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Digital Library

of the European Council for Modelling and Simulation

 

Title:

Identifying regional models of active grandparenting in Russia based on cluster analysis

Authors:

Oksana Shubat, Irina Shmarova

Published in:

 

 

(2022). ECMS 2022, 36th Proceedings
Edited by: Ibrahim A. Hameed, Agus Hasan, Saleh Abdel-Afou Alaliyat, European Council for Modelling and Simulation.

 

DOI: http://doi.org/10.7148/2022

ISSN: 2522-2422 (ONLINE)

ISSN: 2522-2414 (PRINT)

ISSN: 2522-2430 (CD-ROM)

 

ISBN: 978-3-937436-77-7
ISBN: 978-3-937436-76-0(CD)

 

Communications of the ECMS , Volume 36, Issue 1, June 2022,

Ă…lesund, Norway May 30th - June 3rd, 2022

 

Citation format:

Oksana Shubat, Irina Shmarova (2022). Identifying regional models of active grandparenting in Russia based on cluster analysis, ECMS 2022 Proceedings Edited By: Ibrahim A. Hameed, Agus Hasan, Saleh Abdel-Afou Alaliyat, European Council for Modeling and Simulation.

doi:10.7148/2022-0078

DOI:

https://doi.org/10.7148/2022-0078

Abstract:

One of the important social roles the elderly perform is that of grandparents. Our study aims to identify groups of Russian regions with similar models of grandparental activity. The research focuses only on grandmothers. To determine these models, we applied the hierarchical cluster analysis. We used indicators that characterize potential (based on the age criterion) and active (based on intensive involvement in caring for grandchildren) grandparenting in Russian regions. In the process of clustering, we use the growth rates of active grandmothers in the total number of potential grandmothers in 2011-2014, 2014-2016, 2016-2018. The analysis based on the Ward method and the Euclidean distance allowed us to identify 4 models of grandparental activity (regarding grandmothers) in Russian regions. The models differ significantly in the specifics of changes in the degree of grandmothers' involvement in caring for their grandchildren. These models provide the framework for developing specific demographic policy measures with the regional heterogeneity in mind..

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