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MAGA & MAGYAR: The strategic use of common sense by Trump and Orbán during their state addresses

Christian Lamour

European Journal of Political Research2026https://doi.org/10.1017/s1475676525100522article
ABDC A
Weight
0.41

Abstract

The 2024 election of Donald Trump has been followed by executive decisions never before experienced in the history of American democracy. This new approach is grounded on a radical right (RR) program that had already been put in place in the Hungary of Viktor Orbán, who is presented as a model by Trump. Both leaders have defined a performative communication style, attracting a large segment of their respective citizenry. This style is based on the strategic use of common sense. However, we barely know how commonsensical executive RR leaders are during one of the most sacred events in a liberal democracy: the annual State of the Union or State of the Nation address. Based on a critical discourse analysis of the multiple speeches produced by Trump and Orbán in the frame of these events, the current research investigates the routinized and multifaceted usefulness of common sense to contest liberal democracy. The findings indicate that these leaders use the state address as a ritual of liberal democracy to impose a new RR order grounded in commonsensical policies, polities, and authorities.

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https://doi.org/https://doi.org/10.1017/s1475676525100522

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@article{christian2026,
  title        = {{MAGA & MAGYAR: The strategic use of common sense by Trump and Orbán during their state addresses}},
  author       = {Christian Lamour},
  journal      = {European Journal of Political Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1017/s1475676525100522},
}

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MAGA & MAGYAR: The strategic use of common sense by Trump and Orbán during their state addresses

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.