26 research outputs found

    Parental labor in the Republic of Tuva in the context of the regional cluster structure of Russia's demographic space (1990-2019)

    Get PDF
    Despite the overall positive dynamics of demographic processes related to the natural reproduction of the population in the Republic of Tuva, the region currently experiences a fairly negative state of several spheres of human capital functioning and development. This may indicate a problematic state of the sphere of parental labor in the region. The article presents the results of identifying the place of the Republic of Tuva in the cluster structures of Russian regions. These structures were formed by the parameters of parental labor during the period from 1990 to 2019. The authors assess the place of the Republic of Tuva in the cluster space of Russian regions according to indicators that demonstrate the conditions, organization and results of parental labor. The research is based on an interdisciplinary concept of parental labor, which implies the labor character of parenthood and its compliance with all the features of work activity. The sources of the study are the data of the Federal State Statistics Service and the data of federal statistical observations on socio-demographic issues. Two key features of the position of the Republic of Tuva in the regional cluster structure have been identified. The first one is that Tuva either does not fit into the structure of the formed regional cluster space and is not included in any of the identified clusters, or it is geometrically located at a very far distance from the center of the cluster to which it is assigned. The second feature is that the profile of Tuva as part of the entire cluster is in most cases characterized by polarity and extreme ambiguity. Β© 2023 New Reaearch of Tuva. All rights reserved.SS–1327.2022.2The research was conducted as part of the project β€œRussian Pro-Natalist Policy Support Institutions: Potential and Prospects for Influencing Birth Rate Growth” supported by the Council for Grants of the President of the Russian Federation for State Support to Leading Scientific Schools of the Russian Federation (SS–1327.2022.2)

