Der Artikel führt den Begriff der epistemischen Konkurrenz ein. Im Gegensatz zu „wissenschaftliche Kontroverse“ beschreibt er eine Situation, in der sich zwei Forschungsfelder gegenseitig als mit demselben Bereich von Phänomen befasst wahrnehmen, wobei ihre methodischen Ansätze und theoretischen Erklärungen jedoch so unterschiedlich sind, dass ein offener Konflikt über die Wahrheit oder Falschheit bestimmter Aussagen oder die Genauigkeit in der Anwendung einer Methode nicht stattfindet. Nichtsdestotrotz streben beide Parteien danach, die maßgebliche Erklärung der entsprechenden Phänomene anzubieten. Indem die erweiterte Gemeinschaft der (...) Forschenden oder die Öffentlichkeit einen Ansatz als maßgeblich anerkennt, handeln sie als eine dritte, gewissermaßen neutrale Partei, die einen Preis vergibt, um den die anderen Parteien konkurrieren. Der Artikel beschreibt das Verhältnis von Genetik und Entwicklungsbiologie um 1900 als epistemische Konkurrenz. Diese Forschungsfelder geben unterschiedliche Erklärungen für die Phänomene der organischen Reproduktion. Die Erklärungen unterscheiden sich bezüglich der Formbegriffe und entsprechend hinsichtlich der Begriffe der Vererbung von Aspekten der Form eines Organismus. Zudem basieren die Erklärungen der beiden Felder auf unterschiedlichen Arten kausalen Schließens, die in unterschiedliche experimentelle Ansätze eingebettet sind. Diese Unterschiede können als Instanzen eines allgemeineren Unterschieds zwischen der Tradition der Naturgeschichte, die sich mit Unterschieden zwischen Organismen auseinandersetzt, und der Tradition der Anatomie, die sich mit den Teilen der Organismen beschäftigt, angesehen werden. Dieses Bild der Genetik und Entwicklungsbiologie als Zweige unterschiedlicher fest verankerter Traditionen widerspricht dem Narrativ der Trennung des Begriffs der Vererbung von dem der Entwicklung im Zuge einer Trennung der Disziplinen der Genetik und der Embryologie, das in der Historiographie der Biologie nach wie vor weit verbreitet ist. (shrink)

Understanding the operation and evolution of gene regulation networks is critical to understanding ontogeny and evolution. According to Stuart Kauffman's view, (1) each cell type cycles through its own repeated pattern of gene expression, (2) the order of ontogeny is dependent on these cycles being short, and (3) evolution is possible because these cycles mutate gradually. This view of gene regulation reflects Kauffman's view that ontogeny is fundamentally the process of cells repeating cycles of activity. I criticize Kauffman's view of (...) gene regulation networks and offer the connectionist theory of gene regulation as an alternative. On this view, the generic order of gene regulation mechanisms is due to the qualitatively consistent way that one gene product influences the expression of another. This allows networks to be stable and evolve to regulate accurately, allowing cells to react appropriately to their microenvironments, due to design by natural selection. 1. Introduction2. Kauffman's Model of Gene Regulation3. Explaining the Order of Kauffman's K = 2 Networks4. The Importance and Relevance of Kauffman's Explanations of the Order of Gene Regulation5. Additional Orderly Facts of Transcription6. The Order of Network Accuracy7. The Accuracy of Connectionist Networks8. The Evolvability of Gene Regulation Networks9. Laws of Structure. (shrink)

Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

First, a comment on a pessimistic note: Salmon says we can't be sure there is any such thing as inductive inference: in demanding that some explanations have the form of correct inductive inferences, “we may be laying down a requirement which cannot be fulfilled.” To doubt that we can fulfill that requirement is to doubt that we can formalize inductive logic. It may be true, but why begin the fight by throwing in the sponge? It is also true that there (...) are difficulties involved in formalizing acceptance rules for inductive conclusions, but these difficulties may be overcome. It is false to claim that we ‘cannot claim to know exactly’ what these acceptance rules are. Only two years ago I did just that. It was true that my claim was shown to be erroneous a year later, but that fate can befall almost any worthwhile claim. (shrink)

Much is being written these days about integration, its desirability and even its necessity when complex research problems are to be addressed. Seldom, however, do we hear much about the failure of such efforts. Because integration is an ongoing activity rather than a final achievement, and because today’s literature about integration consists mostly of manifesto statements rather than precise descriptions, an examination of unsuccessful integration could be illuminating to understand better how it works. This paper will examine the case of (...) prokaryote phylogeny and its apparent failure to achieve integration within broader tree-of-life accounts of evolutionary history. Despite the fact that integrated databases exist of molecules pertinent to the phylogenetic reconstruction of all lineages of life, and even though the same methods can be used to construct phylogenies wherever the organisms fall on the tree of life, prokaryote phylogeny remains at best only partly integrated within tree-of-life efforts. I will examine why integration does not occur, compare it with integrative practices in animal and other eukaryote phylogeny, and reflect on whether there might be different expectations of what integration should achieve. Finally, I will draw some general conclusions about integration and its function as a ‘meta-heuristic’ in the normative commitments guiding scientific practice. (shrink)

