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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | George Mason University |
| Country | United States |
| Start Date | Jun 01, 2025 |
| End Date | May 31, 2027 |
| Duration | 729 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2449568 |
This project explores how scientific messages about environmental adaptation shape people’s decisions, especially when their beliefs about the environment, politics, and other issues are closely connected. By examining why some individuals embrace adaptation measures—such as flood-proofing homes or relocating from high-risk areas—while others do not, the project seeks to clarify how these choices can unintentionally deepen social and economic inequalities.
In doing so, the project addresses the national interest by improving public understanding of climate risks, fostering more informed decision-making, and promoting inclusive, effective adaptation strategies. The project also advances broader societal goals by training undergraduate researchers, partnering with nonprofit organizations to develop practical outreach methods, and creating software tools that can be used to study belief systems in various contexts.
This project develops a new conceptual framework, new methodological tools, and survey-based measurement approach for “belief networks,” capturing how an individual’s attitudes about topics such as climate, people migration, and social fairness simultaneously influence one another. Large-scale surveys in the United States and a case study in Virginia will map how these networks vary across partisan, demographic, and socioeconomic groups.
The researchers will then design and implement scientific communication experiments to examine how information targeting specific attitudes—and the links among them—affects people’s adaptive capacity and motivation. Alongside these empirical studies, the project supports new network science methods to analyze individual-level belief systems at scale, providing computational and statistical tools for extracting, modeling, and comparing complex attitude linkages.
By integrating these methodological advances with science communication research, the project offers insights into how scientific information can most effectively encourage robust, evidence-based adaptation decisions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
George Mason University
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