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Statistical analysis is often used to evaluate the strength of evidence for or against scientific hypotheses. Here we consider evidence measurement from the point of view of representational measurement theory, focusing in particular on the 0-points of measurement scales. We argue that a properly calibrated evidence measure will need to count up fr...

The persistent pervasiveness of small studies in empirical fields is regularly deplored in scientific discussions. Taken individually, higher-powered studies are more likely to be truth-conducive. However, are they also beneficial for the wider performance of truth-seeking communities? We study the impact of sample sizes on collective exploration d...

When solving a complex problem in a group, should we always choose the best available solution? In this paper, I build simulation models to show that, surprisingly, a group of agents who randomly follow a better available solution than their own can end up outperforming a group of agents who follow the best available solution. The reason for this r...

Belief polarization is the tendency for individuals with opposing beliefs to predictably disagree more upon being exposed to certain types of evidence. A variety of recent papers have argued that many of the core empirical results surrounding this effect are consistent with standard Bayesian or approximately-Bayesian theories of rationality. I argu...

Belief polarization occurs when individuals diverge in their beliefs about some hypothesis when updating on certain kinds of evidence. It a persistent feature in society, with important ramifications for scientific, political and cultural discourse. Conventionally, belief polarization has often been treated as a consequence of irrationality. Howeve...

The accuracy-first program attempts to ground epistemology in the norm that one’s beliefs should be as accurate as possible, where accuracy is measured using a scoring rule. We argue that considerations of scientific progress suggest that such a monism about epistemic value is untenable. In particular, we argue that counterexamples to the standar...

Belief polarization occurs when the beliefs of agents diverge upon updating on certain types of evidence. Recent research indicates that belief can arise even amongst rational agents \cite{Jern_Polarization, Kelly_2008, O_Connor_Polarization}. Although the specific mechanisms differ, I distinguish two general origins of belief polarization. First i...

Is social and cognitive diversity beneficial for scientific knowledge production? How do we promote diversity in science? Are there gender or racial gaps in productivity, quality, or citation in academic publications? What are the potential causes for such gaps, and how do we close them? In the past few years, a new subfield in philosophy of scienc...

We study the epistemic success of different data collection strategies. We develop a computational multi-agent model of the scientific process that jointly formalizes its core aspects: data collection, data explanation, and social learning. We find that agents who choose new experiments at random develop the most accurate accounts of the world. On ...

Belief polarization occurs when individuals with opposing initial beliefs strengthen their beliefs in response to the same evidence. In previous work (“Disagreement, Dogmatism, and Belief Polarization,” Journal of Philosophy 2008), I explored the hypothesis that the psychological mechanisms that give rise to belief polarization are rational one...

This study investigates how belief dynamics and social network structures generate different patterns of social change and diversity. The two belief dynamics studied here are indirect minority influence and random drift; the former is parameterized by a leniency threshold ($\lambda$) and the later by an error rate ($\epsilon$). The patterns of soci...

Standard articulations of Inference to the Best Explanation (IBE) imply the uniqueness claim that exactly one explanation should be inferred in response to an explanandum. This claim has been challenged as being both too strong (sometimes agnosticism between candidate explanatory hypotheses seems the rational conclusion) and too weak (in cases wher...

A well-known result by Diaconis and Zabell examines when a shift from a prior to a posterior can be represented by conditionalization. This paper extends their result and connects it to the reflection principle and common priors. A shift from a prior to a set of posteriors can be represented within a conditioning model if and only if the prior and ...