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"It's (Not) Like the Flu": Expert Narratives and the COVID-19 Pandemic in Mainland China, Hong Kong, and the United States.
Au, Larry; Fu, Zheng; Liu, Chuncheng.
  • Au L; Department of Sociology The City College of New York New York NY.
  • Fu Z; Department of Sociology Columbia University New York NY.
  • Liu C; Department of Sociology University of California San Diego La Jolla CA.
Sociol Forum (Randolph N J) ; 2022 Jun 09.
Article in English | MEDLINE | ID: covidwho-1883232
ABSTRACT
We trace the crafting of expert narratives during the initial months of the COVID-19 pandemic in Mainland China, Hong Kong, and the United States. By expert narratives, we refer to how experts drew different lessons from past disease experiences to guide policymakers and the public amidst uncertainty. These expert narratives were mobilized in different sociopolitical contexts, resulting in varying configurations of expertise networks and allies that helped contain and mitigate COVID-19. In Mainland China, experts carefully advanced a managed narrative, emphasizing the new pandemic akin to the 2003 SARS outbreak can be managed while destressing the similar mistakes the government made during the two crises. In Hong Kong, experts invoked a distrust narrative, pointing to a potential coverup of COVID-19 similar to SARS, activating allies in civil society to pressure policymakers to act. In the United States, experts were mired in a contested narrative and COVID-19 was compared to different diseases; varying interpretations of COVID-19's consequences was exacerbated by political polarization. In expert narratives, the resonance of the past is emergent the past becomes a site of struggle and a cultural object that is presented as potentially useful in solving problems of the present.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Qualitative research Language: English Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Qualitative research Language: English Year: 2022 Document Type: Article