Uneven Urban Resilience: The Economic Adjustment and Polarization of Russia’s Cities

Golubchikov, Oleg; Махрова, А. Г.; Badyina, Anna; Brade, Isolde

doi:10.1057/9781137415080_15

Cited by 6 publications

(4 citation statements)

References 17 publications

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“…An ever-increasing amount of resources is required for managing the built-up territories, while the demand for new housing is soaring due to several factors. The first factor is a colossal inflow of population into large cities due to uneven development of the country in the aftermath of the collapse of the Soviet distributive model; this manifests itself in hyper-concentration of population and resources in large cities and a rapid exodus of population from small and middle-sized cities and towns (Golubchikov et al 2013). The second factor is an increased demand for cheap, mass-produced commercial housing due to low income, unreliable institutions of commercial rent, and the inaccessibility of social housing for the majority of Russia's urbanized population.…”

Section: Causes Of Extensive Developmentmentioning

confidence: 99%

Large Housing Estates under Socialism

2024

Architekturen

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Harnessing large urban housing estates in former socialist countries as a resource for the future housing supply requires innovative and practicable strategies and concepts. What are the challenges to be overcome? How can the often mono-structural estates be altered, and how can spatial and cultural identities be reinforced? Which role does the community play in these former socialist neighborhoods? The contributors to this volume present perspectives from different disciplines, both in academia and practice. The exchange of international experiences creates the base for further debate and learning and provides insight into the multiplicity of challenges and approaches today.

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Section: Causes Of Extensive Developmentmentioning

confidence: 99%

Large Housing Estates under Socialism

2024

Architekturen

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“…As a result, their intergenerational socio-economic mobility remains significantly constrained. These areas are characterized by a lack of public services and home ownership security, a dense population [17], vulnerability to eviction and poor population status [18]. Furthermore, unauthorized use of electricity and water is found in almost every location [19], inadequate basic services and several rented houses [20], as well as high vulnerability to diseases [21], are also prevalent.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Spatial Data on Accuracy Values of Slum Area Distribution in Palembang City, Indonesia

Sukmaniar,

Listyaningsih,

Muhidin

2023

Preprint

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Urbanization triggers the emergence of slums in urban areas. Palembang is one of the Indonesian cities with slum settlements. This research aimed to analyze the interpolation of slum positions in Palembang and their distribution pattern using kernel density analysis and by modeling spatial data on accuracy values. It employed a quantitative method with a survey approach. Samples were selected using proportional random sampling from families in 64 slum areas across the 13 districts in the city, and their positions were recorded with a GPS device and then processed and mapped in ArcGIS. The data were analyzed with inverse distance weighted, kernel density, and spatial data modeling. Results showed that slum areas near the riverbanks had high population density, while those located further were lower. The values obtained from the kernel density analysis varied from 0 to 58.1123, while the inverse distance weighted showed a value range of 2.26745–380.991. The spatial data modelling analysis demonstrated that the distribution of slum areas was widely spread along the Musi River, with an accuracy value of 96.8%, which falls within the range of >0.9-1.

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“…2019; Golubchikov et al . 2015). Utilizing rare or previously classified archival data allows to fill some of the gaps in understanding of the evolving sociopolitical structuring of the Soviet city, the changing political goals and associated data production.…”

Section: Introductionmentioning

confidence: 99%

“…The demise of the Communist system has opened opportunities for studies of urban sociospatial differentiation in the post-Communist cities of Eastern Europe and the former USSR; analyses of their inner differentiation often focus on post-Soviet Moscow (e.g. Sidorov 1992;Vendina 1997;Vendina 2002;Vendina et al 2019;Golubchikov et al 2015). Utilizing rare or previously classified archival data allows to fill some of the gaps in understanding of the evolving sociopolitical structuring of the Soviet city, the changing political goals and associated data production.…”

Section: Introductionmentioning

confidence: 99%

Sociospatial Differentiation in Stalinist Moscow

Sidorov

2022

Tijd voor Econ & Soc Geog

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In 1917, the Bolsheviks took power in Russia under the banner of equality. Within the city, their aspiration to eliminate the core-periphery sociospatial disparities resulted in dividing Moscow's privileged historic centre among its peripheral districts. This attempt to design districts of similar socio-economic composition was short-lived. Already in the 1930s, corresponding with the rise of the Stalinist state, the city centre partially re-appeared in the form of the newly established smaller sectorial districts that were eliminated only after Stalin's death. Utilizing previously classified archival data of the 1939 population census, this paper sheds light on the sociospatial differentiation of Stalinist Moscow by comparing its central districts to the rest of the city as well as to the Bolshevik zoning of the 1920s. This analysis posits that the Bolshevik ideal of territorial equality was not achieved: politically, ethnically and socially, Stalinist Moscow in the late 1930s remained spatially unequal.

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Uneven Urban Resilience: The Economic Adjustment and Polarization of Russia’s Cities

Cited by 6 publications

References 17 publications

Large Housing Estates under Socialism

Large Housing Estates under Socialism

Modeling of Spatial Data on Accuracy Values of Slum Area Distribution in Palembang City, Indonesia

Sociospatial Differentiation in Stalinist Moscow

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