Online research in philosophy

Theoretical models are an important tool for many aspects of scientific activity. They are used, i.a., to structure data, to apply theories or even to construct new theories. But what exactly is a model? It turns out that there is no proper definition of the term "model" that covers all these aspects. Thus, I restrict myself here to evaluate the function of models in the research process while using "model" in the loose way physicists do. To this end, I distinguish four kinds of models. These are (1) models as special theories, (2) models as a substitute for a theory, (3) toy models and (4) developmental models. I argue that models of the types (3) and (4) are considerably useful in the process of theory construction. This will be demonstrated in an extended case-study from High-Energy Physics.

I investigate how theoretical assumptions, pertinent to different perspectives and operative during the modeling process, are central in determining how nature is actually taken to be. I explore two different models by Michael Turelli and Steve Frank of the evolution of parasite-mediated cytoplasmic incompatility, guided, respectively, by Fisherian and Wrightian perspectives. Since the two models can be shown to be commensurable both with respect to mathematics and data, I argue that the differences between them in the (1) mathematical presentation of the models, (2) explanations, and (3) objectified ontologies stem neither from differences in mathematical method nor the employed data, but from differences in the theoretical assumptions, especially regarding ontology, already present in the respective perspectives. I use my "set up, mathematically manipulate, explain, and objectify" (SMEO) account of the modeling process to track the model-mediated imposition of theoretical assumptions. I conclude with a discussion of the general implications of my analysis of these models for the controversy between Fisherian and Wrightian perspectives.

Four distinct models of the functional contribution of mirror neurons to social cognition can be distinguished: direct matching, inverse modeling, response modeling, and predictive coding. Each entails a different way in which an agent's own capacities for action and affective experience contribute to understanding and/or predicting others' actions and affective experience. In this paper, the four models and their theoretical frameworks are elucidated, empirical data and theoretical arguments bearing upon each are reviewed, and falsifiable predictions that could help to distinguish empirically among the models are proposed.

The paper examines philosophical issues that arise in contexts where one has many different models for treating the same system. I show why in some cases this appears relatively unproblematic (models of turbulence) while others represent genuine difficulties when attempting to interpret the information that models provide (nuclear models). What the examples show is that while complementary models needn’t be a hindrance to knowledge acquisition, the kind of inconsistency present in nuclear cases is, since it is indicative of a lack of genuine theoretical understanding. It is important to note that the differences in modeling do not result directly from the status of our knowledge of turbulent flows as opposed to nuclear dynamics—both face fundamental theoretical problems in the construction and application of models. However, as we shall, the ‘problem context(s)’ in which the modeling takes plays a decisive role in evaluating the epistemic merit of the models themselves. Moreover, the theoretical difficulties that give rise to inconsistent as opposed to complementary models (in the cases I discuss) impose epistemic and methodological burdens that cannot be overcome by invoking philosophical strategies like perspectivism, paraconsistency or partial structures.

This paper aims 1) to introduce the notion of theoretical story as a resource and source of constraint for the construction and assessment of models of phenomena; 2) to show the relevance of this notion for a better understanding of the role and nature of values in scientific activity. The reflection on the role of values and value judgments in scientific activity should be attentive, I will argue, to the distinction between models and the theoretical story that guides and constrains their construction. The aim of scientific activity is to develop understanding of phenomena, and something that serves this aim and contributes to the development of understanding has a cognitive value. Cognitive values are the features that something that plays a role in scientific activity should have so that it can serve its aim. I will focus my attention on the features of the theoretical story and of the models.

Recent controversy over the existence of biological laws raises questions about the cognitive aims of theoretical modeling in that science. If there are no laws for successful theoretical models to approximate, then what is it that successful theories do? One response is to regard theoretical models as tools. But this instrumental reading cannot accommodate the explanatory role that theories are supposed to play. Yet accommodating the explanatory function, as articulated by Brandon and Sober for example, seems to involve us once again in a reliance on laws. The paper concludes that we must rethink both the nature of laws and theoretical explanation in biology.

What Daniel Hausman has called 'the simple criticism of economic theory' affirms that neoclassical microeconomic models include false statements, and therefore economists cannot rationally accept such models. Hausman considers, but rejects, the modal view of economic models as a defense of neoclassical theory against the simple criticism. I attempt to show that, on the contrary, the modal view can be used to defend neoclassical micro theory. The modal view distinguishes theoretical from applied economic models. Theoretical models afford true descriptions of hypothetical economic agents, whereas applied models contain true or false statements about some real world situation. Relying on the modal view, I argue that the simple criticism is not well-founded, whether it concerns theoretical or applied models.

In this paper I discuss how, given the complexity of biological systems, reliance on theoretical models in the development and testing of biological theories leads to an uncomfortable form of anti-realism. I locate the source of this discomfort in the uniqueness and hence diversity of biological phenomena, in contrast with the simplicity and uniformity of the subject matter of physics. I have argued elsewhere that the use of theoretical models creates an unresolvable tension between the explanatory strength and predictive power of hypotheses, and I review this argument again here. My discussion parallels that of Nancy Cartwright, who claims that the use of ceteris paribus laws in physics creates an antagonism between truth and explanation that requires theoretical models to figure centrally in scientific explanation, thereby precluding realism. I argue instead that in biology it is the use of theoretical models that creates this conflict, and conclude that adequate biological explanation cannot rely on the modeling approach alone. Finally, I claim that if we accept the semantic view of theories, which makes theoretical models an integral part of our conception of theories, we must accept anti-realism as well.

Using Sneed''s metatheory an attempt is made to reconstruct Hodgkin and Huxley''s theory of excitation of cell membranes. The structure of this theory is uncovered by defining set-theoretical predicates for the partial potential models, potential models, and models of the theory. The function of permeability is said to be the only theoretical function with respect to this theory. The main underlying assumptions of the theory are briefly outlined.

Investigating random homicides involves constructing models of an odd sort. While the differences between these models and scientific models are radical, calling them models is justified both by functional and structural similarities. Serial homicide investigations illustrate the marked difference between theoretical models in science and the models applied in these criminal investigations. This is further illustrated by considering Glymourian bootstrapping in attempts to solve such homicides. The solutions that result differ radically from explanations in science that are confirmed or disconfirmed by occurrences. Unlike the scientist, the flatfoot gumshoe is also barefoot: he is bereft of a general, determinative theoretical frame. This result shows that criminal investigations do not apply science in the Galilean sense.