JOURNAL ARTICLE

Tactical Partnerships in an Awkward Dance to Commodify Identities within Haiti's Transnational Space.

  • Published In: Diaspora: A Journal of Transnational Studies, 2024, v. 24, n. 1. P. 29 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Fouron, Georges 3 of 3

Abstract

This article examines a 2007 festival in Ré, a remote and impoverished hamlet in Haiti's South Department, where three distinct Haitian groups—local peasants, internal migrants from Haitian towns, and Haitian emigrants primarily from the United States and Canada—converged, creating a microcosm of Haiti's transnational social dynamics. It highlights how these groups, despite shared Haitian identity and transnational ties, pursued divergent and often self-interested agendas, with emigrants displaying hegemonic behaviors that reinforced social inequalities and gender exploitation, while locals placed hopes on diaspora intervention for national development. The study situates Ré within broader transnationalism frameworks, illustrating how emigrants maintain complex social, economic, and symbolic connections to Haiti, yet their involvement can both support and hinder social progress. Ultimately, the festival revealed missed opportunities for transformative collaboration, as entrenched power imbalances and commodification of identities perpetuated Haiti's structural stagnation rather than fostering meaningful change.

Additional Information

  • Source:Diaspora: A Journal of Transnational Studies. 2024/04, Vol. 24, Issue 1, p29
  • Document Type:Article
  • Subject Area:Geography and Cartography
  • Publication Date:2024
  • ISSN:1044-2057
  • DOI:10.3138/diaspora.24.1.2024.02.14
  • Accession Number:177326631
  • Copyright Statement:Copyright of Diaspora: A Journal of Transnational Studies is the property of University of Toronto Press 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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