Imagination extended and embedded : artifactual versus fictional accounts of models

This paper presents an artifactual approach to models that also addresses their fictional features. It discusses first the imaginary accounts of models and fiction that set model descriptions apart from imagined-objects, concentrating on the latter (e.g., Frigg in Synthese 172(2):251-268, 2010; Frigg and Nguyen in The Monist 99(3):225-242, 2016; Godfrey-Smith in Biol Philos 21(5):725-740, 2006; Philos Stud 143(1):101-116, 2009). While the imaginary approaches accommodate surrogative reasoning as an important characteristic of scientific modeling, they simultaneously raise difficult questions concerning how the imagined entities are related to actual representational tools, and coordinated among different scientists, and with real-world phenomena. The artifactual account focuses, in contrast, on the culturally established external representational tools that enable, embody, and extend scientific imagination and reasoning. While there are commonalities between models and fictions, it is argued that the focus should be on the fictional uses of models rather than considering models as fictions.Peer reviewe

Models and Fiction

Articl

Viewing-as explanations and ontic dependence

According to a widespread view in metaphysics and philosophy of science, all explanations involve relations of ontic dependence between the items appearing in the explanandum and the items appearing in the explanans. I argue that a family of mathematical cases, which I call “viewing-as explanations”, are incompatible with the Dependence Thesis. These cases, I claim, feature genuine explanations that aren’t supported by ontic dependence relations. Hence the thesis isn’t true in general. The first part of the paper defends this claim and discusses its significance. The second part of the paper considers whether viewing-as explanations occur in the empirical sciences, focusing on the case of so-called fictional models. It’s sometimes suggested that fictional models can be explanatory even though they fail to represent actual worldly dependence relations. Whether or not such models explain, I suggest, depends on whether we think scientific explanations necessarily give information relevant to intervention and control. Finally, I argue that counterfactual approaches to explanation also have trouble accommodating viewing-as cases

Is Captain Kirk a natural blonde? Do X-ray crystallographers dream of electron clouds? Comparing model-based inferences in science with fiction

Scientific models share one central characteristic with fiction: their relation to the physical world is ambiguous. It is often unclear whether an element in a model represents something in the world or presents an artifact of model building. Fiction, too, can resemble our world to varying degrees. However, we assign a different epistemic function to scientific representations. As artifacts of human activity, how are scientific representations allowing us to make inferences about real phenomena? In reply to this concern, philosophers of science have started analyzing scientific representations in terms of fictionalization strategies. Many arguments center on a dyadic relation between the model and its target system, focusing on structural resemblances and “as if” scenarios. This chapter provides a different approach. It looks more closely at model building to analyze the interpretative strategies dealing with the representational limits of models. How do we interpret ambiguous elements in models? Moreover, how do we determine the validity of model-based inferences to information that is not an explicit part of a representational structure? I argue that the problem of ambiguous inference emerges from two features of representations, namely their hybridity and incompleteness. To distinguish between fictional and non-fictional elements in scientific models my suggestion is to look at the integrative strategies that link a particular model to other methods in an ongoing research context. To exemplify this idea, I examine protein modeling through X-ray crystallography as a pivotal method in biochemistry

Informaticology: combining Computer Science, Data Science, and Fiction Science

Motivated by an intention to remedy current complications with Dutch terminology concerning informatics, the term informaticology is positioned to denote an academic counterpart of informatics where informatics is conceived of as a container for a coherent family of practical disciplines ranging from computer engineering and software engineering to network technology, data center management, information technology, and information management in a broad sense. Informaticology escapes from the limitations of instrumental objectives and the perspective of usage that both restrict the scope of informatics. That is achieved by including fiction science in informaticology and by ranking fiction science on equal terms with computer science and data science, and framing (the study of) game design, evelopment, assessment and distribution, ranging from serious gaming to entertainment gaming, as a chapter of fiction science. A suggestion for the scope of fiction science is specified in some detail. In order to illustrate the coherence of informaticology thus conceived, a potential application of fiction to the ontology of instruction sequences and to software quality assessment is sketched, thereby highlighting a possible role of fiction (science) within informaticology but outside gaming

A pragmatic approach to the ontology of models

What are scientific models? Philosophers of science have been trying to answer this question during the last three decades by putting forward a number of different proposals. Some say that models are best understood as abstract Platonic objects or fictional entities akin to Sherlock Holmes, while others focus on their mathematical nature and see them as set theoretical structures. Although each account has its own strengths in offering various insights on the nature of models, several objections have been raised against these views which still remain unanswered, making the debate on the ontology of models seem unresolvable. The primary aim of this paper is to show that a large part of these difficulties stems from an inappropriate reading of the main question on the ontology of models as a purely metaphysical question. Building on Carnap, it is argued that the question of the ontology of scientific models is either (i) an internal theoretical question within an already accepted linguistic framework or (ii) an external practical question regarding the choice of the most appropriate form of language in order to describe and explain the practice of scientific modelling. The main implication of this view is that the question of the ontology of models becomes a means of probing other related questions regarding the overall practice of scientific modelling, such as questions on the capacity of models to provide knowledge and the relation of models with background theories

Modelling virtual urban environments

In this paper, we explore the way in which virtual reality (VR) systems are being broadened to encompass a wide array of virtual worlds, many of which have immediate applicability to understanding urban issues through geocomputation. Wesketch distinctions between immersive, semi-immersive and remote environments in which single and multiple users interact in a variety of ways. We show how suchenvironments might be modelled in terms of ways of navigating within, processes of decision-making which link users to one another, analytic functions that users have to make sense of the environment, and functions through which users can manipulate, change, or design their world. We illustrate these ideas using four exemplars that we have under construction: a multi-user internet GIS for Londonwith extensive links to 3-d, video, text and related media, an exploration of optimal retail location using a semi-immersive visualisation in which experts can explore such problems, a virtual urban world in which remote users as avatars can manipulate urban designs, and an approach to simulating such virtual worlds through morphological modelling based on the digital record of the entire decision-making process through which such worlds are built

Mathematical Representation: Playing a Role

The primary justification for mathematical structuralism is its capacity to explain two observations about mathematical objects, typically natural numbers. Non-eliminative structuralism attributes these features to the particular ontology of mathematics. I argue that attributing the features to an ontology of structural objects conflicts with claims often made by structuralists to the effect that their structuralist theses are versions of Quine's ontological relativity or Putnam's internal realism. I describe and argue for an alternative explanation for these features which instead explains the attributes them to the mathematical practice of representing numbers using more concrete tokens, such as sets, strokes and so on

Fiction and Thought Experiment - A Case Study

Many philosophers are very sanguine about the cognitive contributions of fiction to science and philosophy. I focus on a case study: Ichikawa and Jarvis’s account of thought experiments in terms of everyday fictional stories. As far as the contribution of fiction is not sui generis, processing fiction often will be parasitic on cognitive capacities which may replace it; as far as it is sui generis, nothing guarantees that fiction is sufficiently well-behaved to abide by the constraints of scientific and philosophical discourse, not even by the minimum requirements of conceptual and logical coherence