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Staging High-Visibility Science: Media Orientation in Genome Research

  • Stephen HilgartnerEmail author
Chapter
Part of the Sociology of the Sciences Yearbook book series (SOSC, volume 28)

Abstract

The medialization concept was developed using differentiation theory and has been applied analytically at the level of systems. This chapter develops a complementary perspective for considering medialization that focuses on media orientation as it is expressed in interaction. How do individual scientists or science-intensive organizations manifest an orientation to the media? In what ways, and how intensely, does the media fit into their activities? To address these questions, the chapter develops a framework that conceptualizes media orientation as a specific form of what Erving Goffman calls “theatrical self-consciousness.” The tools of dramaturgical analysis are brought to the staging of science, providing a vocabulary for exploring science-media coupling not as connections between abstract systems but as strategic interaction. The focus on theatrical self-consciousness casts a spotlight on questions about precisely what actors seek to make visible to whom and when. An ethnographic study of genome research during the Human Genome Project provides data. The chapter examines interactions surrounding a specific episode: the announcement that a private firm, Celera Genomics, intended to sequence the human genome before the public project could. The analysis provides a look at the specific and varied ways in which members of a particular research community related to the media. The conclusion distinguishes among four facets of media orientation (the actor as performer, as audience, as commentator, and as builder of media relations infrastructure). Finally, it notes some possible methodological implications.

Keywords

Cold Spring Harbor Press Release Human Genome Project Genome Shotgun News Coverage 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Cornell University

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