    Models of grandparents' labour in the socio-economic space of Russia

    Get PDF
    Π˜Π·ΡƒΡ‡Π΅Π½ΠΈΠ΅ Ρ„Π΅Π½ΠΎΠΌΠ΅Π½Π° ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΠΊΠΎΠ³ΠΎ Ρ‚Ρ€ΡƒΠ΄Π° являСтся ΠΎΠ΄Π½ΠΎΠΉ ΠΈΠ· пСрспСктив развития экономики Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΠΊΠΎΠ³ΠΎ Ρ‚Ρ€ΡƒΠ΄Π° - Π½Π°ΡƒΡ‡Π½ΠΎΠ³ΠΎ направлСния, Π°ΠΊΡ‚ΠΈΠ²Π½ΠΎ Ρ€Π°Π·Π²ΠΈΠ²Π°Π΅ΠΌΠΎΠ³ΠΎ Π·Π°Ρ€ΡƒΠ±Π΅ΠΆΠ½Ρ‹ΠΌΠΈ, Π° с Π½Π°Ρ‡Π°Π»Π° 2000-Ρ… Π³Π³. - ΠΈ российскими исслСдоватСлями. Высокий ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎ-экономичСской Π΄ΠΈΡ„Ρ„Π΅Ρ€Π΅Π½Ρ†ΠΈΠ°Ρ†ΠΈΠΈ российских Ρ‚Π΅Ρ€Ρ€ΠΈΡ‚ΠΎΡ€ΠΈΠΉ, Π° Ρ‚Π°ΠΊΠΆΠ΅ Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΠΎΡΡ‚ΡŒ Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ Π²Π°ΠΆΠ½Ρ‹Ρ… стратСгичСских Π·Π°Π΄Π°Ρ‡, сформулированных Π² Π½Π°Ρ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠΌ ΠΏΡ€ΠΎΠ΅ΠΊΡ‚Π΅ «ДСмография» ΠΈ Π‘Ρ‚Ρ€Π°Ρ‚Π΅Π³ΠΈΠΈ пространствСнного развития Российской Π€Π΅Π΄Π΅Ρ€Π°Ρ†ΠΈΠΈ Π½Π° ΠΏΠ΅Ρ€ΠΈΠΎΠ΄ Π΄ΠΎ 2025 Π³ΠΎΠ΄Π°, Π°ΠΊΡ‚ΡƒΠ°Π»ΠΈΠ·ΠΈΡ€ΡƒΡŽΡ‚ ΠΈΠ·ΡƒΡ‡Π΅Π½ΠΈΠ΅ ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΠΊΠΎΠ³ΠΎ Ρ‚Ρ€ΡƒΠ΄Π°. ЦСль настоящСго исслСдования состоит Π² выявлСнии спСцифичСских Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… ситуаций - ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΠΊΠΎΠ³ΠΎ Ρ‚Ρ€ΡƒΠ΄Π° Π² ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎ-экономичСском пространствС страны. ЭмпиричСской основой Π°Π½Π°Π»ΠΈΠ·Π° послуТили Π΄Π°Π½Π½Ρ‹Π΅ обслСдования Росстата «КомплСксноС наблюдСниС условий ΠΆΠΈΠ·Π½ΠΈ насСлСния», ΠΎΡ‚Π΄Π΅Π»ΡŒΠ½Ρ‹Π΅ вопросы ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠ³ΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡŽΡ‚ Π² ΠΏΠ΅Ρ€Π²ΠΎΠΌ ΠΏΡ€ΠΈΠ±Π»ΠΈΠΆΠ΅Π½ΠΈΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚ΡŒ ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΠΊΠΈΠΉ Ρ‚Ρ€ΡƒΠ΄. Π’ качСствС основного ΠΌΠ΅Ρ‚ΠΎΠ΄Π° ΠΏΡ€ΠΈΠΌΠ΅Π½ΡΠ»ΠΈΡΡŒ иСрархичСских кластСрный Π°Π½Π°Π»ΠΈΠ· (Π½Π° основС ΠΌΠ΅Ρ‚ΠΎΠ΄Π° Π’Π°Ρ€Π΄Π°, ΠΊΠ²Π°Π΄Ρ€Π°Ρ‚Π° Π΅Π²ΠΊΠ»ΠΈΠ΄ΠΎΠ²Π° расстояния ΠΈ Π΄Ρ€ΡƒΠ³ΠΈΡ… ΠΌΠ΅Ρ€) ΠΈ нСиСрархичСский кластСрный Π°Π½Π°Π»ΠΈΠ· (ΠΌΠ΅Ρ‚ΠΎΠ΄ k-срСдних). Π’ процСссС исслСдования ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Ρ‹ Ρ‚Π΅ΠΎΡ€Π΅Ρ‚ΠΈΠΊΠΎ-мСтодологичСскиС ΠΈ ΠΏΡ€ΠΈΠΊΠ»Π°Π΄Π½Ρ‹Π΅ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹. Π‘Ρ‹Π»Π° прСдставлСна мСтодологичСская основа изучСния ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΠΊΠΎΠ³ΠΎ Ρ‚Ρ€ΡƒΠ΄Π°, сформированная Π½Π° Π±Π°Π·Π΅ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² исслСдований Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΠΊΠΎΠ³ΠΎ Ρ‚Ρ€ΡƒΠ΄Π° ΠΈ Π·Π°Ρ€ΡƒΠ±Π΅ΠΆΠ½Ρ‹Ρ… дСмографичСских исслСдований ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΡ‚Π²Π°. ЭмпиричСский Π°Π½Π°Π»ΠΈΠ· ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ» Π²Ρ‹ΡΠ²ΠΈΡ‚ΡŒ ΠΈ ΠΎΡ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ·ΠΎΠ²Π°Ρ‚ΡŒ 6 ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΠΊΠΎΠ³ΠΎ Ρ‚Ρ€ΡƒΠ΄Π° Π±Π°Π±ΡƒΡˆΠ΅ΠΊ, ΡΠ»ΠΎΠΆΠΈΠ²ΡˆΠΈΡ…ΡΡ Π² российском ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎ-экономичСском пространствС. ВыявлСнныС ΠΌΠΎΠ΄Π΅Π»ΠΈ Ρ€Π°Π·Π»ΠΈΡ‡Π°ΡŽΡ‚ΡΡ ΠΏΠΎ ΡƒΡ€ΠΎΠ²Π½ΡŽ ΠΈ интСнсивности Π²ΠΊΠ»ΡŽΡ‡Π΅Π½Π½ΠΎΡΡ‚ΠΈ ΠΆΠ΅Π½Ρ‰ΠΈΠ½ ΡΡ‚Π°Ρ€ΡˆΠ΅Π³ΠΎ возраста Π² сфСру ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΠΊΠΎΠ³ΠΎ Ρ‚Ρ€ΡƒΠ΄Π°, Π° Ρ‚Π°ΠΊΠΆΠ΅ ΠΈΡ… ΠΏΠΎΡ‚Π΅Π½Ρ†ΠΈΠ°Π»Ρƒ Π² этой сфСрС. Π‘Ρ‹Π» прСдставлСн Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹ΠΉ состав ΠΊΠ°ΠΆΠ΄ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΠΊΠΎΠ³ΠΎ Ρ‚Ρ€ΡƒΠ΄Π° - Π²Ρ‹Π΄Π΅Π»Π΅Π½Ρ‹ Ρ€Π΅Π³ΠΈΠΎΠ½Ρ‹-ядра, ΠΏΡ€Π΅Π΄ΡΡ‚Π°Π²Π»ΡΡŽΡ‰ΠΈΠ΅ собой Π³Ρ€ΡƒΠΏΠΏΡ‹ Ρ€Π΅Π³ΠΈΠΎΠ½ΠΎΠ², устойчиво связанных Π² Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… Π²Π°Ρ€ΠΈΠ°Π½Ρ‚Π°Ρ… кластСризации. ΠŸΠΎΠΊΠ°Π·Π°Π½Ρ‹ прСимущСства Π°ΠΊΡ‚ΠΈΠ²ΠΈΠ·Π°Ρ†ΠΈΠΈ ΠΈ стимулирования со стороны государства ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΠΊΠΎΠ³ΠΎ Ρ‚Ρ€ΡƒΠ΄Π° Π² Ρ€Π΅Π³ΠΈΠΎΠ½Π°Ρ… страны. ΠŸΠ΅Ρ€ΡΠΏΠ΅ΠΊΡ‚ΠΈΠ²Ρ‹ исслСдования - ΠΈΠ·ΡƒΡ‡Π΅Π½ΠΈΠ΅ особСнностСй ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΠΊΠΎΠ³ΠΎ Ρ‚Ρ€ΡƒΠ΄Π° для Ρ€Π°Π·Π½Ρ‹Ρ… ΠΊΠ°Ρ‚Π΅Π³ΠΎΡ€ΠΈΠΉ Π΅Π³ΠΎ ΡΡƒΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠ² - ΠΌΡƒΠΆΡ‡ΠΈΠ½, ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»Π΅ΠΉ, ΠΏΡ€ΠΎΠΆΠΈΠ²Π°ΡŽΡ‰ΠΈΡ… вмСстС с Π²Π½ΡƒΠΊΠ°ΠΌΠΈ ΠΈ ΠΎΡ‚Π΄Π΅Π»ΡŒΠ½ΠΎ ΠΎΡ‚ Π½ΠΈΡ…, ΠΏΡ€ΠΎΠΆΠΈΠ²Π°ΡŽΡ‰ΠΈΡ… Π² ΠΎΠ΄Π½ΠΎΠΌ Π³ΠΎΡ€ΠΎΠ΄Π΅, Ρ€Π΅Π³ΠΈΠΎΠ½Π΅ ΠΈΠ»ΠΈ Ρ€Π°Π·Π½Ρ‹Ρ… российских Ρ€Π΅Π³ΠΈΠΎΠ½Π°Ρ….Foreign researchers consider the phenomenon of grandparents’ labour in the framework of the economy of parental labour. Since the early 2000s, Russian scientists have been actively studying this problem due to high socio-economic disparity of Russian regions, and important strategic objectives stated in the Demography National Project and the Strategy of Spatial Development of the Russian Federation for the period until 2025. We identified and described specific regional situations, namely, models of grandparents’ labour in the socio-economic space of the country. To analyse grandparents’ labour, we examined individual questions of the β€œComprehensive monitoring of living conditions” survey published by the Federal State Statistics Service (Rosstat). The research methodology includes both hierarchical (based on Ward’s method, the square of the Euclidean distance, and other measures) and non-hierarchical cluster analysis (the k-means method). We proposed a method for studying grandparents’ labour based on research of parental labour and international demographic studies on grandparenthood. The empirical analysis revealed 6 models of grandparents’ labour in the socio-economic space of Russia. These models differ in the level and intensity of involvement of older women in the sphere of grandparents’ labour and their potential in this area. For each model of grandparents’ labour, we identified the core regions (groups of regions) involved in the clustering. We explained why the government should be interested in the activation and stimulation of grandparents’ labour in Russian regions. Further research should focus on examining the particularities of grandparents’ labour depending on the actors: men, grandparents living with their grandchildren and apart from them, living in the same city, in the same or different regions of Russia.ИсслСдованиС Π²Ρ‹ΠΏΠΎΠ»Π½Π΅Π½ΠΎ ΠΏΡ€ΠΈ финансовой ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΠ΅ РЀЀИ Π² Ρ€Π°ΠΌΠΊΠ°Ρ… Π½Π°ΡƒΡ‡Π½ΠΎΠ³ΠΎ ΠΏΡ€ΠΎΠ΅ΠΊΡ‚Π° β„–20–011–00280.The article has been prepared with the support of Russian Foundation for Basic Research, the project No. 20–011–00280

