CFA: 8th Scientific Understanding and Representation (SURe) annual workshop   Call for abstracts        We invite authors to submit abstracts of up to 750-words for the upcoming...

Can we do philosophy by writing fiction, drawing, designing a game, or telling a story? Submit work to this special issue honouring the legacy of Helen De Cruz.

Julian Huxley is remembered as the author of his landmark 1942 Evolution: The Modern Synthesis. Nowadays, however, he is criticized for having reduced biology to the selection of genes. Some have nevertheless suggested that Huxley’s biological views were more expansive—including rather than excluding issues regarding development or environment. In this paper, using hitherto unexamined sources, I show that Huxley’s developmental understanding of animal characters was rooted in his education at Oxford in the early 20th century. From embryologically and physiologically trained Oxford teachers, he learned to see characters as things that could not be predicted from the cell’s physico-chemical properties. Characters arose anew through dynamic interactions between parts. Huxley and his teachers labeled these as “epigenetic” processes that integrated multiple cross-pollinating causes such as heredity and development. After briefly exploring Huxley’s understanding of character development, I show how we can get to grips with Huxley’s biological views by exploring the context of his education at Oxford from 1906 to 1909. I then show how Huxley received and used these ideas, before I illustrate how they played an important role in his academic and socio-political work.

Some philosophers have worried that AI threatens meaning in life by making humans redundant in the workplace or by relegating them to menial tasks. While these worries may be justified, there's ...

Many successful explanations show how causally individuated parts are responsible for the occurrence of the phenomena that scientists seek to explain. On this view, parts that are chosen only by convention, and related only through correlations, cannot possibly figure in successful explanations. This is because without some form of causal grounding, it seems unintelligible why any explanatory relation between these parts and the phenomenon of interest would hold. This problem is particularly pronounced in functional connectivity models (FC) in neuroscience. These models typically represent time series of recurrent neural activity in conventionally determined spatial regions (as a network’s nodes) and synchronization likelihoods among these time series (as its edges). Many neuroscientists and philosophers maintain that because of this, FC models cannot provide explanations. We formulate this problem more precisely and then show that it rests on an impoverished interpretation of scientific models in general and FC models in particular. We then provide a positive account of how FC models provide a variety of neuroscientific explanations.

Metascience -

We are inviting abstracts for the Second HPS of Biodiversity Meeting.

April 3 - 4, 2026