Investigation of the Influence of a Number of Socio-Economic Factors on Migration Flows Between the Federal Districts of the Russian Federation

2018 ◽  
pp. 36-39
Author(s):  
Sergey Rusakov ◽  
Olga Rusakova ◽  
Maksim Immis
Keyword(s):  
Russian Federation ◽  
Economic Factors ◽  
Federal Districts ◽  
The Russian Federation ◽  
Migration Flows ◽  
Socio Economic Factors

scholarly journals Environmental terrorism and socio-economic factors in the mechanism of countering terrorist crimes

2021 ◽  
Vol 244 ◽  
pp. 12017
Author(s):  
Irina Danilova ◽  
Olga Knyazeva ◽  
Svetlana Mayorova ◽  
Liliana Peremolotova
Keyword(s):  
Law Enforcement ◽  
Russian Federation ◽  
Criminal Code ◽  
Economic Factors ◽  
International Convention ◽  
Modern Period ◽  
International Obligations ◽  
The Russian Federation ◽  
Financing Of Terrorism ◽  
Socio Economic Factors

In the modern period of the widespread processes of globalization, integration and rapid migration, complicated foreign policy relations of a number of states belonging to transnational blocs defending opposing interests, of course, the problem of effectively countering terrorist and extremist activities, as well as preventing the spread of relevant ideologies, is becoming particularly acute. The international community, realizing the danger of terrorism and striving to develop effective measures to prevent it, has adopted a number of documents, which include United Nations conventions (for example, the International Convention for the Suppression of the Taking of Hostages, the International Convention for the Suppression of Terrorist Bombings, the International Convention for the Suppression of financing of terrorism). The increased importance of this type of crime is also confirmed by the consolidation in federal legislation of the relevant concepts and forms in which the considered illegal activity can be carried out, the methods of its prevention and sanctions used for committing offenses of an extremist and terrorist nature. The main normative legal acts in this area are the federal laws of July 25, 2002 No. 114-FZ “On Countering Extremist Activity” and of March 6, 2006 No. 35-FZ “On Countering Terrorism.” For the purposes of criminal law enforcement of countering terrorism and in the interests of fulfilling international obligations, the Criminal Code of the Russian Federation of June 13, 1996 (as amended on November 28, 2015, hereinafter referred to as the Criminal Code of the Russian Federation) establishes responsibility for the commission of crimes against international security.

scholarly journals Impact of socio-economic factors on the formation of disability in children of Russia

2020 ◽  
Vol 23 (6) ◽  
pp. 365-371
Author(s):  
Rimma N. Terletskaya ◽  
Andrey P. Fisenko ◽  
Elena V. Antonova ◽  
Irina V. Vinyarskaya
Keyword(s):  
Russian Federation ◽  
Rank Correlation ◽  
Correlation Method ◽  
Economic Situation ◽  
Economic Factors ◽  
Rank Correlation Method ◽  
Disability Prevalence ◽  
The Russian Federation ◽  
Monetary Income ◽  
Socio Economic Factors

Introduction. There are not enough studies dealing with the assessment of impact of socio-economic factors on the health of the population at the interregional level. However, the instability of the economic situation requires a periodic repetition of such researches. The aim of the study is to establish the relationship between the children’s disability prevalence and the main indices characterizing socio-economic situation in the Russian Federation. Materials and methods. Official data on the prevalence of disability in children aged 0-17 years and the level of basic indices characterizing the socio-economic situation in the country were analyzed in the context of 83 constituent entities of the Russian Federation for the period 2017-2019. The socio-economic characteristics of the population were the unemployment rate, monetary income, housing conditions, and consumption of basic food products. Spearman rank correlation method was used to determine the links. Results. It was established that there is still significant interregional variability in the prevalence of children’s disability both in Federal districts and in the subjects of the Federation. It’s been revealed various degrees of severity correlation between the childrens’ disability prevalence in the subjects of the Russian Federation and many socio-economic factors including unemployment; average per capita monetary income of the population; the proportion of the population with monetary incomes below the subsistence minimum; total area of residential premises, which is on average per inhabitant; the share of young families registered as needing housing, from the total number of family cells with children under 18 years; consumption of cheaper food. Conclusion. The results should be taken into account in the development of programs for the children’s disability prevention; full responsibility should not been placed on the healthcare system only.

scholarly journals 3.3. ANALYSIS OF FACTORS OF FERTILITY OF POPULATION IN THE REGIONS OF THE RUSSIAN FEDERATION BY THE MODEL OF MODELING

2021 ◽  
pp. 48-55
Author(s):  
А.Б. Берендеева ◽  
О.В. Сизова
Keyword(s):  
Russian Federation ◽  
Birth Rate ◽  
Economic Factors ◽  
Russian Regions ◽  
Total Birth ◽  
Total Birth Rate ◽  
Main Tendency ◽  
The Russian Federation ◽  
The Impact ◽  
Socio Economic Factors