    ΠšΠ›ΠΠ‘Π’Π•Π ΠΠ«Π™ ΠΠΠΠ›Π˜Π— Π’ Π˜Π‘Π‘Π›Π•Π”ΠžΠ’ΠΠΠ˜Π˜ Π Π•Π“Π˜ΠžΠΠΠ›Π¬ΠΠžΠ™ Π”Π˜Π€Π€Π•Π Π•ΠΠ¦Π˜ΠΠ¦Π˜Π˜ ΠŸΠ ΠžΠ¦Π•Π‘Π‘ΠžΠ’ Π’ΠžΠ‘ΠŸΠ ΠžΠ˜Π—Π’ΠžΠ”Π‘Π’Π’Π ΠœΠžΠ›ΠžΠ”ΠžΠ“Πž ΠŸΠžΠšΠžΠ›Π•ΠΠ˜Π― Π’ РОББИИ

    Get PDF
    Historically, there have been significant differences between the various parts of Russia as regards socio-economic parameters. Clearly, the use of a single set of measures to address demographic problems in different parts of Russia cannot be effective. This situation requires a differentiated approach based on the allocation of groups of regions that are similar in features of the current demographic situation. The purpose of the study was to identify the regional differentiation of the processes of young generation reproduction. The authors performed an agglomerative hierarchical clustering algorithm to identify groups of regions characterised by similar features in the sphere of reproduction. The analysis enabled to reveal five groups of regions where the situation with young population has characteristic features.The study has allowed drawing a number of theoretical and practical conclusions aimed at improving the country’s state youth policy. In addition, this research has shown that statistical cluster analysis can be considered as an effective tool of development of practical recommendations for prompt solving problems among youth. Therefore, this type of analysis can be integrated as an analytical tool in the research component of the state youth policy.Π˜ΡΡ‚ΠΎΡ€ΠΈΡ‡Π΅ΡΠΊΠΈ Ρ€Π΅Π³ΠΈΠΎΠ½Ρ‹ России сущСствСнно Ρ€Π°Π·Π»ΠΈΡ‡Π°ΡŽΡ‚ΡΡ ΠΌΠ΅ΠΆΠ΄Ρƒ собой ΠΏΠΎ Ρ†Π΅Π»ΠΎΠΌΡƒ ряду ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎ-экономичСских ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ. ΠžΡ‡Π΅Π²ΠΈΠ΄Π½ΠΎ, Ρ‡Ρ‚ΠΎ Π² этих условиях для Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ дСмографичСских ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌ российских Ρ‚Π΅Ρ€Ρ€ΠΈΡ‚ΠΎΡ€ΠΈΠΉ ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ Π΅Π΄ΠΈΠ½ΠΎΠ³ΠΎ, ΡƒΡ€Π°Π²Π½ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Π° Π½Π΅ ΠΌΠΎΠΆΠ΅Ρ‚ Π±Ρ‹Ρ‚ΡŒ эффСктивным. Π—Π΄Π΅ΡΡŒ Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌ Π΄ΠΈΡ„Ρ„Π΅Ρ€Π΅Π½Ρ†ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹ΠΉ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄, основанный Π½Π° Π²Ρ‹Π΄Π΅Π»Π΅Π½ΠΈΠΈ Π³Ρ€ΡƒΠΏΠΏ Ρ€Π΅Π³ΠΈΠΎΠ½ΠΎΠ², ΠΎΡ‚Π»ΠΈΡ‡Π°ΡŽΡ‰ΠΈΡ…ΡΡ схоТими особСнностями слоТившСйся дСмографичСской ситуации.ЦСль настоящСго исслСдования - выявлСниС Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠΉ Π΄ΠΈΡ„Ρ„Π΅Ρ€Π΅Π½Ρ†ΠΈΠ°Ρ†ΠΈΠΈ процСссов воспроизводства ΠΌΠΎΠ»ΠΎΠ΄ΠΎΠ³ΠΎ поколСния Π² России Π½Π° основС кластСрного Π°Π½Π°Π»ΠΈΠ·Π°. Для выдСлСния Π³Ρ€ΡƒΠΏΠΏ Ρ€Π΅Π³ΠΈΠΎΠ½ΠΎΠ², Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ·ΡƒΡŽΡ‰ΠΈΡ…ΡΡ схоТими тСндСнциями Π² этой сфСрС, примСнялся ΠΌΠ΅Ρ‚ΠΎΠ΄ Π°Π³Π»ΠΎΠΌΠ΅Ρ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠΉ иСрархичСской кластСризации. Π’ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π΅ Π°Π½Π°Π»ΠΈΠ·Π° Π±Ρ‹Π»ΠΈ Π²Ρ‹Π΄Π΅Π»Π΅Π½Ρ‹ ΠΏΡΡ‚ΡŒ сСгмСнтов, Ρ€Π°Π·Π»ΠΈΡ‡Π°ΡŽΡ‰ΠΈΡ…ΡΡ спСцификой воспроизводства ΠΌΠΎΠ»ΠΎΠ΄ΠΎΠ³ΠΎ поколСния.ΠŸΡ€ΠΎΠ²Π΅Π΄Π΅Π½Π½ΠΎΠ΅ исслСдованиС ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΡΡ„ΠΎΡ€ΠΌΡƒΠ»ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ ряд Π²Ρ‹Π²ΠΎΠ΄ΠΎΠ² тСорСтичСского ΠΈ ΠΏΡ€ΠΈΠΊΠ»Π°Π΄Π½ΠΎΠ³ΠΎ Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€Π°, Π½Π°Ρ†Π΅Π»Π΅Π½Π½Ρ‹Ρ… Π½Π° ΡΠΎΠ²Π΅Ρ€ΡˆΠ΅Π½ΡΡ‚Π²ΠΎΠ²Π°Π½ΠΈΠ΅ Ρ€Π΅Π°Π»ΠΈΠ·ΡƒΠ΅ΠΌΡ‹Ρ… Π² странС ΠΌΠ΅Ρ€ государствСнной ΠΌΠΎΠ»ΠΎΠ΄Π΅ΠΆΠ½ΠΎΠΉ ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠΈ. ΠšΡ€ΠΎΠΌΠ΅ Ρ‚ΠΎΠ³ΠΎ, исслСдованиС ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΎ, Ρ‡Ρ‚ΠΎ статистичСский инструмСнтарий кластСрного Π°Π½Π°Π»ΠΈΠ·Π° ΠΌΠΎΠΆΠ΅Ρ‚ Ρ€Π°ΡΡΠΌΠ°Ρ‚Ρ€ΠΈΠ²Π°Ρ‚ΡŒΡΡ Π² качСствС эффСктивного ΠΌΠ΅Ρ…Π°Π½ΠΈΠ·ΠΌΠ° создания практичСских Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†ΠΈΠΉ для ΠΎΠΏΠ΅Ρ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ Π²ΠΎΠ·Π½ΠΈΠΊΠ°ΡŽΡ‰ΠΈΡ… Π² ΠΌΠΎΠ»ΠΎΠ΄Π΅ΠΆΠ½ΠΎΠΉ срСдС ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌ ΠΈ поэтому ΠΌΠΎΠΆΠ΅Ρ‚ Π±Ρ‹Ρ‚ΡŒ ΠΈΠ½Ρ‚Π΅Π³Ρ€ΠΈΡ€ΠΎΠ²Π°Π½ Π² ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΡΠΊΡƒΡŽ ΡΠΎΡΡ‚Π°Π²Π»ΡΡŽΡ‰ΡƒΡŽ государствСнной ΠΌΠΎΠ»ΠΎΠ΄Π΅ΠΆΠ½ΠΎΠΉ ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠΈ

    Corporate Family-Friendly Policies: The Possibility of Implementation in Russian Regions

