Rational analysis is an influential but contested account of how probabilistic modeling can be used to construct non-mechanistic but self-standing explanatory models of the mind. In this paper, I disentangle and assess several possible explanatory contributions which could be attributed to rational analysis. Although existing models suffer from evidential problems that question their explanatory power, I argue that rational analysis modeling can complement mechanistic theorizing by providing models of environmental affordances.

Ian Hacking (born in 1936, Vancouver, British Columbia) is most well-known for his work in the philosophy of the natural and social sciences, but his contributions to philosophy are broad, spanning many areas and traditions. In his detailed case studies of the development of probabilistic and statistical reasoning, Hacking pioneered the naturalistic approach in the philosophy of science. Hacking’s research on social constructionism, transient mental illnesses, and the looping effect of the human kinds make use of historical materials to shed (...) light on how developments in the social, medical, and behavioural sciences have shaped our contemporary conceptions of identity and agency. Hacking’s other contributions to philosophy include his work on the philosophy of mathematics (Hacking, 2014), philosophy of statistics, philosophy of logic, inductive logic (Hacking, 1965, 1979, 2001) and natural kinds (Hacking, 1991, 2007a). (shrink)

Universities are knowledge institutions. Compared to several other knowledge institutions (e.g. schools, government research organisations, think tanks), research universities have unusual, anarchic organisational features. We argue that such anarchic features are not a weakness. Rather, they reflect the special standing of research universities among knowledge institutions. We contend that the distributed, self-organising mode of knowledge production maintains a diversity of approaches, topics and solutions needed in frontier research, which involves generating relevant knowledge under uncertainty. Organisational disunity and inconsistencies should sometimes (...) be protected by institutional structures and procedures in order for research universities to best serve their purpose as knowledge institutions. The quality control for the knowledge produced stems from knowledge fields, clusters of knowledge and research that exist beyond the confines of individual organisations. The diversity of epistemic contributions is therefore kept in check by the order imposed by the internal logic of science as a social practice. Our argument provides a new defence for the autonomy of research conducted at universities. (shrink)