EAGER: Quantifying the Scale of Foreign Influence: Estimating Base Rates and Perception Gaps in U.S. Research Security

The United States’ global leadership in research and technological innovation relies on an open, collaborative environment—a strength that simultaneously exposes the enterprise to exploitation by adversarial nations. While federal directives like NSPM-33 and the CHIPS and Science Act prioritize research security, a critical knowledge gap persists regarding the actual prevalence of foreign influence mechanisms, such as undisclosed rewards, coercion, and theft. Because these topics are highly sensitive, traditional surveys are unreliable due to fear of repercussions and social desirability bias. Consequently, policymakers lack accurate data and instead rely on anecdotal evidence, which drives either complacent or alarmist strategies. This project addresses these vulnerabilities by establishing a definitive baseline for research security risks. Using a sophisticated questioning technique that protects respondent anonymity, the project shifts the national discourse to an evidence-based strategy. Specifically, it: 1) estimates the true base rates of key security issues among U.S. academic researchers and administrators; 2) assesses perceived threat levels; and 3) compares actual rates with perceived threats to identify critical "perception gaps." Establishing these base rates provides an empirical foundation for federal policies, safeguarding intellectual property while maintaining the responsible international collaborations critical to U.S. scientific leadership. Grounded in recommendations from a recent NSF-funded workshop (Dao et al., 2024), this mixed-methods study quantifies the scale of research security incidents by establishing definitive baseline rates. The research estimates the actual prevalence of security threats and compares them against the threat levels perceived by U.S. academic researchers and administrators. To ensure robust data, the study employs a stratified random sample based on institutional research expenditures and disciplinary focus (STEM versus non-STEM). To overcome the social desirability bias and underreporting inherent in surveying sensitive behaviors, the methodology applies the Crosswise Model. This indirect questioning technique guarantees anonymity by mathematically decoupling individual responses from aggregate estimates. It ensures participants' absolute privacy while leveraging recent methodological advances to mitigate potential upward bias in base-rate estimates. By triangulating actual prevalence rates against perceived threats measured via standard scales, the analysis identifies critical perception gaps. Highlighting these misalignments will directly guide targeted education and evidence-based policy adjustments within the U.S. research enterprise. 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.