Independent third-party citations, academic references, and professional community recognition of AUTHREX governance research. These references were generated organically, without solicitation, by researchers, academic journals, defense communities, and media outlets across multiple countries.
5
Independent References
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Academic Citations
4
Countries
EB2-NIW Relevance (Dhanasar Framework):
Under Prong 1, independent citations demonstrate substantial merit. Under Prong 2, unsolicited third-party references confirm the applicant is well positioned to advance the proposed endeavor. Under Prong 3, international recognition across defense, governance, and academic communities confirms national interest benefit.
Academic CitationApril 1, 2026
Cited in "The Ethics of AI in U.S. Warfare"
LexAI Journal, University of Toronto, Faculty of Law
A multi-author academic article published by the University of Toronto's Law and Ethics of Artificial Intelligence Students' Association cited the ERAM framework paper as Reference #4. The article examines decision compression in AI-enabled military command, directly referencing the ERAM framework's analysis of how automated decision-support systems destabilize human oversight in military operations.
Work Cited: Oktenli, B. (2026). "Decision Compression and Escalation Risk in AI-Enabled Military Command and Control: An Operational Analysis of the ERAM Framework." SSRN.
A bilingual (English/Spanish) strategic paper addressed to Ministries of Defense, Armed Forces, and state institutions across multiple countries cited the LinkedIn article as a strategic analysis source, listed alongside official U.S. government sources including the Department of Defense (DoD), Defense Logistics Agency (DLA), U.S. Army DEVCOM Soldier Center, and USDA.
Work Cited: Oktenli, B. "Why Freeze-Dried Food Is Becoming a Strategic Asset in Defense, Emergency Preparedness, and National Security." LinkedIn Pulse.
SSRN Official Community, Facebook (Elsevier / Social Science Research Network)
The official SSRN Community page, operated by Elsevier's Social Science Research Network, one of the world's largest open-access academic repositories, selected and featured the submarine surface signatures paper on their social media platform, amplifying its visibility to SSRN's global research audience.
Work Featured: Oktenli, B. "Physics-Based Analysis of Submarine Surface Signatures: Hydrodynamic Mechanisms and Detection Frameworks." SSRN.
SSRN Community
Official SSRN / Elsevier · Facebook
Physics-Based Analysis of Submarine Surface Signatures: Hydrodynamic Mechanisms and Detection Frameworks
Featured by the official SSRN Community page, operated by Elsevier's Social Science Research Network, which amplified this research to their global academic audience.
Wargaming Weekly, a defense and military simulation community account, independently shared the LinkedIn article on AI-driven simulation in U.S. defense testing with the quote: "By injecting AI agents, massive parallelism, and data-driven analysis into simulations, the military can explore far more scenarios, catch hidden flaws, and train personnel more effectively."
Work Shared: Oktenli, B. "AI-Driven Simulation: Transforming US Defense Testing." LinkedIn Pulse.