Online research in philosophy

Most scientific models are not physical objects, and this raises important questions. What sort of entity are models, what is truth in a model, and how do we learn about models? In this paper I argue that models share important aspects in common with literary fiction, and that therefore theories of fiction can be brought to bear on these questions. In particular, I argue that the pretence theory as developed by Walton (1990, Mimesis as make-believe: on the foundations of the representational arts. Harvard University Press, Cambridge/MA) has the resources to answer these questions. I introduce this account, outline the answers that it offers, and develop a general picture of scientific modelling based on it.

What are models that they may be used to represent reality? Here is a first pass. Models are objects that can be used to represent reality by exhibiting a designated similarity to physical objects. To be more specific, I need to indicate the kinds of objects models may be and how they may exhibit a designated similarity to real objects. My prototype for a model is a standard road map. This is a physical object (usually made of paper) that I would say represents a terrain in virtue of quite specific spatial similarities. I move on to scale models, such as Watson?s original physical model of DNA. Next I treat abstract models, which are abstract objects not to be confused with the linguistic entities that may be used to characterize them. Finally, I discuss theoretical models which I now regard as abstract models constructed according to the principles of an overarching theory. Serious use of the notion of similarity is often criticized on the ground that anything may be similar to anything else in some respect or other. It is also often claimed that there is no satisfactory general characterization of similarity. I exploit these facts by insisting that claims of similarity between models and real objects must be accompanied by (perhaps tacit) specifications of the respects and the degrees to which similarity is claimed. Such specifications cannot be intrinsic to either a model or a physical object, but must be supplied by those using the model according to their own interests. Thus, taking the relationship between models and physical systems to be one of similarity implies that nothing is intrinsically a model of anything. It is only by intention, or convention, that some object becomes a model of some physical things. For models, at least, the motto is: No representation without representers. Moreover, no general characterization of similarity is needed. It is enough that we can say what counts as sufficiently similar for specific respects. This we can certainly do.

I. Introduction. Philosophical discussions of models and modeling in the biological sciences have exploded in the last few decades. Given that there are three-dimensional models of DNA in molecular genetics, individual-based computer simulations in population ecology, statistical models in paleontology, diffusion models in population genetics, and remnant models in taxonomy, we clearly should have a philosophical account of such models and their relation to the world. In this essay, I provide a critical survey of the accounts of models provided by philosophers of science and philosophers of biology including models as analogies, relational structures, partially independent representations, and material objects. However, there is much, much more work to be done.

The personal computer has become the primary research tool in many scientific and engineering disciplines. The role of the computer has been extended to be an experimental and modelling tool both for convenience and sometimes necessity. In this paper some of the relationships between real models and virtual models, i.e. models that exist only as programs and data structures, areexplored. It is argued that the shift from experimenting with real objects to experimentation with computer models and simulations may also require a new approach for evaluating scientific theories derived from these models. Accepting the additional sets of assumptions that are associated with computer models and simulations requires ‘leaps of faith’, which we may not want to make in order to preserve scientific rigor. There are problems in providing acceptable arguments and explanations as to why a particular computer model or simulation should be judged scientifically sound, plausible, or even probable. These problems not only emerge from models that are particularly complex, but also in models that suffer from being too simplistic.

I advance an objection to Graham Priest’s account of fictional entities as nonexistent objects. According to Priest, fictional characters do not have, in our world, the properties they are represented as having; for example, the property of being a bank clerk is possessed by Joseph K. not in our world but in other worlds. Priest claims that, in this way, his theory can include an unrestricted principle of characterization for objects. Now, some representational properties attributed to fictional characters, a kind of fictional entities, involve a crucial reference to the world in which they are supposed to be instantiated. I argue that these representational properties are problematic for Priest’s theory and that he cannot accept an unrestricted version of the principle of characterization. Thus, while not refuting Priest’s theory, I show that it is no better off than other Meinongian theories.

Scientific models occupy centre stage in scientific practice. Correspondingly, in recent literature in the philosophy of science, scientific models have been a focus of research. However, little attention has been paid so far to the ontology of scientific models. In this essay, I attempt to clarify the issues involved in formulating an informatively rich ontology of scientific models. Although no full-blown theory—containing all ontological issues involved—is provided, I make several distinctions and point to several characteristic properties exhibited by scientific models that are relevant for individuating scientific models.

This essay explains why creationism about fictional characters is an abject failure. Creationism about fictional characters is the view that fictional objects are created by the authors of the novels in which they first appear. This essay shows that, when the details of creationism are filled in, the hypothesis becomes far more puzzling than the linguistic data it is used to explain. No matter how the creationist identifies where, when and how fictional objects are created, the proposal conflicts with other strong intuitions we have about fictional characters. CiteULike Connotea Del.icio.us Digg Reddit Technorati What's this?

Introduction -- What is fiction? -- Realism about fictional objects -- Fictional objects are nonexistents -- Worlds and truth : fictional worlds, possible worlds, and impossible worlds -- Fictional entities are abstract artifacts -- Irrealism : fiction and intentionality -- Some fictionalists -- Fictionalism about possible worlds -- Moral fictionalism -- Retrospect.

There has recently been considerable interest in accounts of fiction which treat fictional characters as abstract objects. In this paper I argue against this view. More precisely I argue that such accounts are unable to accommodate our intuitions that fictional negative existentials such as “Raskolnikov doesn’t exist” are true. I offer a general argument to this effect and then consider, but reject, some of the accounts of fictional negative existentials offered by abstract object theorists. I then note that some of the sort of data invoked by the abstract object theorist in fact cuts against her position. I concludle that we should not regard fictional characters as abstract objects but rather should adopt a make-believe theoretic account of fictional characters along the lines of those developed by Ken Walton and others.

Scientific models invariably involve some degree of idealization, abstraction, or fictionalization of their target system. Nonetheless, I argue that there are circumstances under which such false models can offer genuine scientific explanations. After reviewing three different proposals in the literature for how models can explain, I shall introduce a more general account of what I call model explanations , which specify the conditions under which models can be counted as explanatory. I shall illustrate this new framework by applying it to the case of Bohr’s model of the atom, and conclude by drawing some distinctions between phenomenological models, explanatory models, and fictional models.