University of Helsinki
At the next Perspectives on Science seminar on Monday 1.11., Dingmar van Eck (University of Amsterdam) will give a presentation titled “Mechanist Idealisation in Systems Biology”. The seminar takes place in Zoom from 14:15 to 15:45.
Perspectives on Science is a weekly research seminar which brings together experts from science studies and philosophy of science. It is organized by TINT – Centre for Philosophy of Social Science at the University of Helsinki. More information about the seminar here.
To join the seminar, please sign up here.
Abstract:
This paper adds to the philosophical literature on mechanistic explanation by elaborating two related explanatory functions of idealisation in mechanistic models. The first function involves explaining the presence of structural/organizational features of mechanisms by reference to their role as difference-makers for performance requirements. The second involves tracking counterfactual dependency relations between features of mechanisms and features of mechanistic explanandum phenomena. To make these functions salient, we relate our discussion to an exemplar from systems biological research on the mechanism for countering heat shock—the heat shock response (HSR) system—in Escherichia coli (E.coli) bacteria. This research also reinforces a more general lesson: ontic constraint accounts in the literature on mechanistic explanation provide insufficiently informative normative appraisals of mechanistic models. We close by outlining an alternative view on the explanatory norms governing mechanistic representation.
Author bio:
Dingmar van Eck is assistant professor in philosophy of science at the University of Amsterdam, the Netherlands, and postdoctoral researcher in philosophy of science at Ghent University, Belgium. His research focuses on scientific explanation, explanatory power, and scientific methods. His current research is focused on a variety of issues related to scientific explanation in various scientific disciplines, such as biology, engineering science, cognitive science, and neuroscience, as well as general issues concerning scientific explanation. Recent research foci have been, inter alia, roles of idealizations in explanatory models in systems biology, the explanatory value of dynamical models in cognitive science, the applicability of philosophical accounts of mechanism discovery to cognitive scientific practice, and explications of inference to the best explanation in failure analysis in engineering science. What unites these investigations is a pluralist approach to the study of scientific explanation that takes seriously (and makes precise) the idea that scientific explanation is not a unitary notion but, rather, that different kinds of scientific explanation are suited for different explanatory requests.