology-related risk (ADR-risk), taking into account changes in production capacity utilization in the oil and gas industry.

Methods: the work used a combination of probit models with fractional regressions and distribution of weights of sustainability ratings for ADR-risk targeting. The models sensitivity was assessed using graphical multidimensional analysis, calculation of marginal effects, and the delta method.

Results: the comprehensive testing of the relationship between changes in sales volumes, fixed assets, capital investments and technology-related risk indicators in terms of critical depreciation of fixed assets (ADR), taking into account the distribution of weights of sample elements based on public ESG ratings, demonstrate a high sensitivity of the risk of production assets critical depreciation to production load and revenue reduction. The income elasticity of large companies reduces the ADR risk by 2.8% with a 1% drop in revenue, but inversion of the revenue change from negative to positive increases the risk by 3.7%. An increase in fixed asset investments by 1% reduces the risk by 1.3-2.0%, with the most pronounced effect observed in companies with small production assets. It was found that OECD companies with high ESG ratings often have critical equipment depreciation, while companies in the CIS, India, and the Middle East show better ADR with lower ratings. Large companies use the size of fixed assets as a buffer to mitigate the impact of revenue fluctuations on risk.

Scientific novelty: for the first time, the limits of revenue elasticity under production reduction were quantified. It was proved that a decrease in sales paradoxically improves ADR risk, while a sharp increase worsens it. An asymmetric effect was identified: the transition from a decrease to an increase in revenue increases the risk by 1.3 times compared to just an increase. It was shown that public ESG ratings are weakly correlated with the actual production assets depreciation.

Practical significance: the simulation can help companies in the oil and gas sector plan fiscal policy in case of revenue fluctuations, prioritize investments in fixed assets modernization, and regard reduced capacity utilization as a tool for managing technology-related risks, not just as a financial loss.

Objective: to substantiate the conceptual limitations of the risk-based approach applied to civil liability for harm caused by artificial intelligence, and to provide arguments for the criterion of algorithmic behavior predictability.

Methods: based on the fiction of the complete controllability of algorithmic systems shaped within the legal doctrine, the author substantiates a comprehensive methodology combining comparative legal studies (comparing the risk-based AI Act model with Russian law), formal legal analysis (Articles 1, 10, 15, 393, 401, 404, 1079, 1083 of the Russian Civil Code) and hermeneutical method for transferring technical concepts (“hallucinations”, “reproducibility”) into legally relevant categories.

Results: the authors raises the question of the difference between risk and predictability: risk describes the probability and scale of harm (post hoc), while predictability characterizes the controllability of the system behavior ex ante. The authors substantiates that predictability allows one to transform engineering parameters (autonomy, stochasticity) into legally relevant criteria for assessing integrity and reasonableness (Articles 1, 401 of the Russian Civil Code). Using the example of “hallucinations” of generative models, the authors demonstrates that statistically expected deviations qualify within the framework of ordinary business risk, while going beyond the documented limits of testing may indicate a violation of the requirements for system manageability. The research shows that low predictability with high autonomy undermines the grounds of subjective liability and justifies the “source of increased danger” regime (Art. 1079 of the Russian Civil Code): differentiation of liability corresponds to the graduated nature of predictability (Articles 404, 1083 of the Russian Civil Code).

Scientific novelty: the authors substantiates the need to shift the focus from retrospective distribution of harm to a preliminary assessment of decisions on the algorithmic systems implementation, by institutionalizing algorithmic due diligence procedures, including documented evidence of predictability.

Practical significance: an algorithm for judicial assessment of three groups of circumstances is proposed (information about the system, empirical verification, organizational control mechanisms), as well as a recommendation to stipulate in a dedicated AI law the requirement to ensure and assess the predictability of high-risk AI systems.

Objective: to describe and evaluate Pavel Ivanovich Kovalevsky’s views on crime, a criminal personality, the causes of crime and measures to counter it based on the analysis of his scientific works and the opinions of experts.

Methods: general (analysis, synthesis, comparison, grouping, modeling, interpretation) and specific (historical-legal, content analysis of publications in scientific works and in the media) scientific methods used in modern criminological science.