Рассмотрена динамика суммарного коэффициента рождаемости в Российской Федерации и факторы рождаемости. Выделено пять групп регионов РФ по уровню суммарного коэффициента рождаемости. На примере пяти регионов-лидеров и пяти регионов-антилидеров проанализировано воздействие на по-казатель рождаемости девяти социально-экономических факторов. Рассмотрена динамика ко-эффициента рождаемости и выявлена основная тен-денция изменения данного показателя. С помощью корреляционно-регрессионного анализа выявлены факторы, оказывающие определяющее воздействие на рождаемость в РФ. Выделены группы факторов по степени влияния на рождаемость населения. The dynamics of the total fertility rate in Russia and fertility factors are considered. Five groups of Russian regions were identified by the level of the total birth rate. Using the example of 5 leading regions and 5 anti-leader regions, we analyzed the impact on the birth rate of 9 socio-economic factors. The dynamics of the birth rate is examined and the main tendency for this indicator to change. Using correlation and re-gression analysis, factors were identified that have a decisive effect on fertility in Russia. Groups of factors are identified by the degree of influence on the birth rate of the population.

scholarly journals Statistical Data Research on Staff Training for the Digital Economy in the Russian Federation

2021 ◽  
Vol 30 (11) ◽  
pp. 29-41
Author(s):  
Yu. V. Frolov ◽  
T. M. Bosenko
Keyword(s):  
Russian Federation ◽  
Regression Models ◽  
Statistical Data ◽  
Digital Economy ◽  
Economic Factors ◽  
Objective Functions ◽  
Economic Sectors ◽  
Different Dimensions ◽  
The Russian Federation ◽  
Socio Economic Factors

The article analyzes the statistical data relating to training specialists for digitalized economy by secondary vocational and higher education institutions. The purpose of the study was to develop and test personnel support indices for digitalization of the economy, as well as to identify social and economic factors that significantly affect the level of personnel support for the processes of digital transformation of the economy. The authors applied data from the official statistical reporting of the Russian Federation. The proposed staffing indices were modeled as objective functions depending on socio-economic factors characterizing the development of the economy in different dimensions. At the same time, the indices themselves were calculated as values in which the parameters of the output of digital specialists and their relevance in the economy were correlated. In the course of the study, a comparison of statistical and neural network data modeling methods and generalizing indices was performed. An analysis of the obtained regression models and an analysis of the sensitivity of trained neural networks made it possible to evaluate their accuracy in predicting the trends in the staffing of the digital economy and to identify factors that significantly affect the achievement of the goal of matching the output of specialists and the demands of economic sectors.

scholarly journals Trends in educational migration in the Russian Federation

2019 ◽  
Vol 3 (2) ◽  
pp. 52-65
Author(s):  
Alfiya R. Kuznetsova
Keyword(s):  
Russian Federation ◽  
Federal District ◽  
Educational Institutions ◽  
Sociocultural Factors ◽  
North West ◽  
The North ◽  
Federal Districts ◽  
The Russian Federation ◽  
Migration Flows ◽  
Educational Migration

This article analyzes the trends in international migration processes in federal districts. The analysis of state statistics (2016-2018) revealed conflicting trends in its various aspects. The results show that international educational migration in Russia has an extremely low proportion, which is only 3% of the total migration inflow. The number of educated migrants has grown by almost a third. The main contributing countries of the educational sphere are Kazakhstan, China, Turkmenistan, Tajikistan, Uzbekistan, India, and Iraq among others. At the same time, the number of educational migrants from Kazakhstan, Ukraine, and Moldova has slightly decreased over three years. The results show significant imbalances in the territorial distribution of educational migration flows in the Russian Federation. They mostly take place in the regions and the North-West Federal District (about 50% of migrants by educational institutions, Volga and Siberia — more than 30%). This means that the education system and the use of infrastructure are unlimited. This article identifies the types of dynamics of the formed clusters in federal districts, which resulted in the corresponding typology. The author has calculated the growth rate of educational migration, which is the ratio of the growth in the number of educational migrants to the increase in the total number of people who arrived in the federal district and registered as migrants. It seems appropriate that within the framework of research in the field of the modern sociocultural approach, the mechanism of redistribution of human capital should be involved. This will allow a deeper study of sociocultural factors and the consequences of educational migration.

Effects of socio-economic factors on old-age mortality in Russia

2022 ◽  
pp. 910-918
Author(s):  
Г. Л. Сафарова ◽  
В.А. Кипяткова ◽  
А. А. Сафарова
Keyword(s):  
Old Age ◽  
Russian Federation ◽  
Regional Differences ◽  
Age Groups ◽  
Mortality Rates ◽  
Economic Factors ◽  
Demographic Development ◽  
Female Population ◽  
The Russian Federation ◽  
Socio Economic Factors

Исследование смертности занимает важное место в демографии в целом и в особенности в демографии старения. России свойственна неоднородность демографического развития, в частности региональная дифференциация показателей смертности населения. Работа посвящена анализу зависимости смертности в регионах России в старших возрастных группах от социально-экономических показателей. Исследование проводили с использованием методов регрессионного анализа, где в качестве единиц наблюдения выступали субъекты РФ, в качестве объясняемой переменной - смертность мужского (женского) населения старшего (60+) возраста, представленная в виде стандартизованных по структуре населения коэффициентов. В результате работы выявлены значимые социально-экономические факторы, позволяющие объяснить различия уровней смертности в субъектах РФ. Studies of old-age mortality are an important part of demography, especially the demography of ageing. Demographic development of Russia is characterized by heterogeneity including regional differences in mortality. The aim of the paper is to analyze the dependence of mortality at old-age groups on socio-economic indicators. The study is conducted using methods of regression analysis; the units of observation are the regions of the Russian Federation, the explained variable is the mortality rate of male (female) population at older (60+) ages standardized by the population-age structure. As a result, the significant socio-economic factors, explaining the differences of mortality rates in the regions of the Russian Federation, were identified.

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