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  1. Agent‐Based Models of Scientific Interaction.Dunja Šešelja - forthcoming - Wiley: Philosophy Compass.
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  • The Distribution of Ethical Labor in the Scientific Community.Vincenzo Politi & Alexei Grinbaum - 2020 - Journal of Responsible Innovation 7:263-279.
    To believe that every single scientist ought to be individually engaged in ethical thinking in order for science to be responsible at a collective level may be too demanding, if not plainly unrealistic. In fact, ethical labor is typically distributed across different kinds of scientists within the scientific community. Based on the empirical data collected within the Horizon 2020 ‘RRI-Practice’ project, we propose a classification of the members of the scientific community depending on their engagement in this collective activity. Our (...)
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  • Germs, Genes, and Memes: Function and Fitness Dynamics on Information Networks.Patrick Grim, Daniel J. Singer, Christopher Reade & Steven Fisher - 2015 - Philosophy of Science 82 (2):219-243.
    Understanding the dynamics of information is crucial to many areas of research, both inside and outside of philosophy. Using computer simulations of three kinds of information, germs, genes, and memes, we show that the mechanism of information transfer often swamps network structure in terms of its effects on both the dynamics and the fitness of the information. This insight has both obvious and subtle implications for a number of questions in philosophy, including questions about the nature of information, whether there (...)
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  • Let’s Not Agree to Disagree: The Role of Strategic Disagreement in Science.Carlos Santana - 2019 - Synthese 198 (Suppl 25):6159-6177.
    Supposedly, stubbornness on the part of scientists—an unwillingness to change one’s position on a scientific issue even in the face of countervailing evidence—helps efficiently divide scientific labor. Maintaining disagreement is important because it keeps scientists pursuing a diversity of leads rather than all working on the most promising, and stubbornness helps preserve this disagreement. Planck’s observation that “Science progresses one funeral at a time” might therefore be an insight into epistemically beneficial stubbornness on the part of researchers. In conversation with (...)
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  • Rational Social and Political Polarization.Daniel J. Singer, Aaron Bramson, Patrick Grim, Bennett Holman, Jiin Jung, Karen Kovaka, Anika Ranginani & William J. Berger - 2019 - Philosophical Studies 176 (9):2243-2267.
    Public discussions of political and social issues are often characterized by deep and persistent polarization. In social psychology, it’s standard to treat belief polarization as the product of epistemic irrationality. In contrast, we argue that the persistent disagreement that grounds political and social polarization can be produced by epistemically rational agents, when those agents have limited cognitive resources. Using an agent-based model of group deliberation, we show that groups of deliberating agents using coherence-based strategies for managing their limited resources tend (...)
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  • The Computational Philosophy: Simulation as a Core Philosophical Method.Conor Mayo-Wilson & Kevin J. S. Zollman - 2021 - Synthese 199 (1-2):3647-3673.
    Modeling and computer simulations, we claim, should be considered core philosophical methods. More precisely, we will defend two theses. First, philosophers should use simulations for many of the same reasons we currently use thought experiments. In fact, simulations are superior to thought experiments in achieving some philosophical goals. Second, devising and coding computational models instill good philosophical habits of mind. Throughout the paper, we respond to the often implicit objection that computer modeling is “not philosophical.”.
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  • What Is the Epistemic Function of Highly Idealized Agent-Based Models of Scientific Inquiry?Daniel Frey & Dunja Šešelja - 2018 - Philosophy of the Social Sciences 48 (4):407-433.
    In this paper we examine the epistemic value of highly idealized agent-based models of social aspects of scientific inquiry. On the one hand, we argue that taking the results of such simulations as informative of actual scientific inquiry is unwarranted, at least for the class of models proposed in recent literature. Moreover, we argue that a weaker approach, which takes these models as providing only “how-possibly” explanations, does not help to improve their epistemic value. On the other hand, we suggest (...)
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  • Coherence and Correspondence in the Network Dynamics of Belief Suites.Patrick Grim, Andrew Modell, Nicholas Breslin, Jasmine Mcnenny, Irina Mondescu, Kyle Finnegan, Robert Olsen, Chanyu An & Alexander Fedder - 2017 - Episteme 14 (2):233-253.
