A strategic analysis of science and technology policy

Abstract

Strategic decision-making in science and technology policy relies on conceptual strategies that synthesize empirical assertions, normative values, and predictive claims to justify public resource allocation. These strategies often lack the analytical rigor characteristic of other policy domains, frequently substituting crisis-driven intuition for systematic evaluation. Federal support for basic research is primarily grounded in market-failure arguments and the assumption that scientific knowledge is a prerequisite for economic growth, yet the efficacy of this model remains difficult to verify due to long lead times and irreversible outcomes. Innovation policy oscillates between engineering-based interventions and market-oriented approaches, often lacking a cohesive theoretical framework or specific performance indicators. In domains such as science education and information dissemination, justifications prioritize national security and technological competitiveness, frequently overemphasizing utilitarian outcomes while neglecting the internal dynamics of the scientific enterprise. Current bureaucratic incentives favor budget maximization over institutional flexibility, hindering the development of a critical analytical tradition. Enhancing the quality of science policy requires a shift toward portfolio management, the preservation of strategic options, and the design of adaptive, learning-oriented institutions capable of responding to emergent information and shifting socioeconomic conditions. – AI-generated abstract.