Abstract

Rationalities of Knowledge Production: On Transformations of Objects, Technologies and Information in Biomedicine and the Life Sciences. Since decades, scientific change has been interpreted in the light of of paradigm shifts and scientific revolutions. The Kuhnian interpretation of scientific change however is now more and more confronted with non‐disciplinary thinking in both, science and studies on science. This paper explores how research in biomedicine and the life sciences can be characterized by different rationalities, sometimes converging, sometimes contradictory, all present at the same time with varying ways of influence, impact, and visibility. In general, the rationality of objects is generated by fitting new objects and findings into a new experimental context. The rationality of hypotheses is a move towards the construction of novel explanatory tools and models. This is often inseparable meshing with the third, the technological rationaliy, in which a technology‐driven, self‐supporting and sometimes self‐referential refinement of methods and technologies comes along with an extension into other fields. During the second and the third phase, the new and emerging fields tend to expand their explanatory reach not only across disciplinary boundaries but also into the social sphere, creating what has been characterized as “exceptionalism” (e.g. genetic exceptionalism or neuro‐exceptionalism). Finally, recent biomedicine and life‐sciences reach a level in which experimental work becomes more and more data‐driven because the technologically constructed experimental systems generate a plethora of findings (data) which at some point start to blur the original hypotheses. For the rationality of information the materiality of research practices becomes secondary and research objects are more and more getting out of sight. Finally, the credibility of science as a practice becomes more and more dependent on consensus about the applicability and relevance of its results. The rationality of interest (and accountability) has become more and more characteristic for a research process which is no longer primarily determined by the desire for knowledge but by the desire for relevance. This paper explores in which ways object‐driven and hypotheses‐driven experimental life‐sciences transformed into domains of experimental research evolving in a technologically constructed, data‐driven environment in which they are subjected to constant morphing due to the forces of different rationalities.