JOURNAL ARTICLE
Evaluating well‐being after compulsory resettlement: Livelihoods, standards of living, and well‐being in Manantali, Mali.
Published In: Economic Anthropology, 2024, v. 11, n. 2. P. 210 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Koenig, Dolores 3 of 3
Abstract
Despite efforts to improve outcomes, resettlement projects that aim to improve livelihoods and living standards of the displaced often do not achieve their goals. Could greater attention to the well‐being of the affected improve resettlement outcomes? This article considers standards of living and well‐being among one resettled group, the Bahingkolu of Manantali, Mali, relocated in the mid‐1980s by construction of the Manantali Dam. Anthropological approaches to well‐being that include a greater understanding of people's own conceptions of well‐being and consider well‐being in relationship to their social and physical worlds help elucidate why the Bahinkolu are unsatisfied with their well‐being despite higher standards of living. Because they can no longer grow enough for food self‐sufficiency, they must encourage family members to work elsewhere, thereby risking the sustainability of the family as a single economic unit. In this context, household heads feel constant anxiety about their ability to maintain a cohesive household. The Bahingkolu publicly maintain that they are "victims of the resettlement" as a strategy to gain more resources for the community. To improve the generally negative consequences of involuntary resettlement, planning should expend more effort to appreciate the conceptions of well‐being among the affected. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Economic Anthropology. 2024/06, Vol. 11, Issue 2, p210
- Document Type:Article
- Subject Area:Geography and Cartography
- Publication Date:2024
- ISSN:2330-4847
- DOI:10.1002/sea2.12322
- Accession Number:177903849
- Copyright Statement:Copyright of Economic Anthropology 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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