ArticleNpj complexity2025
Governance as a complex, networked, democratic, satisfiability problem.
Article in Npj complexity, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
9 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Democratic governments comprise a subset of a population whose goal is to produce coherent decisions solving societal challenges while respecting the will of the people. New governance frameworks represent this as a social network rather than as a hierarchical pyramid with centralized authority. But how should this network be structured? We model the decisions a population must make as a satisfiability problem and the structure of information flow involved in decision-making as a social hypergraph. This framework allows to consider different governance structures, from dictatorships to direct democracy. Between these extremes, we find a regime of effective governance where small overlapping decision groups make specific decisions and share information. Effective governance allows even incoherent or polarized populations to make coherent decisions at low coordination costs. Beyond simulations, our conceptual framework can explore a wide range of governance strategies and their ability to tackle decision problems that challenge standard governments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.