When Papers Stop Scaling: The Knowledge Abundance Paradox and the Institutional Economics of Scientific Coordination

Abstract

Artificial intelligence can lower the cost of producing plausible research outputs without proportionally lowering the cost of verification and accumulation. This position paper defines the Knowledge Abundance Paradox, develops a quality-adjusted lifecycle framework for comparing paper-centered coordination with a DGP-hybrid treatment inherited from DGP Multiverse Science, separates matched-task processing effects from total institutional effects, and specifies an adoption-equilibrium gate. Papers remain narrative interfaces and journals remain institutions of curation and judgment.