Results: the author identified, described and introduced into scientific discourse new literary sources – the works of Pavel Ivanovich Kovalevsky, published in the late 19^th and early 20^th centuries in the Russian and foreign languages and devoted to assessing the state of crime, a criminal personality, the causes of crime and measures to counter it. The work determined P. I. Kovalevsky’s contribution to the formation and development of the psychopathological field of Russian criminological science.

Scientific novelty: for the first time in Russian criminological science, the research assesses the content of the maximum number of literary works by one of the prominent Russian representatives of the psychopathological field in criminology, P. I. Kovalevsky, which were published in the Russian, French, English and German languages. The evaluation of P. I. Kovalevsky’s works by his contemporaries was monitored based on reviews, comments, and other information published in scientific periodicals.

Practical significance: the research can be used to prepare textbooks, teaching aids and other educational materials for the Criminology course, as well as to theoretically develop the foundations of a new scientific field of Russian criminology – historical criminology. It can provide new content to the “History of Russian Criminology” section.

Objective: to study the potential of artificial intelligence as a decision-making support tool in the Russian criminal proceedings in the context of the approved Concept of Digital Transformation of the Prosecutor’s Office, to define the acceptable limits of its application, and to develop models of practical integration.

Methods: a comparative legal analysis of the Russian and foreign legislation in the field of artificial intelligence regulation; an empirical study including a dialogue with leading language models (Claude Opus4, GPT 4.1, DeepSeek R1, Qwen3, Yandex GPT) to identify their self-assessment in relation to justice administration; a systematic analysis of the requirements for technological infrastructure (unified electronic criminal case) and information security.

Results: the research proved the scientific inconsistency of the hypothesis that the key criminal process subjects – judges and prosecutors – could be adequately replaced with artificial intelligence, as the latter lacks internal conviction and legal personality and cannot bear legal responsibility. By the example of the first judicial precedent in Russia (the sentence of the Yeisk City Court of the Krasnodar Territory), the author analyzed the legal risks of using artificial intelligence in the processing of procedural documents. The concept of a “smart assistant prosecutor” was developed and substantiated, including specific models: a “smart punishment calculator”, an analyzer of the legal positions of courts of higher instances, and a system for verifying judicial practice.

Scientific novelty: the research proposes an original compartment model of the artificial intelligence integration into the prosecutor’s activity, synchronized with the stages of the departmental Concept of Digital Transformation until 2030. The work empirically confirmed the consensus of the artificial intelligence language models on the fundamental obstacles to their autonomous participation in the administration of justice.

Practical significance: the conclusions and suggestions of the study can be used to form a regulatory framework governing the use of artificial intelligence in criminal proceedings, as well as to develop it as part of the digital transformation of law enforcement agencies and the judicial system.

Objective: to identify patterns of regulation of relations associated with quantum technologies development in Russia, foreign countries, and the international regulatory system.

Methods: based on the shaped fragmentation of Russian regulation and integrated approaches in the EU and the USA, the author justifies the preferential use of the comparative legal method as it allows offsetting the national specifics of legal technology. The application of this method goes through the stages of comparison (identification of differences in the conceptual framework, institutional architecture and export control regimes) and the actual comparison, which is expressed in the identification of common patterns and differences in the national context. The author raises the question of the formation of “quantum law” as a specialized legal discourse, which also determines the use of a systematic approach and formal legal analysis.

Results: the comparative legal analysis allowed the author to formulate the following answers to the research questions. First, the fragmentation of Russian regulation was revealed, in contrast to the integrated approaches in the USA (NQIA law) and the EU (preparation of the European Quantum Act). The author proved that it is the law that performs an expressive function, publicly articulating the priority of the quantum sphere. Second, it was established that in all analyzed legal systems, quantum communications and post-quantum cryptography receive priority development. The author interpreted this as an existential threat of “harvest now – decrypt later” (HNDL). Third, the research confirmed the trend of combining government support measures with control tools (NIST/ANSSI standardization, export control). Fourth, the author identified the institutional pattern of reliance on “national champions”. Fifth, he established the increasing role of technical standards as a universal regulatory tool under technological uncertainty.

