Let’s Get Loud: Intersectionally Studying the Super Bowl’s Halftime Show

• Autor(a) principal: Van Bauwel, Sofie
• Data de Publicação: 2021
• Outros Autores: Krijnen, Tonny
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://doi.org/10.17645/mac.v9i3.4152
• topic: discourse analysis; intersectionality; Latinidad; listening; popular culture; Super Bowl Halftime Show

The study of popular culture has always been closely related to the study of class, gender, race, and sexuality. An increasing number of authors have called for an intersectional approach. However, the contradictory, fluid meanings articulated in popular culture render such an approach difficult, and many ignore the call for intersectional analysis. We will not. We will try to engage with an intersectional analysis of popular culture, using Shakira and Jennifer Lopez’s performance at the 2020 Super Bowl Halftime Show as a case to study the intersections of identity markers. We aim to bridge the different meanings attributed to their performance and to understand them as different elements in the intersectional configuration. A discourse analysis of the performance, and of reviews thereof, was performed to unravel five elements highlighted in the discourse: the quality of the show, Shakira and Lopez’s empowered performances, the incorporation of Latinidad elements, the performers’ sexiness, and perceived political messages. Our aim to understand how the contradictory discourses about these elements arose urges the reader to use listening to grapple with the complexity of intersectional analysis. Truly listening includes putting effort into opening up academic cultures, finding other voices. It is important to recognize global gender inequity, but we need to start investing far more to understand the politics of media representations as a transnational affair that causes multiple conceptions of gender (and other related) concepts to clash, mesh, and integrate.