Epistemology Of Models Research Articles

Can fiction and veritism go hand in hand?

The epistemology of models has to face a conundrum: models are often described as highly idealised, and yet they are considered to be vehicles for scientific explanations. Truth-oriented—veritist—conceptions of explanation seem thereby undermined by this contradiction. In this article, I will show how this apparent paradox can be avoided by appealing to the notion of fiction. If fictionalism is often thought to lead to various flavours of instrumentalism, thereby weakening the veritist hopes, the fiction view of models offers a framework much richer than it seems at first sight. To do so, I will call upon the concepts of modality, counterfactual structure and credible worlds. In the end, veritism of explanation and fiction can indeed go hand in hand, but the scope of explanations we can hope to draw from models must be more precisely delineated.

A dialectical vision of mathematical models of complex systems

Purpose Mathematical models are constructed at the interface between practice, experience and theories. The function of models puts us on guard against the privilege granted to what is accepted as abstract and formal, and at the same time puts us on guard against a static and phenomenological conception of knowledge. The epistemology of models does not suppress in any way the objectives of science: only, a dogmatic conception concerning truth is removed, and dynamic and dialectical aspects of monitoring are stressed to establish the most viable model. The purpose of this paper is to examine hybrid methodologies (inductive-deductive) that may either propose hypothetical causal relations and seek support for them in field data or detect causal relations in field data and propose hypotheses for the relations detected. Design/methodology/approach The authors follow a dialectical analysis for a type of inductive-deductive model. Findings In this work, the authors present an inductive-deductive methodology whose practical result satisfies the Hegelian dialectic. The consequent implication of their mutual reciprocal integration produces abstractions from the concrete that enable thought. The real problem in this case is a given ontological system or reality. Originality/value The essential elements of the models – variables, equations, simulation and feedback – are studied using a dialectic Hegelian theory.

Key-Aspects of Scientific Modeling Exemplified by School Science Models: Some Units for Teaching Contextualized Scientific Methodology

Models and modeling are core elements of scientific methods and consequently also are of key importance for the conception and teaching of scientific methodology. The epistemology of models and its transfer and adaption to nature of science education are not, however, simple themes. We present some conceptual units in which school science models are used for exemplifying aspects and issues that we consider crucial for an understanding of models and modelling, such as: the perspectival and conceptual character of models, their mediating, interpretive and predictive function, and the nature and potentialities of theoretical–mathematical models. The models used to exemplify these aspects are some particle models of matter, Newton’s two-body planetary model, and models of mechanical oscillations. The units are designed as a NOS education series for teachers and upper high school students, but they could also be used independently. The underlying concept for designing the units is based on teaching scientific methodology explicitly and contextualized in curricular science content.

Special issues on Epistemology of Modelling and Simulation

Special issues on Epistemology of Modelling and Simulation

Epistemology of Modeling and Simulation: Variations on a Theme

The three papers that follow formed part of a 3-day conference in the Epistemology of Modeling and Simulation at the University of Pittsburgh, 1st through 3rd April 2011 (www.modelingepistemology.pitt.edu). They reflect variations on a theme that emerged in the course of the conference both in more traditional paper sessions and in breakout workshops on specific computational models: the Long House Valley Anasazi model, the CCSM3 climate change model, and the Epstein smallpox model. The papers collected here concentrate on issues of modeling and simulation, experimentation, and materiality. Tarja Knuuttilla and Andrea Loettger’s “Modeling and Experimenting: The Combinatorial Modeling Strategy of Synthetic Biology” explores a triangulation strategy between model organisms, synthetic experimentation, and mathematical models and associated simulations. The authors argue that each of these fulfills a specific epistemic role, with an analysis of cases that adds significant nuance to older debates regarding simulation, experimentation, and materiality. The central modeling goal of simplification is the focus of Gerhard Konig’s “Simulation and the Problem of Simplification: Between Scylla and Charybdis?” Konig’s piece is particularly valuable in that it is not content to emphasize the dangers Philos. Technol. (2013) 26:73–74 DOI 10.1007/s13347-012-0080-9

History and Epistemology of Models: Meteorology (1946-1963) as a Case Study

This paper focuses on scientific practices and problems of modeling in the case of meteorology. This domain is especially interesting because of its crucial influence on the conception of mathematical models and its links with numerical instability, computers, and the science of chaos and dynamic systems. All of these questions involve for their solution a considerable mathematical apparatus which was developed by several mathematicians. An early example is von Neumann’s and Charney’s Princeton Meteorological Project in the period 1946–53 which ended with daily numerical prediction in less than 2 hours. After this stage, the questions of long-range forecasting and general circulation of the atmosphere became of greater importance. The late 1950s saw the emergence of an alternative: were atmospheric models used mainly for prediction or understanding? This controversial debate in particular occurred during an important colloquium in Tokyo in 1960 which gathered together J. Charney, E. Lorenz, A. Eliassen, and B. Saltzman, among others, and witnessed discussions on statistical methods for predictions and/or maximum simplification of dynamic equations. This phase ended in 1963 with Lorenz’s seminal paper on “Deterministic non periodic flows.”