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In this paper we explore the constraints that our preferred account of scientific representation places on the ontology of scientific models. Pace the Direct Representation view associated with Arnon Levy and Adam Toon, we argue that scientific models should be thought of as imagined systems, and clarify the relationship between imagination and representation.¹

Novels and scientific models have in common being functional kinds, being products of make-believe, essentially involving narration, being schematic/sketchy, having cognitive functions, concretising abstract ideas, having representative functions without necessarily having truth values, essentially involving scenarios, and being instruments for the filtering of experience. Suspension of disbelief is required for the understanding of both novels and models. Novels refer to real world instantiations of some, or all of, the concepts of actions, subjectivity, situations, and things. Novels involve implicitly two kinds of models: Internal models of the Storyworld and External models of the slices of reality that pertain to the Storyworld. They filter experiences and emotions. Keywords: Scientific models, literary models, make-believe, literary emotions, believability

Upholders of fictionalism about scientific models have not yet successfully explained how scientists can learn about the real world by making comparisons between models and the real phenomena they stand for. In this paper I develop an account of model-world comparisons in terms of what I take to be the best antirealist analyses of comparative claims that emerge from the current debate on fiction.

It is frequently acknowledged that some scientific models do not have a target. In that case, it is not clear how surrogative reasoning is possible. In this article, I contend that every model has a target. I argue that targets should not be identified with selected phenomena or with selected portions or aspects of the real world. I intend to show that the target of any model is always the outcome of a complex process of construction, a process that cannot be accounted for solely by means of abstraction from the phenomena. I conclude that although all models have a fixed target, their domain of application may change or even be empty.

Roman Frigg and others have developed a general epistemological argument designed to cast doubt on the capacity of a broad range of mathematical models (including many climate models) to generate “decision relevant predictions.” In this article, we lay out the structure of their argument—an argument by analogy—with an eye to identifying points at which certain epistemically significant distinctions might limit the force of the analogy. Finally, some of these epistemically significant distinctions are introduced and defended as relevant to a great many of the predictive mathematical modeling projects employed in contemporary climate science.

Issue Title: MODELS AND SIMULATIONS 2

Issue Title: MODELS AND SIMULATIONS. Guest Editors: Roman Frigg, Stephan Hartmann and Cyrille Imbert

Issue Title: LOGIC AND PHILOSOPHY OF SCIENCE IN THE FOOTSTEPS OF E. W. BETH

Issue Title: THE ONTOLOGY OF SCIENTIFIC MODELS. Guest Editor: Gabriele Contessa

Issue Title: MODELS AND SIMULATIONS 2