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  1. Theory-Choice, Transient Diversity and the Efficiency of Scientific Inquiry.AnneMarie Borg, Daniel Frey, Dunja Šešelja & Christian Straßer - 2019 - European Journal for Philosophy of Science 9 (2):26.
    Recent studies of scientific interaction based on agent-based models suggest that a crucial factor conducive to efficient inquiry is what Zollman has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories lasting sufficiently long for the community to identify the best theory and to converge on it. But what exactly generates transient diversity? And is transient diversity a decisive factor when it comes to the efficiency of inquiry? In this paper we (...)
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  • Endogenous Epistemic Factionalization: A Network Epistemology Approach.James Owen Weatherall & Cailin O'Connor - unknown
    Why do people who disagree about one subject tend to disagree about other subjects as well? In this paper, we introduce a network epistemology model to explore this phenomenon of “epistemic factionization”. Agents attempt to discover the truth about multiple beliefs by testing the world and sharing evidence gathered. But agents tend to mistrust evidence shared by those who do not hold similar beliefs. This mistrust leads to the endogenous emergence of factions of agents with multiple, highly correlated, polarized beliefs.
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  • Truth Tracking Performance of Social Networks: How Connectivity and Clustering Can Make Groups Less Competent.Ulrike Hahn, Jens Ulrik Hansen & Erik J. Olsson - forthcoming - Synthese:1-31.
    Our beliefs and opinions are shaped by others, making our social networks crucial in determining what we believe to be true. Sometimes this is for the good because our peers help us form a more accurate opinion. Sometimes it is for the worse because we are led astray. In this context, we address via agent-based computer simulations the extent to which patterns of connectivity within our social networks affect the likelihood that initially undecided agents in a network converge on a (...)
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