Vol 12, No 3 (2025): MANAGEMENT OF THE STATE FAMILY AND DEMOGRAPHIC POLICY

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On the basis of statistical material and sociological research, the authors demonstrate the crisis nature of demographic processes in Russia in general and focus in particular on men as a risk group for premature mortality. The analysis of demographic indicators shows that the continuing excess of mortality over the birth rate is due in no small part to the excess mortality of the male population of working age. It is noted that despite the difference in the biological resistance of the male and female organism, the reasons for the increased mortality of men lie not only in this difference, but also in their insufficiently formed culture of careful attitude to their health. The author’s sociological research, conducted among 6280 male respondents selected on the basis of a representative sample, reveals negative health practices in the life of Russian men and identifies stable patterns of men’s behavior that negatively affect their health. The study pays special attention to the analysis of socio-cultural determinants, which create significant barriers to seeking timely medical help. It concluded that Russian men pay insufficient attention to physical activity, tend to have unhealthy eating habits, are reluctant to undergo medical examinations, often fail to comply with treatment regimes and adopt a passive attitude to health issues. The study identified three dominant patterns of behavior in men’s attitudes to health issues: orientation towards the state health care system, emphasis on environmental factors and psychological stability, and emphasis on personal responsibility. The data show the prevalence of a passive attitude in which responsibility for health is delegated to medical institutions, which significantly reduces the effectiveness of preventive measures. The authors argue that it is necessary to apply health-building and health-enhancing technologies of demographic management to men. Special emphasis is placed on the development of specific communication strategies to overcome harmful stereotypes and to motivate men to adopt healthy lifestyles.

The study analyzes theoretical approaches to understanding the essence of reproductive behavior, factors influencing its formation, the role and structure of demographic policy. The study considers the specifics of demographic policy, the evolution of Russian experience in managing demographic processes, and provides statistical data. Attention is drawn to the expansion of the range of socio-psychological and socio-cultural motivation of reproductive behavior. The state demographic policy is considered as a response to the challenges of the country’s social development, and the key role of a number of documents is shown. The author shows crucial importance of the national projects “Healthcare”, “Demography”, “Education”, and “Culture” in solving the fertility crisis in the country. Most of the measures to support families with children and stimulate fertility were provided in the national Demography project. Attention is drawn to the launch of the new national project “Family”, which continues the best practices of the Demography project, as well as provides comprehensive support for families with children, reducing poverty, and creating a positive image of having many children. The study systematizes measures of demographic policy at the federal and regional levels, identifies their specifics in the Republic of Tatarstan in the context of changing patterns of reproductive behavior. Regional measures to support families with children and large families are presented in relation to the dynamics of demographic indicators of the republic in the period from the beginning of the 21st century to 2024. During the period of implementation of the measures, a more prosperous demographic state of the Republic of Tatarstan was noted in comparison with the regions of the Volga Federal District and Russia as a whole in terms of fertility and life expectancy. In 2022, the federal total fertility rate was 8.9‰, while the republican birth rate was 9.2‰.

The study analyzes the impact of state agglomeration policy on demographic trends in Russia, with a special focus on the relationship between urbanization and birth rate. The study is based on data on population size and differences in demographic indicators between urban and rural areas, and includes a forecast of possible changes in the demographic situation up to 2100 using scenario modeling methods. The purpose of the study is to identify the key consequences of the agglomeration approach for long-term demographic development in line with the new “Spatial Development Strategy of the Russian Federation for the period up to 2030 with a forecast up to 2036”, as well as to assess possible approaches to adjusting state policy in the context of depopulation. The study materials include Rosstat’s estimated data on population size and components of its change, including total fertility rates for urban and rural populations. Methods of forecasting demographic dynamics components were applied, in particular SARIMA (implemented in Python) for fertility forecasting. The population is projected using the cohort-component method (“age shifting”) with the Spectrum software (DemProj module). Three main scenarios are considered: continuation of the current urbanization trend, maintenance of a static share of urban and rural population, and a “deurbanization” scenario as a possible alternative. The results show that given the current low birth rates and zero migration growth, Russia’s population will continue to decline under all three scenarios. The issue of declining birth rates in cities is particularly acute, exacerbated by the consolidation of agglomerations. It is concluded that the ongoing urbanization policy, combined with low birth rates, intensifies the country’s depopulation, while a deurbanization policy cannot radically change the demographic situation.

The study analyzes the features of the use of artificial intelligence in the field of public administration in the Russian Federation and the European Union. At the same time, the focus has shifted to the area of legal regulation of this process. The study presents an analysis of key regulatory legal acts that contain the main provisions for the use of this type of end-to-end digital technologies in the field of public administration. The author emphasizes that the formation of the regulatory framework of Russia and the EU countries began at about the same time and independently of each other. At the same time, the rule-making process in both legal systems has both common features and significant differences. The author offers his own view on the research methods of the indicated problem. The author also highlights the lack of knowledge of the designated topic, both in Russia and abroad, despite the similarity of the challenges that digital transformations bring with them for national security. The study states that there are differences in the field of legal regulation of the use of end-to-end digital technologies, including artificial intelligence, primarily since public authorities interpret them differently. The established rule-making tradition is also considered as an important factor. The author emphasizes the tradition that has taken shape in European countries to give priority attention to the protection of negative freedoms of citizens, which has also left its mark on the specifics of the legislation of the European Union. The study concludes that the Russian approach to rulemaking is characterized by greater attention to the problems of state security. The study suggests considering international experience in the legislative process, despite the divergence in national accents in the emerging global digital law. A special feature of the conducted research is the fact that the study provides a detailed analysis of the provisions of the main documents that regulate the use of artificial intelligence in both legal systems. At the same time, it is noted that in each jurisdiction there is no key law act regulating the use of artificial intelligence in the field of public administration.