Reflections of/on US Media Stereotypes of Class and Socioeconomic Status

Conference: The European Conference on Media, Communication & Film (EuroMedia2022)
Title: Reflections of/on US Media Stereotypes of Class and Socioeconomic Status
Stream: Mass Communication
Presentation Type: Oral Presentation
Rebecca Lind, University of Illinois at Chicago, United States


Beverley Skeggs argued that "Class will always be a site of struggle, as it encompasses interests, power and privilege" (2004, p. 44). Scholars from many disciplines have long been interested in mediated representations of class. This paper continues that tradition, containing three main sections. First, the paper reviews stereotypes in media representations of class and socio-economic status (SES) in the 20th and 21st Centuries. Briefly: The working class and the poor are relatively nonexistent in the media, and shown as deserving of their fate. The poor are blamed for their own poverty. The middle class is normative. The wealthy are fascinating and benevolent; wealth (like poverty) is rooted in individual qualities, not inequitable social structures. Next, the paper reviews research demonstrating the effects of stereotypical representations on people and policy. Perceiving social class as controllable (due to individuals’ behaviors/choices) affects people’s support for relevant economic and social policies. Mediated portrayals of the poor can even predict government spending and official policy regarding the poor. Finally, the paper encourages scholars to continue to theorize representations of class/SES and people’s responses thereto. For example, Behm-Morawitz, Miller, and Lewallen’s (2018) model for quantitatively identifying representations of social class includes occupation, financial security, and material possessions. This model could be expanded to explicitly incorporate Bourdieu’s multiple forms of capital: economic, symbolic, cultural and social, thereby faciliating a richer, more contextualized, and more relational understanding of social class even in the quantitative realm.

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