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The Daily Show: Discursive Integration and the Reinvention of Political Journalism

Open access
Baym, Geoffrey·2005·Political Communication

Abstract

The boundaries between news and entertainment, and between public affairs and pop culture, have become difficult if not impossible to discern. At the intersection of those borders sits The Daily Show with Jon Stewart, a hybrid blend of comedy, news, and political conversation that is difficult to pigeon hole. Although the program often is dismissed as being “fake” news, its significance for political communication may run much deeper. This study first locates The Daily Show within an emerging media environment defined by the forces of technological multiplication, economic consolidation, and discursive integration, a landscape in which “real” news is becoming increasingly harder to identify or define. It then offers an interpretive reading of the program that understands the show not as “fake news,” but as an experiment in journalism. It argues that the show uses techniques drawn from genres of news, comedy, and television talk to revive a journalism of critical inquiry and advance a model of deliberative democracy. Given the increasing popularity of the program, this essay concludes that The Daily Show has much to teach us about the possibilities of political journalism in the 21st century.

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Metadata

Authors
Baym, G.
Venue
Political Communication
Published
2005-07-01
Volume
22
Issue
3
Pages
259-276
ISSN
  • 1058-4609 (ISSN-L)
  • 1091-7675
OpenAlex
W2159751970
Cited by
560
References
0
FWCI
46.24
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: The Daily Show: Discursive Integration and the Reinvention of Political Journalism. https://app.cochat.ai/papers/10.1080/10584600591006492
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Baym, G. (2005). The Daily Show: Discursive Integration and the Reinvention of Political Journalism. Political Communication. https://doi.org/10.1080/10584600591006492

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.