The Reliability of Scientific Communities: a Logical Analysis
Hanna Sofie van Lee

Abstract:
In the history of science, it has often occured that an entire community of scientists believes in a theory that is later proven to be wrong. For example, in 1915, Einstein and De Haas published a paper on the Einstein-De Haas effect. During the years after, experimental results showing that the effect was incorrect were ignored by the scientists in their field. Only ten years later it got accepted by the entire community that the results of the Einstein-De Haas experiment were false. There are many possible explanations for such a collective failure of a scientific community. Bayesian analyses of Kevin Zollman suggest that specific network structures can repair false beliefs more easily than others, and that varying the weights of beliefs (i.e., ensure the diversity of opinions) can also positively affect the reliability of scientific communities.

This thesis investigates the truth-tracking abilities of scientific communities from a logical perspective such that it can highlight the higher-order reasoning abilities of agents. The thesis starts with a contribution to the most relevant philosophical debates on truth and the social dimensions of science and knowledge. Then, a summary of other research on the relationship between the network of epistemic communities and their truth-tracking abilities will be given. Next, a Multi-agent Dynamic Evidence-based Logic will be introduced and it will be shown how to apply this to analyse the subjects under study. The final part of the thesis gives an overview of different conclusions that a logical analysis can give on the reliability of scientific communities. The main conclusion of this thesis is that the truth-tracking ability of scientific communities is greatly affected by the distributions of the bias evidence and distribution of the failures of the experiments. In fact, in the settings of this thesis, these distributions affect the behaviour of the agents more dominantly than the structure of the network or the weights of the bias evidence do.

Keywords: logic, philosophy