Localising the ‘Characteristic Town’: A Socio-Spatial Framework for Understanding the Everyday Rural Urbanisation of China’s Hinterlands

Author:

Lynam Ava1

Affiliation:

1. Center for Cultural Studies on Science and Technology in China, Technische Universität Berlin, Berlin 10553, Germany

Abstract

The shift towards an urbanised world is generating profound social, economic, and environmental complexities. Agglomerating regions require new understandings to capture the socio-spatial restructuring of this planetary urbanisation. In China, top-down rural urbanisation policies such as the Characteristic Town, or tese xiaozhen, address urban-rural polarisation through a ‘one-town-one-characteristic-industry’ model aiming to generate localised rural economic development. Characteristic Towns have been criticised as only superficially addressing local challenges, imposing tabula-rasa developments that extend urbanisation into rural areas, excluding vulnerable groups. Within the mega-urban Yangtze River Delta corridor, the Smart Moulding Town in Huangyan-Taizhou’s hinterland is leading regional industrial upgrading processes, epitomising visions of politicians, planners, and developers. The urban-rural interface is undergoing a fragmented transition towards industrialisation while villagers adapt their local economies and everyday practices, generating new socio-spatial typologies for dwelling. This inductive research reveals the role of villagers in shaping, and being shaped by, top-down rural urbanisation programs. The multi-scalar theoretical framework is structured around private, collective, and institutional layers of dwelling, interrogated through Lefebvre’s spatial production theory. Uncovering hybrid urban-rural qualities and actor networks, the empirical findings illustrate that villagers’ micro-scale tactics are deeply embedded in trans-local industrialisation processes, redefining rural identities and defying top-down spatial compartmentalisation by negotiating informality.

Publisher

AccScience Publishing

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