Won-Ki Moon
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Articles (14)
Numerous studies have been conducted to identify the factors that predict trust/distrust in science. However, most of these studies are based on closed-ended survey research, which does not allow researchers to gain a more nuanced understanding of the phenomenon. This study integrated survey analysis conducted within the United States with computational text analysis to reveal factors previously obscured by traditional survey methodologies. Even after controlling for political ideology—which has been the most significant explanatory factor in determining trust in science within a survey framework—we found those with concerns over boundary-crossing (i.e. concerns or perceptions that science overlaps with politics, the government, and funding) were less likely to trust science than their counterparts.
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2024
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2024
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2024
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2023
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2023
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2022
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2022
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2022
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2022
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2022
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2021
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2021
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2020
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2020
Collaborators (5)
Hayoung Sally Lim
University of Texas at Austin
S Mo Jones-Jang
Associate professor
Boston College
Marshall Taylor
Assistant Professor
University of New Mexico
Sangwon Lee
University of New Mexico
Myojung Chung
Assistant Professor
Northeastern University
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