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Silencing nonstandard speakers: A content analysis of accent portrayals on American primetime television

Published online by Cambridge University Press:  28 January 2016

Marko Dragojevic
Affiliation:
Department of Communication, University of Kentucky, 227 Grehan Building, Lexington, KY 40506-0042, [email protected]
Dana Mastro
Affiliation:
Department of Communication, University of California, Santa Barbara 4005 Social Sciences & Media Studies Bldg., Santa Barbara, CA 93106-4020, USA
Howard Giles
Affiliation:
Department of Communication, University of California, Santa Barbara 4005 Social Sciences & Media Studies Bldg., Santa Barbara, CA 93106-4020, USA
Alexander Sink
Affiliation:
Department of Communication, University of California, Santa Barbara 4005 Social Sciences & Media Studies Bldg., Santa Barbara, CA 93106-4020, USA

Abstract

Accent is a potent cue to social categorization and stereotyping. An important agent of accent-based stereotype socialization is the media. The present study is the first quantitative content analysis to comprehensively examine accent portrayals on American primetime television. We focused our analysis on portrayals of Standard American (SA), Nonstandard American (NSA), Foreign-Anglo (FA), and Foreign-Other (FO) accents. Results provide clear evidence that American media's portrayals of different accents are biased, reflecting pervasive societal stereotypes. Whereas SA and FA speakers are over-represented on television, NSA and FO speakers are effectively silenced, by virtue of their sheer absence and gross under-representation. Moreover, when NSA and FO speakers do rarely appear on television, they tend to be portrayed less favorably on status-related traits and physical appearance than SA and FA speakers. These findings provide insight into the potential influence of media consumption on consumers’ social perceptions of different linguistic groups. (Accents, media, language attitudes, stereotypes, content analysis)*

Type
Articles
Copyright
Copyright © Cambridge University Press 2016 

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