This paper is an interpretation and defense of Richard Levins’ “The Strategy of Model Building in Population Biology,” which has been extremely influential among biologists since its publication 40 years ago. In this article, Levins confronted some of the deepest philosophical issues surrounding modeling and theory construction. By way of interpretation, I discuss each of Levins’ major philosophical themes: the problem of complexity, the brute-force approach, the existence and consequence of tradeoffs, and robustness analysis. I argue that Levins’ article is (...) concerned, at its core, with justifying the use of multiple, idealized models in population biology. (shrink)

The question of the relationship of the making of value judgments in a typically ethical sense to the methods and procedures of science has been discussed in the literature at least to that point which e. e. cummings somewhere refers to as “The Mystical Moment of Dullness.” Nevertheless, albeit with some trepidation, I feel that something more may fruitfully be said on the subject.

Although the recent emphasis on models in philosophy of science has been an important development, the consequence has been a shift away from more traditional notions of theory. Because the semantic view defines theories as families of models and because much of the literature on “scientific” modeling has emphasized various degrees of independence from theory, little attention has been paid to the role that theory has in articulating scientific knowledge. This paper is the beginning of what I hope will be (...) a redress of the imbalance. I begin with a discussion of some of the difficulties faced by various formulations of the semantic view not only with respect to their account of models but also with their definition of a theory. From there I go on to articulate reasons why a notion of theory is necessary for capturing the structure of scientific knowledge and how one might go about formulating such a notion in terms of different levels of representation and explanation. The context for my discussion is the BCS account of superconductivity, a `theory' that was, and still is, sometimes referred to as a `model'. BCS provides a nice focus for the discussion because it illuminates various features of the theory/model relationship that seem to require a robust notion of theory that is not easily captured by the semantic account. (shrink)

Critics of the erotetic model of explanation question its ability to discriminate significant from spurious explanations. One response to these criticisms has been to impose contextual restrictions on a case-by-case basis. In this article, the author argues that these approaches have overestimated the role of interests at the expense of other contextual aspects characteristic of social-scientific explanation. For this reason, he shows how procedures of measuring occupational status and social mobility affected different aspects of one explanation that Peter Blau and (...) Otis Dudley Duncan offered in their sociological classic, The American Occupational Structure. He uses the findings from this case study to meet objections to the erotetic model. Key Words: explanation • social science • erotetic • why-question • context. (shrink)

Although epistemic values have become widely accepted as part of scientific reasoning, non-epistemic values have been largely relegated to the "external" parts of science (the selection of hypotheses, restrictions on methodologies, and the use of scientific technologies). I argue that because of inductive risk, or the risk of error, non-epistemic values are required in science wherever non-epistemic consequences of error should be considered. I use examples from dioxin studies to illustrate how non-epistemic consequences of error can and should be considered (...) in the internal stages of science: choice of methodology, characterization of data, and interpretation of results. (shrink)

The Embodied Mind provides a unique, sophisticated treatment of the spontaneous and reflective dimension of human experience.

In several accounts of what models are and how they function a specific view dominates. This view contains the following characteristics. First, there is a clear-cut distinction between theories, models and data and secondly, empirical assessment takes place after the model is built. This view in which discovery and justification are disconnected is not in accordance with several practices of mathematical business-cycle model building. What these practices show is that models have to meet implicit criteria of adequacy, such as satisfying (...) theoretical, mathematical and statistical requirements, and be useful for policy. In order to be adequate, models have to integrate enough items to satisfy such criteria. These items include besides theoretical notions, policy views, mathematisations of the cycle and metaphors also empirical data and facts. So, the main thesis of this chapter is that the context of discovery is the successful integration of those items that satisfy the criteria of adequacy. Because certain items are empirical data and facts, justification can be built-in. (shrink)

The concept of the receptive field, first articulated by Hartline, is central to visual neuroscience. The receptive field of a neuron encompasses the spatial and temporal properties of stimuli that activate the neuron, and, as Hubel and Wiesel conceived of it, a neuron’s receptive field is static. This makes it possible to build models of neural circuits and to build up more complex receptive fields out of simpler ones. Recent work in visual neurophysiology is providing evidence that the classical receptive (...) field is an inaccurate picture. The receptive field seems to be a dynamic feature of the neuron. In particular, the receptive field of neurons in V1 seems to be dependent on the properties of the stimulus. In this paper, we review the history of the concept of the receptive field and the problematic data. We then consider a number of possible theoretical responses to these data. (shrink)

Although a strict dichotomy between facts and values is no longer accepted, less attention has been paid to the roles values should play in our acceptance of factual statements, or scientific descriptive claims. This paper argues that values, whether cognitive or ethical, should never preclude or direct belief on their own. Our wanting something to be true will not make it so. Instead, values should only be used to consider whether the available evidence provides sufficient warrant for a claim. This (...) argument is made for all relevant values, including cognitive, ethical, and social values. The rational integrity of science depends not on excluding some values and including others in the reasoning process, but of constraining all values to their proper role in belief acceptance. (shrink)

We call for a new philosophical conception of models in physics. Some standard conceptions take models to be useful approximations to theorems, that are the chief means to test theories. Hence the heuristics of model building is dictated by the requirements and practice of theory-testing. In this paper we argue that a theory-driven view of models can not account for common procedures used by scientists to model phenomena. We illustrate this thesis with a case study: the construction of one of (...) the first comprehensive model of superconductivity by London brothers in 1934. Instead of theory-driven view of models, we suggest a phenomenologically-driven one. (shrink)