Date of Submission

Spring 2015

Academic Programs and Concentrations


Project Advisor 1

Frank Scalzo

Abstract/Artist's Statement

Underrepresentation is an important issue in modern television. While the population in the United States is made up of many varying ethnicities, sexual orientations, and other identities, viewers are finding that white, heteronormative males account for the disproportionately dominant majority of all current actors, writers, show creators and directors. Past research demonstrates that when specific character portrayals become hyper-typical of modern television (such as light-skinned, heteronormative males), such portrayals are normalized within our greater culture more strongly than portrayals of identities that are ignored or seldom shown on television. As a consequence of this underrepresentation of diverse identities on television, there is slower acceptance and higher marginalization of underrepresented groups. This project proposes three studies that would measure implicit attitude change resulting from viewing either socially positive or negative portrayals of underrepresented identities reflected in characters shown on television. While the participants in Study 1 will view different portrayals of African American characters, the participants in Studies 2 and 3 will view portrayals of women and gay men, respectively. It is predicted that participants who view positive portrayals of underrepresented characters will demonstrate less implicit bias towards either light-skin, men, or heteronormativity, than will participants who view negative portrayals of characters depicting underrepresented identities. The goal of this project is to design an experiment for large networks to replicate easily, in order to understand better how the content such networks present has and will affect social attitudes and acceptance of diversity in the United States.

Open Access Agreement

On-Campus only

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.