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Improving the framework for analyzing community resilience to understand rural revitalization pathways in China

Improving the framework for analyzing community resilience to understand rural revitalization pathways in China
Improving the framework for analyzing community resilience to understand rural revitalization pathways in China
Community resilience (CR) is receiving increasing attention within rural studies, especially as many rural communities, worldwide, appear to be gradually declining. In 2017, the Chinese government outlined a “rural revitalization strategy”, which recommends four pathways for revitalizing rural communities and helping them to withstand external shocks. To advance understanding of rural revitalization pathways in China, we developed an improved conceptual framework for analyzing CR. The study's innovativeness lies in its integration of principles for building social-ecological resilience into the framework, and the provision of a step-by-step process for analyzing CR. We analyzed major risks and shocks faced within each of the four revitalization pathways in China on the basis of a literature review, and identified key slow variables and their mutual effects as well as corresponding thresholds and core indicators. Our results showed that slow-onset disturbances, which differ greatly among the four pathways, pose the greatest threat to CR. However, the impacts of slow variables on rural communities are often ignored as they are difficult to observe. Therefore, rules should be introduced to avoid shortsighted decisions in policymaking. Our findings can provide valuable inputs for the implementation of rural revitalization pathways in China. Moreover, they highlight the need for more empirical case studies focusing on diversified pathways.
0743-0167
287-294
Zhang, Ruoyan
cbb6e751-2424-4577-9a17-5ff80f12cebb
Yuan, Yuan
7ba078d3-bebb-4e96-ad64-1927de596914
Li, Hongbo
a698dd78-4c20-402e-bfb5-3c5f55d99225
Hu, Xiao
d6f3fb9c-8e5e-45ec-91bf-f2549a50c7a0
Zhang, Ruoyan
cbb6e751-2424-4577-9a17-5ff80f12cebb
Yuan, Yuan
7ba078d3-bebb-4e96-ad64-1927de596914
Li, Hongbo
a698dd78-4c20-402e-bfb5-3c5f55d99225
Hu, Xiao
d6f3fb9c-8e5e-45ec-91bf-f2549a50c7a0

Zhang, Ruoyan, Yuan, Yuan, Li, Hongbo and Hu, Xiao (2022) Improving the framework for analyzing community resilience to understand rural revitalization pathways in China. Journal of Rural Studies, 94, 287-294. (doi:10.1016/j.jrurstud.2022.06.012).

Record type: Article

Abstract

Community resilience (CR) is receiving increasing attention within rural studies, especially as many rural communities, worldwide, appear to be gradually declining. In 2017, the Chinese government outlined a “rural revitalization strategy”, which recommends four pathways for revitalizing rural communities and helping them to withstand external shocks. To advance understanding of rural revitalization pathways in China, we developed an improved conceptual framework for analyzing CR. The study's innovativeness lies in its integration of principles for building social-ecological resilience into the framework, and the provision of a step-by-step process for analyzing CR. We analyzed major risks and shocks faced within each of the four revitalization pathways in China on the basis of a literature review, and identified key slow variables and their mutual effects as well as corresponding thresholds and core indicators. Our results showed that slow-onset disturbances, which differ greatly among the four pathways, pose the greatest threat to CR. However, the impacts of slow variables on rural communities are often ignored as they are difficult to observe. Therefore, rules should be introduced to avoid shortsighted decisions in policymaking. Our findings can provide valuable inputs for the implementation of rural revitalization pathways in China. Moreover, they highlight the need for more empirical case studies focusing on diversified pathways.

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Accepted/In Press date: 29 June 2022
e-pub ahead of print date: 12 July 2022
Published date: 12 July 2022

Identifiers

Local EPrints ID: 489936
URI: http://eprints.soton.ac.uk/id/eprint/489936
ISSN: 0743-0167
PURE UUID: f1895a6f-22b8-45ca-96cd-03f792fee18f

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Date deposited: 07 May 2024 17:00
Last modified: 13 May 2024 16:33

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Contributors

Author: Ruoyan Zhang
Author: Yuan Yuan
Author: Hongbo Li
Author: Xiao Hu

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