JOURNAL ARTICLE

"The audience has decided...": Children's Television Play as a Socio-Material Assemblage.

  • Published In: Research on Children & Social Interaction, 2025, v. 9, n. 1. P. 30 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Poveda, David; Galera, Nieves 3 of 3

Abstract

This article examines the play and peer interactions of Gitano (Spanish Roma) children aged 5 to 17 around the television reality show Gran Hermano (GH, the Spanish adaptation of Big Brother) during summer 2001 in a central Spanish city. Using a linguistic ethnographic dataset, the study analyzes how children creatively appropriated GH media scripts, re-signified their physical environment, and incorporated research technologies into their play, conceptualizing GH play as a socio-material assemblage that intertwines social interactions, material objects, media resources, and spatial settings. The children's enactments included mimetic reproduction of show routines (e.g., eviction ceremonies), hybridization with other media genres, and collaborative use of ethnographic recording devices as play props, illustrating emergent, multimodal, and more-than-human dimensions of play. The findings highlight children's active and inventive engagement with media and materiality in informal urban play spaces, offering a framework relevant to understanding contemporary child play as dynamic socio-material processes.

Additional Information

  • Source:Research on Children & Social Interaction. 2025/01, Vol. 9, Issue 1, p30
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2025
  • ISSN:2057-5807
  • DOI:10.3138/rcsi-2024-0004
  • Accession Number:187494512
  • Copyright Statement:Copyright of Research on Children & Social Interaction 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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