Michael Weisberg – författare

In the 1950s, John Reber convinced many Californians that the best way to solve the state's water shortage problem was to dam up the San Francisco Bay. Against massive political pressure, Reber's opponents persuaded lawmakers that doing so would lead to disaster. They did this not by empirical measurement alone, but also through the construction of a model. Simulation and Similarity explains why this was a good strategy while simultaneously providing an account of modeling and idealization in modern scientific practice. Michael Weisberg focuses on concrete, mathematical, and computational models in his consideration of the nature of models, the practice of modeling, and nature of the relationship between models and real-world phenomena. In addition to a careful analysis of physical, computational, and mathematical models, Simulation and Similarity offers a novel account of the model/world relationship. Breaking with the dominant tradition, which favors the analysis of this relation through logical notions such as isomorphism, Weisberg instead presents a similarity-based account called weighted feature matching. This account is developed with an eye to understanding how modeling is actually practiced. Consequently, it takes into account the ways in which scientists' theoretical goals shape both the applications and the analyses of their models.

Descartes once argued that, with sufficient effort and skill, a single scientist could uncover fundamental truths about our world. Contemporary science proves the limits of this claim. From synthesizing the human genome to predicting the effects of climate change, some current scientific research requires the collaboration of hundreds (if not thousands) of scientists with various specializations. Additionally, the majority of published scientific research is now co-authored, including more than 80% of articles in the natural sciences, meaning small collaborative teams have become the norm in science. This volume is the first to address critical philosophical questions regarding how collective scientific research could be organized differently and how it should be organized. For example, should scientists be required to share knowledge with competing research teams? How can universities and grant-giving institutions promote successful collaborations? When hundreds of researchers contribute to a discovery, how should credit be assigned - and can minorities expect a fair share? When collaborative work contains significant errors or fraudulent data, who deserves blame? In this collection of essays, leading philosophers of science address these critical questions, among others. Their work extends current philosophical research on the social structure of science and contributes to the growing, interdisciplinary field of social epistemology. The volume's strength lies in the diversity of its authors' methodologies. Employing detailed case studies of scientific practice, mathematical models of scientific communities, and rigorous conceptual analysis, contributors to this volume study scientific groups of all kinds, including small labs, peer-review boards, and large international collaborations like those in climate science and particle physics.

Nobel laureate Roald Hoffmann's contributions to chemistry are well known. Less well known, however, is that over a career that spans nearly fifty years, Hoffmann has thought and written extensively about a wide variety of other topics, such as chemistry's relationship to philosophy, literature, and the arts, including the nature of chemical reasoning, the role of symbolism and writing in science, and the relationship between art and craft and science. In Roald Hoffmann on the Philosophy, Art, and Science of Chemistry, Jeffrey Kovac and Michael Weisberg bring together twenty-eight of Hoffmann's most important essays. Gathered here are Hoffmann's most philosophically significant and interesting essays and lectures, many of which are not widely accessible. In essays such as "Why Buy That Theory," "Nearly Circular Reasoning," "How Should Chemists Think," "The Metaphor, Unchained," "Art in Science," and "Molecular Beauty," we find the mature reflections of one of America's leading scientists. Organized under the general headings of Chemical Reasoning and Explanation, Writing and Communicating, Art and Science, Education, and Ethics, these stimulating essays provide invaluable insight into the teaching and practice of science.

In the 1950s, John Reber convinced many Californians that the best way to solve the state's water shortage problem was to dam up the San Francisco Bay. Against massive political pressure, Reber's opponents persuaded lawmakers that doing so would lead to disaster. They did this not by empirical measurement alone, but also through the construction of a model. Simulation and Similarity explains why this was a good strategy while simultaneously providing an account of modeling and idealization in modern scientific practice. Michael Weisberg focuses on concrete, mathematical, and computational models in his consideration of the nature of models, the practice of modeling, and nature of the relationship between models and real-world phenomena. In addition to a careful analysis of physical, computational, and mathematical models, Simulation and Similarity offers a novel account of the model/world relationship. Breaking with the dominant tradition, which favors the analysis of this relation through logical notions such as isomorphism, Weisberg instead presents a similarity-based account called weighted feature matching. This account is developed with an eye to understanding how modeling is actually practiced. Consequently, it takes into account the ways in which scientists' theoretical goals shape both the applications and the analyses of their models.