A geodemographic classification of sub-districts to identify education inequality in Central Beijing. (July 2018)

• Record Type: Journal Article
• Authors: Xiang, Lili; Stillwell, John; Burns, Luke; Heppenstall, Alison; Norman, Paul
• Is Part Of: Computers, environment and urban systems. Volume 70(2018)
• Page Start: 59
• Page End: 70
• Publication Date: 2018-07
• Subjects: Geodemographic classification -- Education inequality -- Hukou -- Nearby enrolment -- China; City planning -- Data processing -- Periodicals; Regional planning -- Data processing -- Periodicals; 303.4834
• DOI: 10.1016/j.compenvurbsys.2018.02.002
• Languages: English
• ISSNs: 0198-9715

Abstract

Abstract: The paper explores the use of geodemographics as a means of assessing potential inequality in access to compulsory education. The article argues that applying an area classification, one of the first in China, allows consideration of multi-dimensional, socio-spatial influences which affect school choice. The ideas are illustrated through a case study of central Beijing. Variables from the 2010 Census have been used to create a sub-district classification to identify whether pupils are living in more or less advantaged locations for access to schools, given China's specific institutional environment. The influence of 'hukou' (the Chinese residential registration system) on the distances that pupils travel to school and the quality of schools that pupils can attend are discussed in detail. Recognition of areas that are most appropriate for additional investment can help improve the efficiency and equity of the allocation of resources to schools. This study also provides new knowledge about the evolution of urban social space, explaining why the implementation of 'nearby enrolment' policy can be both inefficient and inequitable. Highlights: A first geodemographic classification relating to public sector function in China is constructed for central Beijing. It offers a novel data exploration tool to yield new ideas for analysis of the inequality in the demand for education. The influence of four types of 'hukou' on pupils' travel distance and education quality are considered for the first time. It generates new insights to explain why the implementation of nearby enrolment policy may be inefficient in Beijing. It presents an innovative radial plot that the distinctive variables of each cluster are immediately distinguishable.