    Get PDF
    Π’ Ρ€Π΅Π°Π»ΠΈΠ·Π°Ρ†ΠΈΡŽ государствСнной пронаталистской ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠΈ ΠΌΠΎΠΆΠ΅Ρ‚ Π²ΠΊΠ»ΡŽΡ‡ΠΈΡ‚ΡŒΡΡ Ρ†Π΅Π»Ρ‹ΠΉ ряд ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Ρ… институтов. ИспользованиС прСдприятиями ΠΊΠΎΡ€ΠΏΠΎΡ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠΉ ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠΈ, ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠΉ Π½Π° сСмьи Ρ€Π°Π±ΠΎΡ‚Π½ΠΈΠΊΠΎΠ², ΠΏΡ€ΠΈ распространСнности Π² Ρ†Π΅Π»ΠΎΠΌ рядС Π΄Ρ€ΡƒΠ³ΠΈΡ… стран Π² России встрСчаСтся достаточно Ρ€Π΅Π΄ΠΊΠΎ. ΠŸΡ€ΠΈ этом Π² России Π½Π°Π±Π»ΡŽΠ΄Π°Π΅Ρ‚ΡΡ высокий ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ Π΄ΠΈΡ„Ρ„Π΅Ρ€Π΅Π½Ρ†ΠΈΠ°Ρ†ΠΈΠΈ российских Ρ€Π΅Π³ΠΈΠΎΠ½ΠΎΠ² ΠΏΠΎ ΠΌΠ½ΠΎΠ³ΠΈΠΌ ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎ-экономичСским показатСлям. ЦСль исслСдования состоит Π² Ρ‚ΠΎΠΌ, Ρ‡Ρ‚ΠΎΠ±Ρ‹, Π²ΠΎ-ΠΏΠ΅Ρ€Π²Ρ‹Ρ…, Π²Ρ‹ΡΠ²ΠΈΡ‚ΡŒ Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Π΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ развития российского ΠΊΠΎΡ€ΠΏΠΎΡ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ сСктора ΠΈ, Π²ΠΎ-Π²Ρ‚ΠΎΡ€Ρ‹Ρ…, ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΠΈΡ‚ΡŒ Ρ‚Π΅ ΠΈΠ· Π½ΠΈΡ…, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΎΠ±Π»Π°Π΄Π°ΡŽΡ‚ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ высоким ΠΏΠΎΡ‚Π΅Π½Ρ†ΠΈΠ°Π»ΠΎΠΌ распространСния ΠΊΠΎΡ€ΠΏΠΎΡ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠΉ ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠΈ, ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠΉ Π½Π° сСмьи Ρ€Π°Π±ΠΎΡ‚Π½ΠΈΠΊΠΎΠ² ΠΈ Π½Π°ΠΏΡ€Π°Π²Π»Π΅Π½Π½ΠΎΠΉ Π½Π° рост роТдаСмости насСлСния этих Ρ€Π΅Π³ΠΈΠΎΠ½ΠΎΠ². Π“ΠΈΠΏΠΎΡ‚Π΅Π·Π° исслСдования состоит Π² возмоТности выявлСния Ρ‚Π°ΠΊΠΈΡ… российских Ρ€Π΅Π³ΠΈΠΎΠ½ΠΎΠ² Π½Π° основС ΠΌΠ½ΠΎΠ³ΠΎΠΌΠ΅Ρ€Π½ΠΎΠΉ классификации ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎ-экономичСских ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ. Для модСлирования российского экономичСского пространства примСнялся иСрархичСский кластСрный Π°Π½Π°Π»ΠΈΠ·, Π·Π°Ρ‚Π΅ΠΌ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡŒ ΠΏΡ€ΠΎΡ„ΠΈΠ»ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ кластСров ΠΏΠΎ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹ΠΌ ΠΏΠ΅Ρ€Π΅ΠΌΠ΅Π½Π½Ρ‹ΠΌ. Использовались Π΄Π°Π½Π½Ρ‹Π΅ ΠΎΡ„ΠΈΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎΠΉ российской статистики ΠΏΠΎ ΡΡƒΠ±ΡŠΠ΅ΠΊΡ‚Π°ΠΌ Π Π€, Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ·ΡƒΡŽΡ‰ΠΈΠ΅ Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠ΅ ΠΊΠΎΡ€ΠΏΠΎΡ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ сСктора. Π’Ρ‹Π΄Π΅Π»Π΅Π½Ρ‹ ΠΏΡΡ‚ΡŒ кластСров российских Ρ€Π΅Π³ΠΈΠΎΠ½ΠΎΠ². Обосновано, Ρ‡Ρ‚ΠΎ Π΄Π²Π° ΠΈΠ· Π½ΠΈΡ… ΠΌΠΎΠ³ΡƒΡ‚ ΡΡ‚Π°Ρ‚ΡŒ ΠΏΠΈΠ»ΠΎΡ‚Π½Ρ‹ΠΌΠΈ для распространСния ΠΏΡ€Π°ΠΊΡ‚ΠΈΠΊ ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠΈ, ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠΉ Π½Π° сСмьи Ρ€Π°Π±ΠΎΡ‚Π½ΠΈΠΊΠΎΠ², занятых Π½Π° этих прСдприятиях. Π’ Π΄Π°Π½Π½Ρ‹Ρ… кластСрах Π½Π°Π±Π»ΡŽΠ΄Π°ΡŽΡ‚ΡΡ спСцифичСскиС дСмографичСскиС (особо Π½ΠΈΠ·ΠΊΠΈΠ΅ Ρ€ΠΎΠΆΠ΄Π°Π΅ΠΌΠΎΡΡ‚ΡŒ ΠΈ ΠΏΠΎΡ‚Π΅Π½Ρ†ΠΈΠ°Π» Π΅Π΅ роста) ΠΈ экономичСскиС (высокая инновационная Π°ΠΊΡ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒ ΠΈ низкая доля ΡƒΠ±Ρ‹Ρ‚ΠΎΡ‡Π½Ρ‹Ρ… прСдприятий, самыС высокиС ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΠΈ Π΄Π΅ΠΌΠΎΠ³Ρ€Π°Ρ„ΠΈΠΈ ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΉ ΠΈ срСдний ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ ΠΊΠΎΠ½Π΅Ρ‡Π½ΠΎΠ³ΠΎ потрСблСния насСлСния) условия. Π‘Π΄Π΅Π»Π°Π½ Π²Ρ‹Π²ΠΎΠ΄, Ρ‡Ρ‚ΠΎ Π² ΠΊΠΎΡ€ΠΏΠΎΡ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠΌ сСкторС этих российских Ρ€Π΅Π³ΠΈΠΎΠ½ΠΎΠ² ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠ°, ориСнтированная Π½Π° сСмьи Ρ€Π°Π±ΠΎΡ‚Π½ΠΈΠΊΠΎΠ², ΠΌΠΎΠΆΠ΅Ρ‚ ΡΡ‚Π°Ρ‚ΡŒ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ вострСбованной для пСрсонала ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΉ, Π²ΠΏΠΎΠ»Π½Π΅ доступной для прСдприятий ΠΈ эффСктивной Π² качСствС Π½ΠΎΠ²ΠΎΠ³ΠΎ инструмСнта дСмографичСской ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠΈ. Π”Π°Π»ΡŒΠ½Π΅ΠΉΡˆΠΈΠ΅ исслСдования ΠΌΠΎΠ³ΡƒΡ‚ Π±Ρ‹Ρ‚ΡŒ связаны с