Based on da Costa's and French's notions of partial structures and pragmatic truth, this paper examines two possible characterizations of the concept of empirical adequacy, one depending on the notion of partial isomorphism, the other on the hierarchy of partial models of phenomena, and both compatible with an empiricist view. These formulations can then be employed to illuminate certain aspects of scientific practice.An empirical theory must single out a specific part of the world, establish reference to that part, and say—by (...) way of contingent, substantial claim about the world—that its models fit that. Now, how exactly can this be done? Bas C. van Fraassen. (shrink)

List of Illustrations Introduction 1 The Didactic and the Elegant: Some Thoughts on Scientific and Technological Illustrations in the Middle Ages and Renaissance 3 2 Temples of the Body and Temples of the Cosmos: Vision and Visualization in the Vesalian and Copernican Revolutions 40 3 Descartes’s Scientific Illustrations and ’la grande mecanique de la nature’ 86 4 Illustrating Chemistry 135 5 Representations of the Natural System in the Nineteenth Century 164 6 Visual Representation in Archaeology: Depicting the Missing-Link in Human (...) Origins 184 7 Towards an Epistemology of Scientific Illustration 215 8 Illustration and Inference 250 9 Visual Models and Scientific Judgment 269 10 Are Pictures Really Necessary? The Case of Sewall Wright’s ’Adaptive Landscapes’ 303 Bibliography 339 Notes on Contributors 373 Index 377. (shrink)

In the traditional conception of science one assumes that science produces results which are certain and precise. It is argued that this picture is flawed and needs to be replaced with a view where uncertainty and imprecision are an integral part of the scientific enterprise. Uncertainty is still poorly understood by many practising scientists. However, several developments in science indicate that some epistemological uncertainty, e.g. due to processes of abstraction and idealization, will always follow advances in scientific knowledge. There are (...) also other developments that indicate some principal ontological uncertainties, i.e. uncertainties that are due to how the world is. Complexity is one such example. Remarks on post-normal science are thus included. This paper argues, therefore, that scientific uncertainty is a multi-dimensional concept, and that it is unavoidable because it is often the result as much as the cause of new knowledge. (shrink)

This essay attempts to provide additional motivation for the data/phenomena framework advocated in Bogen and Woodward, “Saving the Phenomena”.

In a recent paper, Suárez and Cartwright return to the example of London and London's construction of a model for superconductivity and raise a number of concerns against the account of this construction presented in French and Ladyman and elsewhere. In this discussion note, we examine the challenge they raised and offer our responses.

In this paper a constructive empiricist account of scientific change is put forward. Based on da Costa's and French's partial structures approach, two notions of empirical adequacy are initially advanced (with particular emphasis on the introduction of degrees of empirical adequacy). Using these notions, it is shown how both the informativeness and the empirical adequacy requirements of an empiricist theory of scientific change can then be met. Finally, some philosophical consequences with regard to the role of structures in this context (...) are drawn.Now, we daily see what science is doing for us. This could not be unless it taught us something about reality; the aim of science is not things themselves, as the dogmatists in their simplicity imagine, but the relations between things; outside those relations there is no reality knowable. (shrink)

In “The Toolbox of Science” (1995) together with Towfic Shomar we advocated a form of instrumentalism about scientific theories. We separately developed this view further in a number of subsequent works. Steven French, James Ladyman, Otavio Bueno and Newton Da Costa (FLBD) have since written at least eight papers and a book criticising our work. Here we defend ourselves. First we explain what we mean in denying that models derive from theory – and why their failure to do so should (...) be lamented. Second we defend our use of the London model of superconductivity as an example. Third we point out both advantages and weaknesses of FLBD’s techniques in comparison to traditional Anglophone versions of the semantic conception. Fourth we show that FLBD’s version of the semantic conception has not been applied to our case study. We conclude by raising doubts about FLBD’s overall project. (shrink)

Some twenty years ago, Bogen and Woodward challenged one of the fundamental assumptions of the received view, namely the theory-observation dichotomy and argued for the introduction of the further category of scientific phenomena. The latter, Bogen and Woodward stressed, are usually unobservable and inferred from what is indeed observable, namely scientific data. Crucially, Bogen and Woodward claimed that theories predict and explain phenomena, but not data. But then, of course, the thesis of theory-ladenness, which has it that our observations are (...) influenced by the theories we hold, cannot apply. On the basis of two case studies, I want to show that this consequence of Bogen and Woodward’s account is rather unrealistic. More importantly, I also object against Bogen and Woodward’s view that the reliability of data, which constitutes the precondition for data-to-phenomena inferences, can be secured without the theory one seeks to test. The case studies I revisit have figured heavily in the publications of Bogen and Woodward and others: the discovery of weak neutral currents and the discovery of the zebra pattern of magnetic anomalies. I show that, in the latter case, data can be ignored if they appear to be irrelevant from a particular theoretical perspective (TLI) and that, in the former case, the tested theory can be critical for the assessment of the reliability of the data (TLA). I argue that both TLI and TLA are much stronger senses of theory-ladenness than the classical thesis and that neither TLI nor TLA can be accommodated within Bogen and Woodward’s account. (shrink)

R. Laudan and L. Laudan (1989) have put forth a new model intended to solve the problem of disagreement, the problem of consensus, and the problem of innovation in science. In support of this model they cite the history of the acceptance of continental drift, or plate tectonics. In this discussion, I claim that this episode does not constitute an instance of their model. The historical evidence does not support this model. Indeed, closer examination seems to weaken it. I also (...) sketch an alternative model. (shrink)

In this paper I inquire into Bogen and Woodward’s data/phenomena distinction, which in a similar way to Cartwright’s construal of the model of superconductivity —although in a different domain—argues for a ‘bottom-up’ construction of phenomena from data without the involvement of theory. I criticise Bogen and Woodward’s account by analysing their melting point of lead example in depth, which is usually cited in the literature to illustrate the data/phenomenon distinction. Yet, the main focus of this paper lies on Matthias Kaiser’s (...) case study of the plate tectonic revolution, the most extensive case study that has been put forth to support the bottom-up construction of phenomena. On the basis of new historical evidence, which has been overlooked not only by Kaiser but also by the entire historical literature on the plate tectonic revolution, I demonstrate that phenomena are not constructed from the bottom-up but rather, admittedly counter-intuitively, from the top-down.Keywords: Data; Phenomena; Bottom-up; Theory-ladenness; Plate tectonic revolution. (shrink)

We argue for a foundational epistemic claim and a hypothesis about the production and uses of mathematical epidemiological models, exploring the consequences for our political and socio-economic lives. First, in order to make the best use of scientific models, we need to understand why models are not truly representational of our world, but are already pitched towards various uses. Second, we need to understand the implicit power relations in numbers and models in public policy, and, thus, the implications for good (...) governance if numbers and models are used as the exclusive drivers of decision making. (shrink)