Online research in philosophy

This paper examines the form of mental representation of scientific theories in scientists and nonscientists. It concludes that images and schemas are not the appropriate form of mental representation for scientific theories but that mental models and perceptual symbols do seem appropriate for representing physical/mechanical phenomena. These forms of mental representation are postulated to have an analogical relation with the world and it is this relationship that gives them strong explanatory power. It is argued that the construct of naïve theories as used in developmental psychology may be the appropriate form of mental representation for non physical/mechanical domains. The paper adopts a strong form of psychologism in the philosophy of science and argues that model-based approaches to scientific theories are more appropriate forms of representation for scientific theories than the formalist approaches that dominate current philosophy of science.

The purpose of this paper is to suggest that models in scientific practice can be conceived of as epistemic artifacts. Approaching models this way accommodates many such things that working scientists themselves call models but that the semantic conception of models does not duly recognize as such. That models are epistemic artifacts implies, firstly, that they cannot be understood apart from purposeful human activity; secondly, that they are somehow materialized inhabitants of the intersubjective field of that activity; and thirdly, that they can function also as knowledge objects. We argue that models as epistemic artifacts provide knowledge in many other ways than just via direct representative links. To substantiate our view we use a language‐technological artifact, a parser, as an example.

In this paper, I distinguish scientific models in three kinds on the basis of their ontological status—material models, mathematical models and fictional models, and develop and defend an account of fictional models as fictional objects—i.e. abstract objects that stand for possible concrete objects.

This paper explores a new reason for preferring a model-theoretic approach to understanding the nature of scientific theories. Identifying the models in philosophers' model-theoretic accounts of theories with the concepts in cognitive scientists' accounts of categorization suggests a structure to families of models far richer than has commonly been assumed. Using classical mechanics as an example, it is argued that families of models may be "mapped" as an array with "horizontal" graded structures, multiply hierarchical "vertical" structures, and local "radial" structures. These structures promise important implications for how scientific theories are learned and used in actual scientific practice.

In this paper the topic of the relations between scientific theories and scientific models is tackled by considering the former as hypothetical scientific representations and the latter as fictive scientific representations. A classification of the models is also proposed.

Models are generally used by scientists to obtain predictions and to provide explanations about phenomena. Their predictive and explanatory power is generally thought of as depending on their representative power. It is still not clear, though, in virtue of which features models allow scientists to draw inferences about the system they stand for. In this paper, I focus on a special kind of models, namely imaginary models (I-models) such as the simple pendulum. The main question I address is: how do scientists use I-models in representing target systems? First, I propose a clarification of the very notion of representation, by emphasizing the importance of what I call the format of a representation to the inferences cognitive agents can draw from it. Then, I analyze the various representational relationships that are in play in the use of I-models. I finally conclude that there is no special semantics to be applied to I-models, and that the study of the representational power of models in general should instead focus on the variety of the formats that are used in scientific practice.

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.

A role of models in scientific explanation and insufficiency of unification view of explanation are discussed. Model is constructed by abstracting some important elements from the real world. There are too many complicated interactions in the real world to calculate, but model makes calculations possible. However, that is only part of importance of model in scientific activity. At the first sight, we think that it is better for scientists to use models including more elements (it means the model is closer to the real world), than to use models with less elements. Nevertheless, even when scientists can calculate by using more complex models, they usually use more simple models. This fact gives us the key to clarify an important role of models in scientific explanation. In this presentation, I would like to show that using simple models as possible makes it possible to explain phenomena thus only achieving unification is insufficient for explanation.

The usual question, “Are models fictions?” is replaced by the question, “Should scientific models be regarded as works of fiction?” This makes it clear that the issue is not one of definition but of interpretation. First one must distinguish between the ontology of scientific models and their function in the practice of science. Theoretical models and works of fiction are ontologically on a par, their both being creations of human imagination. It is their differing functions in practice that makes it inappropriate to regard scientific models as works of fiction. Three reasons for thinking scientific models should be regarded as works of fiction are rejected. First, scientists themselves sometimes invoke the idea of fictions in their discussions of specific models. Second, many scientific models are physically impossible to realize in the real world. Third, regarding scientific models as works of fiction supports a general fictionalist understanding of scientific theories. It is concluded that promoting the general idea that scientific models are works of fiction unnecessarily supports attacks on the legitimacy of science itself.