Scientific novelty: the author substantiated the study of “quantum law” not as a branch, but as a legal discourse – an institutionally organized communication that consolidates normative meanings and reproduces legitimate argumentation procedures in doctrine, rulemaking and law enforcement.

Practical significance: the results can be used by legislators developing comprehensive legislation and by regulators preparing post-quantum migration roadmaps (up to 2030-2035) and implementing experimental legal regimes.

Objective: to resolve the conceptual uncertainty of the civil-law status of digital avatars in the metaverse and related problems of their criminal-legal protection, in particular, to develop criteria for distinguishing property, contractual and intellectual rights to these objects.

Methods: the work was based on the comparative-legal method. The author justifies this by the fragmented approaches to determining the legal nature of avatars that have developed in science and practice, as well as the lack of unified legislative regulation in this area. A comparison of the rules for the use of metaverses (Decentraland, Roblox, Spatial) and judicial acts of the Russian Federation, the USA, South Korea and Colombia revealed implicit norms formed by law enforcers. The formal-logical method was used to classify avatars according to economic and personal criteria. In contrast to the abstractdogmatic approach, the tools used by the author made it possible to establish a direct correlation between the avatar inner content and the qualification of specific attacks.

Results: the author proved that the confirmation of rights to an avatar through NFT is a form of rights fixation, but that does not create intellectual property. It is established that an avatar can be the subject of crimes against property only if there is economic content and turnover; however, its seizure is qualified not as theft, but as fraud (Article 159 of the Russian Criminal Code) or unauthorized access (Article 272 of the Russian Criminal Code). The work showed that in the absence of economic value, an avatar is protected as a carrier of personal data (Articles 137, 138 of the Criminal Code) or an object of copyright (Articles 146 of the Criminal Code).

Scientific novelty: for the first time, a two-level classification of digital avatars was proposed: by the presence of economic content (negotiable / non-negotiable); by connection with a personality (inseparable from personal data / existing independently). The author substantiated a comprehensive (“hybrid”) regime of criminal-law protection of avatars, eliminating the need to introduce new structures, but requiring the Plenum of the Russian Supreme Court to expand the crime target of Chapter 21 of the Russian Criminal Code by analogy with digital currency.

Practical significance: the research results can be used to improve the provisions of law enforcement practice in order to protect public relations within the digital assets turnover.

Objective: to systematize legal facts in the field of information privacy through matrix classification in order to identify the logic and patterns of legal relations dynamics in this area.

Methods: historical and legal analysis, classification of legal relations and legal facts, superposition of classifications in order to identify the point of their intersection, borrowing an interdisciplinary concept of the “extended Self” and integrating it into legal theory, abductive method, systematization, regulatory analysis, and analysis of judicial practice.

Results: the author proposed an extended concept of the object of personal right to information privacy. The work developed a matrix classification of legal facts using the example of an absolute civil-legal relationship of information privacy. The author substantiated the applied significance of the interdisciplinary “extended Self” concept and classified the spheres of life of a personal data subject. This deepens the understanding of such qualifying features of personal data as relevance and definability. Five presumptions in the field of information privacy were explained; the nature of the phenomenon of “experiencing” the information privacy rights was clarified. General patterns of dynamics of legal relations of information privacy were formulated.

Scientific novelty: the research combines the classical civilistic classification of legal facts with the classification of the spheres of life of the personal data subject and develops a matrix methodology for such classification. It reveals the legal significance of natural and acquired properties of personal data and the conceptual importance of the right to information privacy of the expected degree of personal data properties. The author proposes an expanded concept of the personal intangible good of information privacy and identifies the internal limits of its implementation. Five presumptions in the field of information privacy were formulated, in order to deepen the understanding of such qualifying features of personal data as relevance and definiteness.

Practical significance: the proposed analysis of legal facts can be used by legislators in the construction and interpretation of legal norms governing information privacy; by law enforcement agencies – in qualifying facts as legally significant and identifying hidden legal relationships based on known legal facts; and by courts – in resolving disputes about violations of information privacy rights. The elaboration of such qualifying features of personal data as relevance and definiteness helps to qualify data as personal and serves as an argument in relevant theoretical disputes.