Rachel Reis Mourão: 2017 Winner of the Gene Burd Outstanding Dissertation in Journalism Studies Award

2017 Winner of the Gene Burd Outstanding Dissertation in Journalism Studies Award

After extensive review the committee voted to award the prize to Rachel Reis Mourão for her dissertation entitled “From Mass to Elite Protests: How Journalists Covered the 2013 and 2015 Demonstrations in Brazil.” The reviewers found the dissertation to be sophisticated and nuanced in its analysis of the changing journalism landscape. Dr. Mourão’s work was supervised by Stephen D. Reese at the The University of Texas at Austin.

Her dissertation uses a media sociology approach to untangle how multiple influences shaped journalistic coverage of two waves of protests in Brazil. In 2013, small demonstrations against bus fares evolved into a series of large protests expressing generalized dissatisfaction with conditions in the country. Following the reelection of center-leftist Dilma Rousseff, another wave of protests returned in 2015, this time with a clear agenda: the removal of the President. Communication research has long examined the “protest paradigm,” a pattern of news coverage that legitimized social movements. The study departs from an understanding of protest coverage as paradigmatic towards a more complex view of the relationship between protesters and the press. The analysis helps elucidate the conditions under which the protest paradigm fails and how favorable coverage can occur. The experience of Brazil shows that when an elite opposition supports protests, journalistic norms and routines validate demonstrations, regardless of journalists’ own attitudes.

Honorable Mention: Dr. Rodrigo Zamith

The runner up for the prize was Dr. Rodrigo Zamith for his dissertation entitled “Editorial Judgment in an Age of Data: How Audience Analytics and Metrics are Influencing the Placement of News Products,” which was a theoretically sophisticated exploration of the extent to which audience analytics—i.e., digital metrics that track the preferences of users based on click behaviors—appear to affect news content.