Rebuilding the Tower of Babel: language policy and political trust in China

My dissertation explores how authoritarian governments use language policy to impact public political trust. Based on a comprehensive examination through survey analyses, experiments, and large-scale text analyses, my research demonstrates that authoritarian governments, such as in China, can use language policy as a political tool to influence citizens’ political attitudes. In particular, language policy empowers the official language used by government representatives, such as street-level bureaucrats, reinforcing their political identities and enhancing citizens' trust in them. Using an original randomized experiment in China based on a new sociolinguistic technique, my research finds robust evidence that listeners hold significantly more trust in bureaucrats who speak the official language than in those who speak dialects, even if the respondent and government representative share the same dialect. Furthermore, my research shows that language not only influences citizens' political trust but also their understanding of political concepts. Using a computer-assisted text analysis of over one million articles from the official newspaper of the dominant party of China from 1946-2003, I indicate a refocusing strategy by which the official discourse about democracy manipulates the meaning of democracy in the Chinese political language without contradicting with the Western democratic values, while simultaneously preserving the authoritarian regime. Drawing on multiple waves of nationally representative surveys from China, my dissertation also identifies distinctive effects of improving listening, speaking, and relative proficiencies of Putonghua on Chinese citizens' political interest, efficacy, pursuit, and institutional-based political trust. This study contributes to political science, and even the entire social science by justifying the important role of language in human social and political lives and turning the research focus from language content to language context.