Scientific Polarization

Contemporary societies are often "polarized", in the sense that sub-groups within these societies hold stably opposing beliefs, even when there is a fact of the matter. Extant models of polarization do not capture the idea that some beliefs are true and others false. Here we present a model, based on the network epistemology framework of Bala and Goyal ["Learning from neighbors", \textit{Rev. Econ. Stud.} \textbf{65}(3), 784-811 (1998)], in which polarization emerges even though agents gather evidence about their beliefs, and true belief yields a pay-off advantage. The key mechanism that generates polarization involves treating evidence generated by other agents as uncertain when their beliefs are relatively different from one's own.Comment: 22 pages, 5 figures, author final versio

Do as I Say, Not as I Do, or, Conformity in Scientific Networks

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 (or more) possible actions yields the better outcome. We find a range of possible outcomes, including stable polarization in belief and action. The model results are sensitive to network structure. In general, though, conformity has a negative effect on a community's ability to reach accurate consensus about the world

Endogenous Epistemic Factionalization

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

Do as I Say, Not as I Do, or, Conformity in Scientific Networks

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 (or more) possible actions yields the better outcome. We find a range of possible outcomes, including stable polarization in belief and action. The model results are sensitive to network structure. In general, though, conformity has a negative effect on a community's ability to reach accurate consensus about the world

Endogenous Epistemic Factionalization

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

Endogenous Epistemic Factionalization

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.Comment: 23 pages, 10 figures. Forthcoming in Synthes

Modeling How False Beliefs Spread

Effective political decision-making requires actors to have accurate beliefs about the domain in which they are acting. But false beliefs about matters of fact are widespread. Such false beliefs are often explained by appeal to individual epistemic factors, such as personal reasoning biases. But these individual factors are only part of the story, as most of what we know, or believe, we have learned directly from other people. Recently, philosophers have begun to use formal methods, including mathematical models and computer simulations, to explore various aspects of social epistemology. This chapter will review the recent literature in the formal social epistemology of false belief. We introduce background work in social epistemology, explain how researchers use models to inform the science of false belief, and discuss what these models tell us about how politically or economically motivated actors shape public belief by exploiting social factors

Endogenous Epistemic Factionalization: A Network Epistemology Approach

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

Do as I Say, Not as I Do, or, Conformity in Scientific Networks

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 (or more) possible actions yields the better outcome. We find a range of possible outcomes, including stable polarization in belief and action. The model results are sensitive to network structure. In general, though, conformity has a negative effect on a community's ability to reach accurate consensus about the world