JOURNAL ARTICLE

Transition from Idealized Science to Culture of Skepticism in South Korea: Micro-Level Evidence for the Two-Culture Model of Public Understanding of Science.

  • Published In: International Journal of Public Opinion Research, 2023, v. 35, n. 3. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Kim, Sei-Hill; Oh, Sang-Hwa; Zain, Ali; Heo, Yujin; Jun, Jungmi 3 of 3

Abstract

This study examines public perceptions of science in South Korea through the lens of the two-culture model of public understanding of science, which suggests that a society's shift from industrializing to post-industrial stages corresponds with a transition from idealized views of science to skepticism. Using 2011 national survey data, the research finds that older South Koreans, who experienced the country's rapid industrialization, tend to hold more positive and idealized perceptions of science compared to younger generations raised in a post-industrial context, who exhibit greater skepticism. The study identifies several mediating factors—including perceived importance of economic development, scientific knowledge, political ideology, perceived uncertainty of scientific risks, and formal education—that help explain these generational differences. Overall, the findings support the two-culture thesis by demonstrating how South Korea's unique historical and socio-political trajectory has shaped contrasting scientific cultures within its population.

Additional Information

  • Source:International Journal of Public Opinion Research. 2023/09, Vol. 35, Issue 3, p1
  • Document Type:Article
  • Subject Area:Politics and Government
  • Publication Date:2023
  • ISSN:0954-2892
  • DOI:10.1093/ijpor/edad026
  • Accession Number:171896169
  • Copyright Statement:Copyright of International Journal of Public Opinion Research is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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