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  1. Rational Polarization.Kevin Dorst - manuscript
    Predictable polarization is everywhere: we can often predict how people’s opinions—including our own—will shift over time. Empirical studies suggest that this is so when evidence is ambiguous. That fact is often thought to demonstrate human irrationality. It doesn’t. Bayesians will predictably polarize iff their evidence is ambiguous. And ours often is: the process of cognitive search—searching a cognitively-accessible space for an item of a particular profile—yields ambiguous evidence that can predictably polarize beliefs, despite being expected to make them more accurate. (...)
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  • Being Rational and Being Wrong.Kevin Dorst - manuscript
    Do people tend to be overconfident in their opinions? Many think so. They’ve run studies to test whether people are calibrated: whether their confidence in their opinions matches the proportion of those opinions that are true. Under certain conditions, people are systematically “over-calibrated”—for example, of the opinions they’re 80% confident in, only 60% are true. From this observed over-calibration, it’s inferred that people are irrationally overconfident. My question: When—and why—is this inference warranted? Answering this question requires articulating a general connection (...)
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  • Formal Models of Scientific Inquiry in a Social Context: An Introduction.Dunja Šešelja, Christian Straßer & AnneMarie Borg - 2020 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 51 (2):211-217.
    Formal models of scientific inquiry, aimed at capturing socio-epistemic aspects underlying the process of scientific research, have become an important method in formal social epistemology and philosophy of science. In this introduction to the special issue we provide a historical overview of the development of formal models of this kind and analyze their methodological contributions to discussions in philosophy of science. In particular, we show that their significance consists in different forms of ‘methodological iteration’ whereby the models initiate new lines (...)
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  • Conformity in Scientific Networks.James Owen Weatherall & Cailin O’Connor - 2018 - Synthese:1-22.
    Scientists are generally subject to social pressures, including pressures to conform with others in their communities, that affect achievement of their epistemic goals. Here we analyze a network epistemology model in which agents, all else being equal, prefer to take actions that conform with those of their neighbors. This preference for conformity interacts with the agents’ beliefs about which of two possible actions yields the better result. We find a range of possible outcomes, including stable polarization in belief and action. (...)
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  • Exploring Scientific Inquiry Via: Agent-Based Modelling.Dunja Šešelja - 2021 - Perspectives on Science 29 (4):537-557.
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  • How to Beat Science and Influence People: Policymakers and Propaganda in Epistemic Networks.James Owen Weatherall, Cailin O’Connor & Justin P. Bruner - 2020 - British Journal for the Philosophy of Science 71 (4):1157-1186.
    In their recent book, Oreskes and Conway describe the ‘tobacco strategy’, which was used by the tobacco industry to influence policymakers regarding the health risks of tobacco products. The strategy involved two parts, consisting of promoting and sharing independent research supporting the industry’s preferred position and funding additional research, but selectively publishing the results. We introduce a model of the tobacco strategy, and use it to argue that both prongs of the strategy can be extremely effective—even when policymakers rationally update (...)
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  • The Role of Source Reliability in Belief Polarisation.Leah Henderson & Alexander Gebharter - 2021 - Synthese:1-24.
    Psychological studies show that the beliefs of two agents in a hypothesis can diverge even if both agents receive the same evidence. This phenomenon of belief polarisation is often explained by invoking biased assimilation of evidence, where the agents’ prior views about the hypothesis affect the way they process the evidence. We suggest, using a Bayesian model, that even if such influence is excluded, belief polarisation can still arise by another mechanism. This alternative mechanism involves differential weighting of the evidence (...)
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  • Conformity in Scientific Networks.Cailin O’Connor & James Owen Weatherall - 2020 - Synthese 198 (8):7257-7278.
    Scientists are generally subject to social pressures, including pressures to conform with others in their communities, that affect achievement of their epistemic goals. Here we analyze a network epistemology model in which agents, all else being equal, prefer to take actions that conform with those of their neighbors. This preference for conformity interacts with the agents’ beliefs about which of two possible actions yields the better result. We find a range of possible outcomes, including stable polarization in belief and action. (...)
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  • Endogenous epistemic factionalization.James Owen Weatherall & Cailin O’Connor - forthcoming - Synthese:1-22.
    Why do people who disagree about one subject tend to disagree about other subjects as well? In this paper, we introduce a model to explore this phenomenon of ‘epistemic factionization’. Agents attempt to discover the truth about multiple propositions 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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  • Towards a Critical Social Epistemology for Social Media.Joshua Habgood-Coote - manuscript
    What are the proper epistemic aims of social media sites? A great deal of social media critique is in the grips of an Epistemic Apocalypse narrative, which claims that the technologies associated with social media have catastrophically undermined our traditional knowledge-generating practices, and that the remedy is to recreate our pre-catastrophe practices as closely as possible. This narrative relies on a number of questionable assumptions, and problematically narrows the imaginative possibilities for redesigning social media. Our goal in this paper is (...)
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  • Mis- and Disinformation in a Bounded Confidence Model.Igor Douven & Rainer Hegselmann - 2021 - Artificial Intelligence 291:103415.
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  • 2006.Alvin Goldman - forthcoming - Social Epistemology. In the Stanford Encyclopedia of Philosophy Available From Http://Plato. Stanford. Edu/Entries/Epistemology-Social.
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  • Modeling How False Beliefs Spread.Cailin O'Connor & James Owen Weatherall - unknown
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  • Individual Representation in a Community of Knowledge.Nathaniel Rabb, Philip M. Fernbach & Steven A. Sloman - 2019 - Trends in Cognitive Sciences 23 (10):891-902.
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  • The Social Dimensions of Scientific Knowledge.Helen Longino - 2008 - Stanford Encyclopedia of Philosophy.