Martin Justin

Industry funding is often indispensable to scientific research, but it can also introduce systematic biases that align study outcomes with commercial interests. Recent philosophical work suggests treating funding disclosures as meta-evidence: evidence about the evidential force of first-order study results. This paper asks whether such meta-evidence can be used to improve collective inquiry. Using an agent-based model, we compare two strategies for aggregating evidence in the presence of industry sponsorship: down-weighting industry-funded results and adjusting them relative to publicly funded studies. The simulations show that both strategies are highly context-sensitive. Relative adjustment can correct for bias when public evidence is reliable and sufficiently broad, but it falls short when public data are noisy or sparse. Down-weighting depends on a difficult and partly arbitrary choice of discount weight. The results suggest that industry sponsorship can be epistemically relevant meta-evidence without yielding a straightforward rule for evidence aggregation.

We investigate the epistemic role of coherence in scientific reasoning, focusing on its use as a heuristic for filtering evidence. Using a novel computational model based on Bayesian networks, we simulate agents who update their beliefs under varying levels of noise and bias. Some agents treat reductions in coherence as higher-order evidence and interpret such drops as signals that something has gone epistemically awry, even when the source of error is unclear. Our results show that this strategy can improve belief accuracy in noisy environments but tends to mislead when evidence is systematically biased. We explore the implications for the rationality of coherence-based reasoning in science.

What is the rational response to a scientific disagreement? Many epistemologists argue that disagreement with an epistemic peer should generally lead to conciliation by lowering confidence in the disputed belief or even suspending judgment altogether. Although this conciliatory approach is widely regarded as a norm of individual rationality, its value in the context of collective scientific inquiry is less clear. Some have even raised concerns that conciliating in scientific disagreements may slow progress or reduce the efficiency of inquiry. In this paper, we introduce a novel agent-based model that captures key aspects of scientific disagreement by incorporating both epistemic norms, which govern belief revision, and zetetic norms, which guide how scientists pursue inquiry. Our results indicate that the effects of conciliating in the face of disagreement---whether detrimental or beneficial---depend on the zetetic norms that scientists follow. When they focus on exploiting the hypothesis that they believe is most likely to succeed, remaining steadfast is more effective. However, with exploratory scientists, conciliation does not negatively affect group performance. These findings highlight the critical role of zetetic norms in determining the rational response to disagreement in scientific practice.

The view that epistemic peers should conciliate in cases of disagreement---the Conciliatory View---had been an important view in the early days of the peer disagreement debate. Over the years, however, the view has been the target of severe criticism; an ''obituary'' was already written for the view, and, as a recent proclamation has it, there is ''no hope'' for it. In this paper, I will argue that we should keep the hope alive by defending the Conciliatory View of peer disagreement. The primary strategy of my defense will be to separate the claims made by the view specific to peer disagreement and claims that concern higher-order evidence more generally. This separation allows us to see which problems cannot be addressed in the context of peer disagreement alone. As I will argue, the upshot of making this distinction is that although the jury is still out on whether higher-order evidence should affect our first-order doxastic states, the Conciliatory View likely follows if it does.