ArticleCognitive processing2025
Breaking through the 'wall of complexity' in a politically themed microworld: a challenge for elected officials and the general public.
Article in Cognitive processing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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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Authors and funding
6 authors.
Funding
Abstract
Political leaders are often regarded as the most qualified individuals to address modern societal challenges, owing to the knowledge they acquire through their experience in dealing with complex issues, governance and management, and working towards making impactful decisions. To understand the influence of prior knowledge on decision-making, we conducted a comparative analysis of complex decision-making performance in a politically themed computer-simulated microworld involving incumbent elected officials and a general population sample, each contrasted with a random-response baseline produced with randomly generated decisions. Participants were tasked to govern a country for re-election while maintaining financial stability. The pattern of results suggests that decision-making faces a 'wall of complexity' whether one is an elected official or a citizen. Although elected officials generally reported having greater political knowledge, their performance was still relatively poor. The elected officials and general population subgroups performed at the same level and only slightly better than chance. Addressing the societal challenges of our time requires elected officials to possess more than domain-specific prior knowledge.
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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.