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Keystone theories of postcrisis discourse: Communication Theory of Resilience and Discourse of Renewal.

  • Published In: Journal of Contingencies & Crisis Management, 2024, v. 32, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Seeger, Matthew W.; Nowling, William; Seeger, Henry S. 3 of 3

Abstract

Theories of resilience are keystones for understanding how individuals, small groups, organizations, and communities arrive at collective meaning, resolve uncertainty, and respond to crisis events. In response to a crisis, organizations can pursue three goals: Returning to the prior equilibrium, creating a new equilibrium with new processes and policies, or a combination of the two. Theories of resilience and renewal address these responses. Resilience has been applied in a diverse set of academic fields as well as in public policy discussions and in popular culture. This broad application, however, has resulted in conceptual confusion and conflicting interpretations. We explore the origins of resilience and its characteristics. We then review two discipline-specific postcrisis theories, The Communication Theory of Resilience and Discourse of Renewal. We ask, how can these theories enrich understanding of postcrisis adaptive processes and create for a more comprehensive picture of how individuals and organizations respond to crises? Taken together, they provide a broader framework for understanding the role of postcrisis discourse and informing practitioners in the enactment of responses. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Contingencies & Crisis Management. 2024/03, Vol. 32, Issue 1, p1
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2024
  • ISSN:0966-0879
  • DOI:10.1111/1468-5973.12533
  • Accession Number:175125169
  • Copyright Statement:Copyright of Journal of Contingencies & Crisis Management 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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