In this book, which remained unfinished at his death, Husserl attempts to forge a union between phenomenology and existentialism.

What do biologists want? If, unlike their counterparts in physics, biologists are generally wary of a grand, overarching theory, at what kinds of explanation do biologists aim? A history of the diverse and changing nature of biological explanation in a particularly charged field, "Making Sense of Life" draws our attention to the temporal, disciplinary, and cultural components of what biologists mean, and what they understand, when they propose to explain life.

Engages with the impact of modern technology on experimental physicists. This study reveals how the increasing scale and complexity of apparatus has distanced physicists from the very science which drew them into experimenting, and has fragmented microphysics into different technical traditions.

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)

The collaborative ‹Big Science’ approach prevalent in physics during the mid- and late-20th century is becoming more common in the life sciences. Often computationally mediated, these collaborations challenge researchers’ trust practices. Focusing on the visualisations that are often at the heart of this form of scientific practice, the paper proposes that the aesthetic aspects of these visualisations are themselves a way of securing trust. Kant’s account of aesthetic judgements in the Third Critique is drawn upon in order to show that (...) the image-building capability of imagination, and the sensus communis, both of which are integral parts of aesthetic experience, play an important role in building and sustaining community in these forms of science. Kant’s theory shows that the aesthetic appeal of scientific visualisations is not isolated from two other dimensions of the visualisations: the cognitive-epistemic, aesthetic-stylistic and interpersonal dimensions, and that in virtue of these inter-relationships, visualisations contribute to building up the intersubjectively shared framework of agreement which is basic for trust. (shrink)

After showing how Deborah Mayo’s error-statistical philosophy of science might be applied to address important questions about the evidential status of computer simulation results, I argue that an error-statistical perspective offers an interesting new way of thinking about computer simulation models and has the potential to significantly improve the practice of simulation model evaluation. Though intended primarily as a contribution to the epistemology of simulation, the analysis also serves to fill in details of Mayo’s epistemology of experiment.

The ArgumentIn its reconstruction of scientific practice, philosophy of science has traditionally placed scientific theories in a central role, and has reduced the problem of mediating between theories and the world to formal considerations. Many applications of scientific theories, however, involve complex mathematical models whose constitutive equations are analytically unsolvable. The study of these applications often consists in developing representations of the underlying physics on a computer, and using the techniques of computer simulation in order to learn about the behavior (...) of these systems. In many instances, these computer simulations are not simple number-crunching techniques. They involve a complex chain of inferences that serve to transform theoretical structures into specific concrete knowledge of physical systems. In this paper I argue that this process of transformation has its own epistemology. I also argue that this kind of epistemology is unfamiliar to most philosophy of science, which has traditionally concerned itself with the justification of theories, not with their application. Finally, I urge that the nature of this epistemology suggests that the end results of some simulations do not bear a simple, straightforward relation to the theories from which they stem. (shrink)