JOURNAL ARTICLE
Book Review: Review of The Continuing Storm: Learning from Katrina, 2022.
Published In: International Journal of Mass Emergencies & Disasters, 2024, v. 42, n. 1. P. 82 1 of 3
Database: Sociology Source Ultimate 2 of 3
Authored By: Gill, Duane A. 3 of 3
Abstract
"The Continuing Storm: Learning from Katrina, 2022" by Kai Erikson and Lori Peek is the final installment of the Katrina Bookshelf Series by the University of Texas Press. The book explores the events and aftermath of Hurricane Katrina, shedding light on overlooked aspects of the disaster. The authors analyze the social factors, location decisions, and infrastructure that played a role in the devastation of New Orleans. They also critique the media's portrayal of the events and its impact on public perception. The book encourages readers to reflect on the societal implications of the Katrina story and the need for a more critical examination of our current society. It challenges traditional approaches to disasters and offers new perspectives on the long-term effects of traumatic events. The authors argue that for some survivors, a disaster may not be over, highlighting ongoing psychological and social impacts. They also discuss the displacement of poor black citizens and the failure of remedial actions in the New Orleans recovery. The book emphasizes the importance of rethinking emergency management and gaining a better understanding of the social history and conditions that contribute to vulnerability. It concludes by suggesting that lessons from events like Katrina and Covid-19 can enhance future preparedness and response efforts. [Extracted from the article]
Additional Information
- Source:International Journal of Mass Emergencies & Disasters. 2024/03, Vol. 42, Issue 1, p82
- Document Type:Article
- Subject Area:Literature and Writing
- Publication Date:2024
- ISSN:0280-7270
- DOI:10.1177/02807270241238727
- Accession Number:177518686
- Copyright Statement:Copyright of International Journal of Mass Emergencies & Disasters is the property of Sage Publications Inc. 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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