How Models Are Used to Represent Reality

Most recent philosophical thought about the scientific representation of the world has focused on dyadic relationships between language-like entities and the world, particularly the semantic relationships of reference and truth. Drawing inspiration from diverse sources, I argue that we should focus on the pragmatic activity of representing, so that the basic representational relationship has the form: Scientists use models to represent aspects of the world for specific purposes. Leaving aside the terms “law ” and “theory, ” I distinguish principles, specific conditions, models, hypotheses, and generalizations. I argue that scientists use designated similarities between models and aspects of the world to form both hypotheses and generalizations. 1. Introduction. Within the philosophy of scienc

An Agent-Based Conception of Models and Scientific Representation

Beginning with hierarchical view of theories and models, I argue for an intentional conception of representation in science that requires bringing scientific agents and their intentions into the picture. So the formula is: Agents 1) intend; 2) to use model, M; 3) to represent a part of the world, W; 4) for some purpose, P. This conception legitimates using similarity as the basic relationship between models and the world. This whole approach is further supported by a brief exposition of some recent work in cognitive, or usage-based, linguistics. Finally, with all the above as background, I examine the recently much discussed idea that abstract scientific models should be thought of as fictional entities

Representing with Physical Models

Physical models have long been used to represent a great many things. By and large, however, the representational powers of physical models have been taken for granted in recent philosophy of science. Interest has focused on more ubiquitous and seemingly more important theoretical models, particularly those found in mathematical physics. In this paper, I focus on physical models, comparing them with theoretical models and finally with recently popular computational models. My aim is to show that the representational aspects of models used in science are fundamentally the same across all three categories of models