[組織經濟學Seminar]“Thugs-for-Hire”: State Coercion and Everyday Repression in China
發文時間:2016-03-14
中國人民大學企業與組織研究中心 組織經濟學Seminar   總第69期 【OE201601】  
組織經濟學(Organizational Economics)Seminar由中國人民大學企業與組織研究中心(CFOS)主辦。CFOS的宗旨是,利用現代經濟學方法研究中國的企業、政府、市場和非營利組織的重大問題,推動企業理論、契約理論和制度經濟學的研究與教學。關注CFOS,請訪問http://CFOS.ruc.edu.cn。
 
時間:2016年3月17日(周四)12:00-13:30
地點:明德主樓734會議室
主講:王慧玲
主題:“Thugs-for-Hire”: State Coercion and Everyday Repression in China(“鮑魚之肆”的雇傭:國家強制與鎮壓)
摘要:This paper examines “thugs-for-hire” (TFH) as a form of state coercion and everyday repression. Violence is central to what TFH do and what they deliver. TFH serves as an extension of the state, implementing illegal measures or unpopular policies upon a recalcitrant population. They lend support to the state’s coercive capacity and bolster its “despotic power”. Taking the shape of third-party violence, TFH constitutes a form of privatized covert repression, which allows the state to evade responsibility. Drawing comparisons with the Mafiaosi, this study underlines why TFH exist, who they are, what they deliver, how they function and their relationship with the state. Third-party violence is commonly deployed by local states to evict homeowners, enforce one-child policy, collect exorbitant exactions, and deal with petitioners and protestors in China. This study contributes to state repression literature by elaborating on the role of thugs and gangsters as a repressive measure. The fact that TFH are commonly hired by local states to get job done illustrates the distinctive fragmented authoritarian nature of the Chinese state.
 
演講者簡介:Lynette H. Ong is an associate professor of political science at the Asian Institute, Munk School of Global Affairs, The University of Toronto. Her publications have appeared in Comparative Politics, International Political Science Review, China Quarterly, Foreign Affairs, among others. She is the author of Prosper or Perish: Rural Credit and Fiscal Systems in China, Cornell University Press, 2012.
 
 
中國人民大學經濟學院 人大企業與組織研究中心 國發院新政治經濟學研究中心 人大微觀數據與實證方法研究中心 2016年3月14日