JOURNAL ARTICLE

Disenchanted comradery: The social process of persistent mistrust among North Korean refugees in the United Kingdom.

  • Published In: Population Space & Place, 2025, v. 31, n. 1. P. 1 1 of 3

  • Database: Sociology Source Ultimate 2 of 3

  • Authored By: Shin, Hwajin; Son, Inseo 3 of 3

Abstract

Previous research on refugees demonstrates that low interpersonal trust impedes their social adaptation in host countries. However, a pervasive sense of low trust among refugees, particularly within their own communities, remains less understood. Using survey and interview data from North Korean refugees in London, United Kingdom, this study probes the social processes that foster mistrust towards their in‐group peers. The quantitative findings show that refugees have created a close‐knit, in‐group community bounded by strong emotional bonds that, counterintuitively, do not necessarily develop into mutual trust. The interviews show that the asylum‐seeking experiences and the cultural norms they bring from North Korea continue to shape how they perceive in‐group contacts as potential threats. Additionally, interactions with locals, especially South Korean immigrants, amplify perceptions of inferiority and mistrust towards in‐group members. These findings illuminate the complex social process through which mutual mistrust continues to persist among refugees, offering insights into the multifaceted challenges refugees face in resettlement. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Population Space & Place. 2025/01, Vol. 31, Issue 1, p1
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2025
  • ISSN:1544-8444
  • DOI:10.1002/psp.2856
  • Accession Number:183850667
  • Copyright Statement:Copyright of Population Space & Place is the property of Wiley-Blackwell 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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