Scientific Polarization

TL;DR

This paper introduces a network epistemology model explaining how societal polarization can persist even when agents seek truth, by incorporating uncertainty in evidence from differing beliefs.

Contribution

It presents a novel model of polarization that accounts for the role of belief differences and evidence uncertainty, extending previous epistemology frameworks.

Findings

Polarization emerges despite agents seeking true beliefs.

Belief differences increase evidence uncertainty, reinforcing polarization.

The model explains stable opposing belief groups in societies.

Abstract

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.