Benign Inequality: Frames of Poverty and Social Class Inequality in Children’s Movies.

Media targeted at adults tends to portray poverty and social class inequality as the result of individual merit and moral worth. Research, however, has not uncovered how poverty and social class inequality are portrayed in media targeted at children. Drawing on a content analysis of the highest gros...

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Publicado en:Journal of Poverty Vol. 21; no. 1; pp. 1 - 20
Autores principales: Streib, Jessi, Ayala, Miryea, Wixted, Colleen
Formato: Artículo
Publicado: Taylor & Francis Ltd Jan/Feb2017
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Benign Inequality: Frames of Poverty and Social Class Inequality in Children’s Movies.
      aug:
        au:
          Streib, Jessi
          Ayala, Miryea
          Wixted, Colleen
        affil: Department of Sociology, Duke University, Durham, North Carolina, USA
      su:
        Mass media
        Poverty
        Social classes
        Classism
        Individual measures (Psychology)
      sug:
        subj:
          Mass media
          Poverty
          Social classes
          Classism
          Individual measures (Psychology)
      keyword:
        Children
        inequality
        media
        movies
        poverty
        social class
      ab: Media targeted at adults tends to portray poverty and social class inequality as the result of individual merit and moral worth. Research, however, has not uncovered how poverty and social class inequality are portrayed in media targeted at children. Drawing on a content analysis of the highest grossing G-rated movies, this study examines the proportional representation of characters in each class as well as frames of class conditions, characters, and the opportunity structure. These frames suggest that children’s media legitimates poverty and social class inequality in a new way—by presenting them as benign.
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    language: English
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      custom: Copyright of Journal of Poverty is the property of Taylor & Francis Ltd 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.
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