Π°Π½Π°Π»ΠΈΠ·ΠΎΠΌ кСйсов российских прСдприятий, Ρ€Π΅Π°Π»ΠΈΠ·ΡƒΡŽΡ‰ΠΈΡ… ΠΏΠΎΠ΄ΠΎΠ±Π½ΡƒΡŽ ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΡƒ, выявлСниСм Π±Π΅Π½Ρ‡ΠΌΠ°Ρ€ΠΊΠΎΠ², ΠΎΡ†Π΅Π½ΠΊΠΎΠΉ возмоТностСй ΠΌΠ°ΡΡˆΡ‚Π°Π±ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΡ Ρ‚Π°ΠΊΠΎΠ³ΠΎ ΠΎΠΏΡ‹Ρ‚Π° ΠΈ ΠΏΡ€ΠΎΠ³Π½ΠΎΠ·ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π΅Π³ΠΎ дСмографичСских Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ².Various social institutions may be involved in the implementation of the state’s pro-natalist policy. Family-friendly corporate policies, common in many countries, are still quite rare in Russia. At the same time, many socio-economic indicators significantly differ across Russian regions. The study aims to identify regional development models of the Russian corporate sector and determine those models that have the highest potential for dissemination of family-friendly corporate policies aimed at increasing the birth rate of the population in these regions. It is hypothesised that such Russian regions can be identified based on a multidimensional classification of socio-economic indicators. The hierarchical cluster analysis was used to model the Russian economic space. Then, the clusters were further grouped according to additional variables. The article analysed official regional statistics characterising the development of the corporate sector. Five clusters of Russian regions were identified. It is proved that corporate family-friendly policies can be disseminated in two regions in particular. Specific demographic (in particular, low birth rate and growth potential) and economic (high innovative activity, small number of loss-making enterprises, the highest demographic indicators among organisations and the average level of priveate consumption) conditions are observed in these clusters. It is concluded that in the corporate sector of these Russian regions, family-friendly policy may gain popularity among staff. This approach, accessible to enterprises, can act as an effective tool of demographic policy. Further research should focus on the analysis of cases of Russian enterprises implementing family-friendly policies, identification of benchmarks, assessment of the possibilities of scaling such experience and forecasting its demographic results.Π Π°Π±ΠΎΡ‚Π° Π½Π°Π΄ ΡΡ‚Π°Ρ‚ΡŒΠ΅ΠΉ О.М. Π¨ΡƒΠ±Π°Ρ‚ ΠΈ А.П. Π‘Π°Π³ΠΈΡ€ΠΎΠ²ΠΎΠΉ Π² части Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ исслСдования, кластСризации российских Ρ€Π΅Π³ΠΈΠΎΠ½ΠΎΠ² ΠΈ ΠΈΠ½Ρ‚Π΅Ρ€ΠΏΡ€Π΅Ρ‚Π°Ρ†ΠΈΠΈ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠ°Π½Π° Π‘ΠΎΠ²Π΅Ρ‚ΠΎΠΌ ΠΏΠΎ Π³Ρ€Π°Π½Ρ‚Π°ΠΌ ΠŸΡ€Π΅Π·ΠΈΠ΄Π΅Π½Ρ‚Π° Российской Π€Π΅Π΄Π΅Ρ€Π°Ρ†ΠΈΠΈ Π½Π° Π³ΠΎΡΡƒΠ΄Π°Ρ€ΡΡ‚Π²Π΅Π½Π½ΡƒΡŽ ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΡƒ Π²Π΅Π΄ΡƒΡ‰ΠΈΡ… Π½Π°ΡƒΡ‡Π½Ρ‹Ρ… школ Российской Π€Π΅Π΄Π΅Ρ€Π°Ρ†ΠΈΠΈ (НШ-1327.2022.2). ВСорСтичСскоС обоснованиС ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌΡ‹ исслСдования, Π²Ρ‹ΠΏΠΎΠ»Π½Π΅Π½Π½ΠΎΠ΅ Π”. Янь, Ρ€Π΅Π°Π»ΠΈΠ·ΠΎΠ²Π°Π½ΠΎ ΠΏΡ€ΠΈ финансовой ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΠ΅ ΠœΠΈΠ½ΠΈΡΡ‚Π΅Ρ€ΡΡ‚Π²Π° Π½Π°ΡƒΠΊΠΈ ΠΈ Π²Ρ‹ΡΡˆΠ΅Π³ΠΎ образования Российской Π€Π΅Π΄Π΅Ρ€Π°Ρ†ΠΈΠΈ Π² Ρ€Π°ΠΌΠΊΠ°Ρ… ΠŸΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡ‹ развития Π£Ρ€Π°Π»ΡŒΡΠΊΠΎΠ³ΠΎ Ρ„Π΅Π΄Π΅Ρ€Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ унивСрситСта ΠΈΠΌΠ΅Π½ΠΈ ΠΏΠ΅Ρ€Π²ΠΎΠ³ΠΎ ΠŸΡ€Π΅Π·ΠΈΠ΄Π΅Π½Ρ‚Π° России Π‘.Н. Π•Π»ΡŒΡ†ΠΈΠ½Π° Π² соотвСтствии с ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠΎΠΉ стратСгичСского акадСмичСского лидСрства Β«ΠŸΡ€ΠΈΠΎΡ€ΠΈΡ‚Π΅Ρ‚-2030Β».The work of Oksana Shubat and Anna Bagirova in terms of developing a research methodology, clustering Russian regions and interpreting the results was supported by the Council for Grants of the President of the Russian Federation for state support of leading scientific schools of the Russian Federation (NSh-1327.2022.2). Theoretical substantiation of the research by Yan Doudou was supported by the Ministry of Science and Higher Education of the Russian Federation within the framework of the development program of the Ural Federal University as part of the strategic academic leadership program Β«Priority 2030Β»

