Understanding institutions in text

Institutions — rules that govern behavior — are among the most important social artifacts of society. So it should come as a great shock that we still understand them so poorly. How are institutions designed? What makes institutions work? Is there a way to systematically compare the language of different institutions? One recent advance is bringing us closer to making these questions quantitatively approachable. The Institutional Grammar (IG) 2.0 is an analytical approach, drawn directly from classic work by Nobel Laureate Elinor Ostrom, that is providing the foundation for computational representations of institutions. IG 2.0 is a formalism for translating between human-language outputs — policies, rules, laws, decisions, and the like. It defines abstract structures precisely enough to be manipulable by computer. Recent work, supported by the National Science Foundation (RCN: Coordinating and Advancing Analytical Approaches for Policy Design & GCR: Collaborative Research: Jumpstarting Successful Open-Source Software Projects With Evidence-Based Rules and Structures ), leveraging recent advances in natural language processing highlighted on this blog, is vastly accelerating the rate and quality of computational translations of written rules.