Paul Thompson, John Beatty, and Elisabeth Lloyd argue that attempts to resolve certain conceptual issues within evolutionary biology have failed because of a general adherence to the received view of scientific theories. They maintain that such issues can be clarified and resolved when one adopts a semantic approach to theories. In this paper, I argue that such conceptual issues are just as problematic on a semantic approach. Such issues arise from the complexity involved in providing formal accounts of theoretical laws (...) and scientific explanations. That complexity is due to empirical and pragmatic considerations, not one's adherence to a particular formal approach to theories. This analysis raises a broader question. How can any formal account properly represent the complex nature of empirical phenomena? (shrink)

In this collection of essays, Bromberger explores the centrality of questions and predicaments they create in scientific research. He discusses the nature of explanation, theory, and the foundations of linguistics.

The theory of concepts advanced in the dissertation aims at accounting for a) how a concept makes successful practice possible, and b) how a scientific concept can be subject to rational change in the course of history. Traditional accounts in the philosophy of science have usually studied concepts in terms only of their reference; their concern is to establish a stability of reference in order to address the incommensurability problem. My discussion, in contrast, suggests that each scientific concept consists of (...) three components of content: 1) reference, 2) inferential role, and 3) the epistemic goal pursued with the concept's use. I argue that in the course of history a concept can change in any of these three components, and that change in one component—including change of reference—can be accounted for as being rational relative to other components, in particular a concept's epistemic goal.This semantic framework is applied to two cases from the history of biology: the homology concept as used in 19th and 20th century biology, and the gene concept as used in different parts of the 20th century. The homology case study argues that the advent of Darwinian evolutionary theory, despite introducing a new definition of homology, did not bring about a new homology concept (distinct from the pre-Darwinian concept) in the 19th century. Nowadays, however, distinct homology concepts are used in systematics/evolutionary biology, in evolutionary developmental biology, and in molecular biology. The emergence of these different homology concepts is explained as occurring in a rational fashion. The gene case study argues that conceptual progress occurred with the transition from the classical to the molecular gene concept, despite a change in reference. In the last two decades, change occurred internal to the molecular gene concept, so that nowadays this concept's usage and reference varies from context to context. I argue that this situation emerged rationally and that the current variation in usage and reference is conducive to biological practice.The dissertation uses ideas and methodological tools from the philosophy of mind and language, the philosophy of science, the history of science, and the psychology of concepts. (shrink)

Part of the scientific enterprise is to measure the material world and to explain its dynamics by means of models. However, not only is measurability of the world limited, analyzability of models is so, too. Most often, computer simulations offer a way out of this epistemic bottleneck. They instantiate the model and may help to analyze it. In relation to the material world a simulation may be regarded as a kind of a “non-material scale model”. Like any other scale model, (...) it does not per se give any scientific explanation but is first in itself an object of scientific enquiry, a world. Since this world is numerical, it is a priori measurable. Its role in scientific explanation will be discussed. (shrink)

Scientific models are important, if not the sole, units of science. This thesis addresses the following question: in virtue of what do scientific models represent their target systems? In Part i I motivate the question, and lay out some important desiderata that any successful answer must meet. This provides a novel conceptual framework in which to think about the question of scientific representation. I then argue against Callender and Cohen’s attempt to diffuse the question. In Part ii I investigate the (...) ideas that scientific models are ‘similar’, or structurally morphic, to their target systems. I argue that these approaches are misguided, and that at best these relationships concern the accuracy of a pre-existing representational relationship. I also pay particular attention to the sense in which target systems can be appropriately taken to exhibit a ‘structure’, and van Fraassen’s recent argument concerning the pragmatic equivalence between representing phenomena and data. My next target is the idea that models should not be seen as objects in their own right, but rather what look like descriptions of them are actually direct descriptions of target systems, albeit not ones that should be understood literally. I argue that these approaches fail to do justice to the practice of scientific modelling. Finally I turn to the idea that how models represent is grounded, in some sense, in their inferential capacity. I compare this approach to anti-representationalism in the philosophy of language and argue that analogous issues arise in the context of scientific representation. Part iii contains my positive proposal. I provide an account of scientific representation based on Goodman and Elgin’s notion of representation-as. The result is a highly conventional account which is the appropriate level of generality to capture all of its instances, whilst remaining informative about the notion. I illustrate it with reference to the Phillips-Newlyn machine, models of proteins, and the Lotka-Volterra model of predator-prey systems. These examples demonstrate how the account must be understood, and how it sheds light on our understanding of how models are used. I finally demonstrate how the account meets the desiderata laid out at the beginning of the thesis, and outline its implications for further questions from the philosophy of science; not limited to issues surrounding the applicability of mathematics, idealisation, and what it takes for a model to be ‘true’. (shrink)

This paper is a conceptual analysis of the theory debate in psychology, as carried out by cognitivists and radical behaviorists. The debate has focused on the necessity of theories in psychology. However, the logically primary issue is the nature of theories, or what theories are. This claim stems from the fact that cognitivists and radical behaviorists adopt disparate accounts of the nature of theories. The cognitivists' account is closely akin to the received view from logical positivism, where theories are collections (...) of statements and theoretical terms are restricted to designate unobservable entities. Radical behaviorists also conceive theories as collections of statements, but restrict theoretical terms in psychology to designate observable entities. If each side approaches the necessity issue with its preferred account, both agree that theories are necessary in psychology. Hence, there is no disagreement over the necessity of theories in psychology per se, only over the nature of theories. The received view, however, has been shown to suffer from irreparable difficulties that have led to its total rejection in post-positivistic philosophy of science. Alternative accounts, like the structuralist and semantic views, do not raise the issue of whether theories are necessary in psychology. (shrink)

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. (shrink)

This thesis inquires what it means to interpret non-relativistic quantum mechanics (QM), and the philosophical limits of this interpretation. In pursuit of a scientific-realist stance, a metametaphysical method is expanded and applied to evaluate rival interpretations of QM, based on the conceptual distinction between ontology and metaphysics, for objective theory choice in metaphysical discussions relating to QM. Three cases are examined, in which this metametaphysical method succeeds in indicating what are the wrong alternatives to interpret QM in metaphysical terms. The (...) first two cases failed in doing so due to different kinds of underdetermination. In the third case, unlike underdetermination, where there are many choices to be made, a “null-determination” is proposed where there may be no metaphysical choices in the available metaphysical literature. Considering what has been discussed, an agnostic philosophic position is adopted concerning the possibility of interpreting QM from a scientific-realistic point of view. (shrink)