    The IARC Monographs: Updated procedures for modern and transparent evidence synthesis in cancer hazard identification

    Get PDF
    The Monographs produced by the International Agency for Research on Cancer (IARC) apply rigorous procedures for the scientific review and evaluation of carcinogenic hazards by independent experts. The Preamble to the IARC Monographs, which outlines these procedures, was updated in 2019, following recommendations of a 2018 expert Advisory Group. This article presents the key features of the updated Preamble, a major milestone that will enable IARC to take advantage of recent scientific and procedural advances made during the 12 years since the last Preamble amendments. The updated Preamble formalizes important developments already being pioneered in the Monographs Programme. These developments were taken forward in a clarified and strengthened process for identifying, reviewing, evaluating and integrating evidence to identify causes of human cancer. The advancements adopted include strengthening of systematic review methodologies; greater emphasis on mechanistic evidence, based on key characteristics of carcinogens; greater consideration of quality and informativeness in the critical evaluation of epidemiological studies, including their exposure assessment methods; improved harmonization of evaluation criteria for the different evidence streams; and a single-step process of integrating evidence on cancer in humans, cancer in experimental animals and mechanisms for reaching overall evaluations. In all, the updated Preamble underpins a stronger and more transparent method for the identification of carcinogenic hazards, the essential first step in cancer prevention

    Comparing NED and SIMBAD classifications across the contents of nearby galaxies

    Full text link
    Cataloguing and classifying celestial objects is one of the fundamental activities of observational astrophysics. In this work, we compare the contents of two comprehensive databases, the NASA Extragalactic Database (NED) and Set of Identifications, Measurements and Bibliography for Astronomical Data (SIMBAD) in the vicinity of nearby galaxies. These two databases employ different classification schemes -- one flat and one hierarchical -- and our goal was to determine the compatibility of classifications for objects in common. Searching both databases for objects within the respective isophotal radius of each of the ~1300 individual galaxies in the Local Volume Galaxy sample, we found that on average, NED contains about ten times as many entries as SIMBAD and about two thirds of SIMBAD objects are matched by position to a NED object, at 5 arcsecond tolerance. These quantities do not depend strongly on the properties of the parent galaxies. We developed an algorithm to compare individual object classifications between the two databases and found that 88% of the classifications agree; we conclude that NED and SIMBAD contain consistent information for sources in common in the vicinity of nearby galaxies. Because many galaxies have numerous sources contained only in one of NED or SIMBAD, researchers seeking the most complete picture of an individual galaxy's contents are best served by using both databases.Comment: 11 pages, 11 figures, 2 tables, to be published in MNRA

    A quantitative analysis of fertility dynamics in small cities of Russia

    Full text link
    The results of comparing the fertility dynamics across Russia and in small cities of Ural in 2006-2010 are provided. Certain components have been studied using structural decomposition. According to the analysis, the fertility behavior of population in small cities is more susceptible to the influence of different factors than in Russia in general. Special measures are necessary to encourage fertility in small cities. In these measures, the specifics of demographic dynamics, population, and lifestyle in small cities must be considered, as well as the higher potential efficiency of their external effects in comparison with big cities. Β© 2012 Pleiades Publishing, Ltd

    Methodology for analyzing the demographic potential of Russian regions using fuzzy clustering

    No full text
    The research is aimed at developing and testing a methodology for analyzing demographic potential of Russian regions. The initial data are the regional official Russian statistics indicators. We proposed an approach for assessing the demographic potential based on a differentiated analysis of its quantitative and qualitative components. The paper presents the developed methodology for estimating the demographic potential, combining multidimensional data classification (fuzzy clustering) and expert assessments. Application of the proposed methodology revealed five specific models in the demographic space of Russia. The first model combines a low level of quantitative components of the demographic potential with a high level of its quality. The second model is characterized by average levels of both components. In the third model, an average level of the quantitative component is accompanied by a rather low level of the demographic potential’s quality. The fourth model combines a high level of quantitative component of the demographic potential with an imbalance of its quality indicators, and the fifth β€” a high level of both components. We have obtained estimates for the quantitative and qualitative components of the demographic potential for each region and rated them. This has allowed identifying β€œanchor”-regions and β€œdriver”-regions, as well as regions with the most and least balanced assessments of the two components. The paper shows the potential application of the developed methodology. In particular, this methodology allows identifying groups of regions, which need the implementation of specific measures for increasing the quantity and improving the quality of the demographic potential. The most significant limitation of the developed methodology is the lack of a complete set of indicators in the official Russian statistics for assessing the demographic potential. Future research will be aimed at applying fuzzy clustering methods to various demographic phenomena, since this approach takes into account the natural uncertainty, which is typical for such processes and, therefore, makes the results of demographic analysis more formalized and valid. Β© 2019 The Linguistic Association of Finland. All Rights Reserved.Council on grants of the President of the Russian FederationThe article has been prepared within the research project β€œFertility and parenting in Russian regions: models, invigoration strategies, forecastsβ€œ, supported by the President of Russian Federation (the grant No. NSh-3429.2018.6)

