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Multilayered “Unification”: The Examination of Government Practices in the PAP

  • Shaoying Zhang
  • Derek McGhee
Part of the Politics and Development of Contemporary China book series (PDCC)

Abstract

Following our discussion about the problems of Xinjiang in Chapter 3, in this chapter we will examine how the Chinese government is to tackle them. To use SKAD’s terminology, this is an examination of the infrastructural and organizational changes of discourse production after the 5 July riots in Xinjiang (Keller 2011: 56). In this chapter, we will explore the infrastructures of implementation that emerged out of the PAP, how the policies contained in the PAP were designed to tackle “problems” in Xinjiang. This will enable us to examine, following James Ferguson (1990), how the instrumental effects produced by the practices of officials in particular, and the unintended consequences of previous policies in Xinjiang in general are in the service of state power. That is, how the failures of previous programmes actually facilitated China’s authority to re-responsibilize its internal infrastructure, build a new shared identity among communist officials, securitize society, tighten control on religion and create more economic development opportunities in Xinjiang. In this case, the failure of previous programmes is construed as further proof of the need to reinforce and extend the power of the state (Dreyfus and Rabinow 1982: 196) in Xinjiang. This is an example of what Carol Bacchi calls the productive role of government in shaping “problems” (2009: 2). Beyond Ferguson’s suggestions, there is also a case that securitization in Xinjiang is more like a politicization of social problems that enables China to take extreme measures to crack down not only on violent “terrorists”, but also “dissidents”.

Keywords

Central Government Communist Party Religious Activity Local Official Bilingual Education 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Shaoying Zhang and Derek McGhee 2014

Authors and Affiliations

  • Shaoying Zhang
    • 1
  • Derek McGhee
    • 2
  1. 1.Yunnan Normal UniversityChina
  2. 2.University of SouthamptonUK

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