The role of scientists as experts is crucial to public policymaking. However, the expert role is contested and unsettled in both public and scholarly discourse. In this paper, I provide a systematic account of the role of scientists as experts in policymaking by examining whether there are any normatively relevant differences between this role and the role of scientists as researchers. Two different interpretations can be given of how the two roles relate to each other. The separability view states that (...) there is a normatively relevant difference between the two roles, whereas the inseparability view denies that there is such a difference. Based on a systematic analysis of the central aspects of the role of scientists as experts – that is, its aim, context, mode of output, and standards, I propose a moderate version of the separability view. Whereas the aim of scientific research is typically to produce new knowledge through the use of scientific method for evaluation and dissemination in internal settings, the aim of the expert is to provide policymakers and the public with relevant and applicable knowledge that can premise political reasoning and deliberation. (shrink)

There has been a resurgence between two closely related discussions concerning modern science funding policy. The first revolves around the coherence and usefulness of the distinction between basic and applied science and the second concerns whether science should be free to pursue research according to its own internal standards or pursue socially responsible research agendas that are held accountable to moral or political standards. In this paper, I argue that the distinction between basic and applied science, and the concomitant debate (...) about freedom and social responsibility, require revision. I contend that the distinction can only be maintained in cases of _urgent science_. I go on to elucidate the notion of urgent science using a case study from research of the climate refugee crisis. (shrink)

Regarding the dichotomy between applied science and pure science, there are two apparently paradoxical facts. First, they are distinguishable. Second, the outcomes of pure sciences (e.g. scientific theories and models) are applicable to producing the outcomes of applied sciences (e.g. technological artefacts) and vice versa. Addressing the functional roles of applied and pure science, i.e. to produce design representation and science representation, respectively, I propose a new characterisation of the dichotomy that explains these two facts.

This article aims to answer what I call the “constitution question of engineering modeling”: in virtue of what does an engineering model model its target system? To do so, I will offer a category-theoretic, structuralist account of design, using the olog framework. Drawing on this account, I will conclude that engineering and scientific models are not only cognitively but also representationally indistinguishable. I will finally propose an axiological criterion for distinguishing scientific from engineering modeling.

From its inception in 1987 social epistemology has been divided into analytic and critical approaches, represented by Alvin I. Goldman and Steve Fuller, respectively. In this paper, the agendas and some basic ideas of ASE and CSE are compared and assessed by bringing into the discussion also other participants of the debates on the social aspects of scientific knowledge—among them Raimo Tuomela, Philip Kitcher and Helen Longino. The six topics to be analyzed include individual and collective epistemic agents; the notion (...) of scientific community; realism and constructivism; truth-seeking communities; epistemic and social values; science, experts, and democracy. (shrink)

Over time, various thematic classifications have been put forward to organize science into a coherent system of specialized areas of research. From an analysis of the historical evolution of the criteria used to distinguish the sciences from one another, I propose in this paper a quadripartite typology for the different thematic classification systems propounded by scholars throughout the centuries. Basically, I argue that the criteria used to differentiate the sciences have been alternately drawn from their respective subject matters, kinds of (...) knowledge, methods and aims. Then, I show that several reclassifications occurred in the thematic structure of science. Finally, I argue that such changes in the structure of learning displaced the modalities of contact between the objects, knowledge, methods and aims of the various branches of science, with the result of outlining reshaped intellectual territories conducive to the emergence of new areas of research. (shrink)