JOURNAL ARTICLE

"The Many Faces and Shades of Blackness": Race, Class, and Geography in Early Twenty-First-Century Telenovela Representations.

  • Published In: Studies in Latin American Popular Culture, 2024, v. 42. P. 97 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Berktay, Asligul 3 of 3

Abstract

This article explores how Brazilian telenovelas reflect long-term understandings of race and race relations in Brazil, as well as within the (tele)-visual legacy and representations shared by the slave societies of the Atlantic world. Specifically, it focuses on two TV Globo telenovelas that were especially significant to Blackness and its televisual representations in the early 2000s by respectively presenting the first main female and male Black telenovela protagonists to the Brazilian televiewing public. Concentrating my analysis on the representations of Black female beauty and subjectivity in Da Cor do Pecado (2004) and on Black male sexuality and agency in the space of the favela in Duas Caras (2007–2008), I contend that, while these telenovelas were certainly important in challenging racial democracy, they nevertheless fell victim to the stereotypical representations and tropes created by slavery and its racialized and often racist aftermath, as well as to the dynamics of completion, distancing, and the ethnographic attitude that are also important components of this (tele)visual legacy. Thus, rather than breaking from the predominance of the continuing hegemony of racial democracy in Brazilian media and society, these telenovelas serve to emphasize it. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Studies in Latin American Popular Culture. 2024/01, Vol. 42, p97
  • Document Type:Article
  • Subject Area:Communication and Mass Media
  • Publication Date:2024
  • ISSN:0730-9139
  • DOI:10.7560/slapc4206
  • Accession Number:179258906
  • Copyright Statement:Copyright of Studies in Latin American Popular Culture is the property of University of Texas 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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