    Forecasting the Number of Grandparents in Sverdlovsk Oblast

    Full text link
    Π£Π²Π΅Π»ΠΈΡ‡Π΅Π½ΠΈΠ΅ стСпСни участия ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»Π΅ΠΉ Π² ΠΆΠΈΠ·Π½Π΅Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ своих Π²Π½ΡƒΠΊΠΎΠ² ΠΈΠΌΠ΅Π΅Ρ‚ ряд дСмографичСских, ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Ρ…, экономичСских эффСктов. Π’ связи с этим ΠΎΠ΄Π½ΠΈΠΌ ΠΈΠ· основных ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ Π΄Π΅ΠΌΠΎΠ³Ρ€Π°Ρ„ΠΈΠΈ ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΡ‚Π²Π° выступаСт Ρ‡ΠΈΡΠ»Π΅Π½Π½ΠΎΡΡ‚ΡŒ ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»Π΅ΠΉ Π² общСствС. На основС авторской ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ, Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½Π½ΠΎΠΉ Π½Π° Π±Π°Π·Π΅ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ прогнозирования числСнности ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»Π΅ΠΉ Π² странС Π² Ρ†Π΅Π»ΠΎΠΌ, Π² ΡΡ‚Π°Ρ‚ΡŒΠ΅ прогнозируСтся Ρ‡ΠΈΡΠ»Π΅Π½Π½ΠΎΡΡ‚ΡŒ Π±Π°Π±ΡƒΡˆΠ΅ΠΊ Π² БвСрдловской области Π½Π° 2021–2025 Π³Π³. РасчСты ΡΠ²ΠΈΠ΄Π΅Ρ‚Π΅Π»ΡŒΡΡ‚Π²ΡƒΡŽΡ‚ ΠΎ Ρ‚ΠΎΠΌ, Ρ‡Ρ‚ΠΎ Π² БвСрдловской области Π½Π΅Ρ‚ явной Ρ‚Π΅Π½Π΄Π΅Π½Ρ†ΠΈΠΈ ΠΊ измСнСнию этого показатСля Π² 5-Π»Π΅Ρ‚Π½Π΅ΠΉ пСрспСктивС, доля Π±Π°Π±ΡƒΡˆΠ΅ΠΊ Π² насСлСнии Ρ€Π΅Π³ΠΈΠΎΠ½Π° Ρ‚Π°ΠΊΠΆΠ΅ являСтся устойчивой. ΠŸΡ€Π°ΠΊΡ‚ΠΈΡ‡Π΅ΡΠΊΠ°Ρ Ρ†Π΅Π½Π½ΠΎΡΡ‚ΡŒ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² состоит Π² Ρ‚ΠΎΠΌ, Ρ‡Ρ‚ΠΎ ΠΏΠΎΠ½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΠΏΡ€ΠΎΠ³Π½ΠΎΠ·ΠΈΡ€ΡƒΠ΅ΠΌΡ‹Ρ… количСствСнных Ρ‚Π΅Π½Π΄Π΅Π½Ρ†ΠΈΠΉ ΠΌΠΎΠΆΠ΅Ρ‚ ΠΏΠΎΠ΄ΡΠΊΠ°Π·Π°Ρ‚ΡŒ ΠΈΡΠΏΠΎΠ»Π½ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹ΠΌ ΠΎΡ€Π³Π°Π½Π°ΠΌ ΡΡƒΠ±ΡŠΠ΅ΠΊΡ‚Π° Π Π€, ΠΎΡ‚Π²Π΅Ρ‡Π°ΡŽΡ‰ΠΈΠΌ Π·Π° Π΄Π΅ΠΌΠΎΠ³Ρ€Π°Ρ„ΠΈΡ‡Π΅ΡΠΊΡƒΡŽ ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΡƒ, управлСнчСскиС Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ Π±ΡƒΠ΄ΡƒΡ‚ Π½Π°ΠΏΡ€Π°Π²Π»Π΅Π½Ρ‹ Π½Π° ΡƒΠ»ΡƒΡ‡ΡˆΠ΅Π½ΠΈΠ΅ ΠΈ качСствСнных характСристик ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΡΡ‚Π²Π°, Π° ΠΈΠΌΠ΅Π½Π½ΠΎ, ΠΏΠΎΠ²Ρ‹ΡˆΠ΅Π½ΠΈΠ΅ Π΄ΠΎΠ»ΠΈ ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»Π΅ΠΉ, Π°ΠΊΡ‚ΠΈΠ²Π½ΠΎ ΡƒΡ‡Π°ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΡ… Π² ΠΆΠΈΠ·Π½Π΅Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ Π²Π½ΡƒΠΊΠΎΠ², Π² числСнности всСх ΠΏΡ€Π°Ρ€ΠΎΠ΄ΠΈΡ‚Π΅Π»Π΅ΠΉ Ρ€Π΅Π³ΠΈΠΎΠ½Π°.An increase in the participation of grandparents in the life of their grandchildren has demographic, social, and economic effects. In this regard, one of the main indicators of the demography of grandparenthood is the number of grandparents in society. Using the authors’ approach developed based on the methodology for forecasting the number of grandparents in the country as a whole, the present research forecasts the number of grandmothers in Sverdlovsk oblast for 2021–2025. Calculations show that, in Sverdlovsk oblast, this indicator is unlikely to change in the 5-year perspective; the share of grandmothers in the population of the region is also stable. Understanding of the perspective quantitative trends can prompt the executive bodies of Russian regions responsible for demographic policy to make decisions aimed at improving the qualitative characteristics of grandparents, namely, increasing the share of grandparents actively involved in the life of grandchildren in the number of all grandparents in the region.ИсслСдованиС Π²Ρ‹ΠΏΠΎΠ»Π½Π΅Π½ΠΎ ΠΏΡ€ΠΈ финансовой ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΠ΅ РЀЀИ Π² Ρ€Π°ΠΌΠΊΠ°Ρ… Π½Π°ΡƒΡ‡Π½ΠΎΠ³ΠΎ ΠΏΡ€ΠΎΠ΅ΠΊΡ‚Π° β„– 20–011–00280.The article has been prepared with the financial support of the Russian Foundation for Basic Research, the scientific project No. 20–011–00280

    Simple reproduction of the population: experience of normativ eforecasting

    Full text link
    Π’ ΡΡ‚Π°Ρ‚ΡŒΠ΅ прСдставлСны Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ Π½ΠΎΡ€ΠΌΠ°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ дСмографичСского прогнозирования Π½Π° основС расчСта суммарного коэффициСнта роТдаСмости, Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΠΎΠ³ΠΎ для обСспСчСния простого воспроизводства насСлСния. ΠŸΡ€Π΅Π΄ΡΡ‚Π°Π²Π»Π΅Π½Ρ‹ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½Ρ‹Π΅ ΠΏΡƒΡ‚ΠΈ достиТСния ΠΎΠ±ΠΎΠ·Π½Π°Ρ‡Π΅Π½Π½ΠΎΠΉ Ρ†Π΅Π»ΠΈ.The article presents the results of the normative population forecasting by calculating the total fertility rate required for simple reproduction of the population. Possiblewaysofachievingthedesignatedgoalarepresented
    corecore