    Coherence and correspondence are classical contenders as theories of truth. In this paper we examine them instead as interacting factors in the dynamics of belief across epistemic networks. We construct an agent-based model of network contact in which agents are characterized not in terms of single beliefs but in terms of internal belief suites. Individuals update elements of their belief suites on input from other agents in order both to maximize internal belief coherence and to incorporate ‘trickled in’ elements of (...)
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  • 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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  • Robustness and Idealizations in Agent-Based Models of Scientific Interaction.Daniel Frey & Dunja Šešelja - 2020 - British Journal for the Philosophy of Science 71 (4):1411-1437.
    The article presents an agent-based model of scientific interaction aimed at examining how different degrees of connectedness of scientists impact their efficiency in knowledge acquisition. The model is built on the basis of Zollman’s ABM by changing some of its idealizing assumptions that concern the representation of the central notions underlying the model: epistemic success of the rivalling scientific theories, scientific interaction and the assessment in view of which scientists choose theories to work on. Our results suggest that whether and (...)
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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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  • Truth and Conformity on Networks.Aydin Mohseni & Cole Randall Williams - 2021 - Erkenntnis 86 (6):1509-1530.
    Typically, public discussions of questions of social import exhibit two important properties: they are influenced by conformity bias, and the influence of conformity is expressed via social networks. We examine how social learning on networks proceeds under the influence of conformity bias. In our model, heterogeneous agents express public opinions where those expressions are driven by the competing priorities of accuracy and of conformity to one’s peers. Agents learn, by Bayesian conditionalization, from private evidence from nature, and from the public (...)
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  • The Credit Incentive to Be a Maverick.Remco Heesen - 2019 - Studies in History and Philosophy of Science Part A 76:5-12.
    There is a commonly made distinction between two types of scientists: risk-taking, trailblazing mavericks and detail-oriented followers. A number of recent papers have discussed the question what a desirable mixture of mavericks and followers looks like. Answering this question is most useful if a scientific community can be steered toward such a desirable mixture. One attractive route is through credit incentives: manipulating rewards so that reward-seeking scientists are likely to form the desired mixture of their own accord. Here I argue (...)
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  • Some Lessons From Simulations of Scientific Disagreements.Dunja Šešelja - 2019 - Synthese 198 (Suppl 25):6143-6158.
    This paper examines lessons obtained by means of simulations in the form of agent-based models about the norms that are to guide disagreeing scientists. I focus on two types of epistemic and methodological norms: norms that guide one’s attitude towards one’s own theory, and norms that guide one’s attitude towards the opponent’s theory. Concerning I look into ABMs that have been designed to examine the context of peer disagreement. Here I challenge the conclusion that the given ABMs provide a support (...)
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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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  • Academic Superstars: Competent or Lucky?Remco Heesen - 2017 - Synthese 194 (11):4499-4518.
    I show that the social stratification of academic science can arise as a result of academics’ preference for reading work of high epistemic value. This is consistent with a view on which academic superstars are highly competent academics, but also with a view on which superstars arise primarily due to luck. I argue that stratification is beneficial if most superstars are competent, but not if most superstars are lucky. I also argue that it is impossible to tell whether most superstars (...)
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  • A Multidisciplinary Understanding of Polarization.Jiin Jung, Patrick Grim, Daniel J. Singer, Aaron Bramson, William J. Berger, Bennett Holman & Karen Kovaka - 2019 - American Psychologist 74:301-314.
    This article aims to describe the last 10 years of the collaborative scientific endeavors on polarization in particular and collective problem-solving in general by our multidisciplinary research team. We describe the team’s disciplinary composition—social psychology, political science, social philosophy/epistemology, and complex systems science— highlighting the shared and unique skill sets of our group members and how each discipline contributes to studying polarization and collective problem-solving. With an eye to the literature on team dynamics, we describe team logistics and processes that (...)
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  • Editorial Introduction to the Topical Issue “Computer Modeling in Philosophy”.Patrick Grim - 2019 - Open Philosophy 2 (1):653-656.
  • 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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