The authors analyzed public disclosures, foundation tax returns, and federal contractor reports to assess how S&P 500 companies support veterans and found little alignment among corporate statements, foundation giving, and protected veteran hiring.
Focusing on S&P 500 firms, RAND researchers analyzed public data on what companies say about veteran support, how their foundations give to veteran causes, and the extent to which federal contractors hire protected veterans.
The authors analyze all Workforce Innovation and Opportunity Act plans across five plan cycles, identifying strategies that policymakers can use to benchmark plans and strengthen coordination between postsecondary education and workforce systems.
This paper draws together the findings of the Justice for All series, reflecting on the contribution of each briefing paper exploring the evidence on the matters under consideration and the key themes that emerge across them.
The authors examine Russia’s activities in Latin America and the Caribbean, how these efforts have advanced Russia’s strategic aims across the region as a whole and with key partners, and the implications for U.S interests in the Western Hemisphere.
RAND Europe scoped technology use in security-sector governance and management, mapping opportunities and risks from real-world cases and distilling lessons and good practices to embed good governance in the adoption and use of these tools.
This RAND Europe research explores UK Veterans’ and Reservists’ participation in civilian labour markets, including economic participation, underemployment and barriers to, and facilitators of, good employment outcomes.
The author describes a formal model of artificial intelligence (AI) adoption and proliferation that focuses on the demand for AI capability.
Recent federal policies establish funding prohibitions and review requirements for certain high-risk life sciences research. The authors advise that federal agencies adopt an objective decisionmaking framework for dangerous gain-of-function research.
Artificial intelligence model distillation (training new models on outputs of more capable ones) could affect U.S. frontier model advantage. New policy tools could augment such technical countermeasures as raising costs or reducing model quality.