Objectivity has a history, and it is full of surprises. In Objectivity, Lorraine Daston and Peter Galison chart the emergence of objectivity in the mid-nineteenth-century sciences--and show how the concept differs from its alternatives, truth-to-nature and trained judgment. This is a story of lofty epistemic ideals fused with workaday practices in the making of scientific images. From the eighteenth through the early twenty-first centuries, the images that reveal the deepest commitments of the empirical sciences--from anatomy to crystallography--are those featured in (...) scientific atlases, the compendia that teach practitioners what is worth looking at and how to look at it. Galison and Daston use atlas images to uncover a hidden history of scientific objectivity and its rivals. Whether an atlas maker idealizes an image to capture the essentials in the name of truth-to-nature or refuses to erase even the most incidental detail in the name of objectivity or highlights patterns in the name of trained judgment is a decision enforced by an ethos as well as by an epistemology. As Daston and Galison argue, atlases shape the subjects as well as the objects of science. To pursue objectivity--or truth-to-nature or trained judgment--is simultaneously to cultivate a distinctive scientific self wherein knowing and knower converge. Moreover, the very point at which they visibly converge is in the very act of seeing not as a separate individual but as a member of a particular scientific community. Embedded in the atlas image, therefore, are the traces of consequential choices about knowledge, persona, and collective sight. Objectivity is a book addressed to anyone interested in the elusive and crucial notion of objectivity-- and in what it means to peer into the world scientifically. Lorraine Daston is Director at the Max Planck Institute for the History of Science in Berlin, Germany. She is the coauthor of Wonders and the Order of Nature, 1150-1750 and the editor of Things That Talk: Object Lessons from Art and Science. Peter Galison is Pellegrino University Professor of the History of Science and of Physics at Harvard University. He is the author of Einstein's Clocks, Poincaré's Maps: Empires of Time, How Experiments End, and Image and Logic: A Material Culture of Microphysics, and other books, and coeditor of The Architecture of Science. (shrink)

Although molecular biology has meant different things at different times, the term is often associated with a tendency to view cellular causation as conforming to simple linear schemas in which macro-scale effects are specified by micro-scale structures. The early achievements of molecular biologists were important for the formation of such an outlook, one to which the discovery of recombinant DNA techniques, and a number of other findings, gave new life even after the complexity of genotype–phenotype
relations had become apparent. Against this (...) background we outline how a range of scientific developments and conceptual considerations can be regarded as enabling and perhaps necessitating contemporary systems approaches. We suggest that philosophical ideas have a valuable part to play in making sense of complex scientific and disciplinary issues. (shrink)

This paper presents a counterfactual account of what a mechanism is. Mechanisms consist of parts, the behavior of which conforms to generalizations that are invariant under interventions, and which are modular in the sense that it is possible in principle to change the behavior of one part independently of the others. Each of these features can be captured by the truth of certain counterfactuals.

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.

"Legend is overdue for replacement, and an adequate replacement must attend to the process of science as carefully as Hull has done. I share his vision of a serious account of the social and intellectual dynamics of science that will avoid both the rosy blur of Legend and the facile charms of relativism.... Because of [Hull's] deep concern with the ways in which research is actually done, Science as a Process begins an important project in the study of science. It (...) is one of a distinguished series of books, which Hull himself edits."—Philip Kitcher, Nature "In Science as a Process, [David Hull] argues that the tension between cooperation and competition is exactly what makes science so successful.... Hull takes an unusual approach to his subject. He applies the rules of evolution in nature to the evolution of science, arguing that the same kinds of forces responsible for shaping the rise and demise of species also act on the development of scientific ideas."—Natalie Angier, New York Times Book Review "By far the most professional and thorough case in favour of an evolutionary philosophy of science ever to have been made. It contains excellent short histories of evolutionary biology and of systematics (the science of classifying living things); an important and original account of modern systematic controversy; a counter-attack against the philosophical critics of evolutionary philosophy; social-psychological evidence, collected by Hull himself, to show that science does have the character demanded by his philosophy; and a philosophical analysis of evolution which is general enough to apply to both biological and historical change."—Mark Ridley, Times Literary Supplement "Hull is primarily interested in how social interactions within the scientific community can help or hinder the process by which new theories and techniques get accepted.... The claim that science is a process for selecting out the best new ideas is not a new one, but Hull tells us exactly how scientists go about it, and he is prepared to accept that at least to some extent, the social activities of the scientists promoting a new idea can affect its chances of being accepted."—Peter J. Bowler, Archives of Natural History "I have been doing philosophy of science now for twenty-five years, and whilst I would never have claimed that I knew everything, I felt that I had a really good handle on the nature of science, Again and again, Hull was able to show me just how incomplete my understanding was.... Moreover, [Science as a Process] is one of the most compulsively readable books that I have ever encountered."—Michael Ruse, Biology and Philosophy. (shrink)

An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent (...) explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

In this powerful work of conceptual and analytical originality, the author argues for the primacy of the material arrangements of the laboratory in the dynamics of modern molecular biology. In a post-Kuhnian move away from the hegemony of theory, he develops a new epistemology of experimentation in which research is treated as a process for producing epistemic things. A central concern of the book is the basic question of how novelty is generated in the empirical sciences. In addressing this question, (...) the author brings French poststructuralist thinking—notably Jacques Derrida’s concepts of “différance” and “historiality”—to bear on the construction of epistemic things. Historiographical perspective shifts from the actors’ minds to their objects of manipulation. These epistemological and historical issues are illuminated in a detailed case study of a particular laboratory, that of the oncologist and biochemist Paul C. Zamecnik and his colleagues, located in a specific setting—the Collis P. Huntington Memorial Hospital of Harvard University at the Massachusetts General Hospital of Boston. The author traces how, between 1945 and 1965, this group developed an experimental system for synthesizing proteins in the test tube that put Zamecnik’s research team at the forefront of those who led biochemistry into the era of molecular biology. (shrink)

Despite the transformation in biological practice and theory brought about by discoveries in molecular biology, until recently philosophy of biology continued to focus on evolutionary biology. When the Human Genome Project got underway in the late 1980s and early 1990s, philosophers of biology -- unlike historians and social scientists -- had little to add to the debate. In this landmark collection of essays, Sahotra Sarkar broadens the scope of current discussions of the philosophy of biology, viewing molecular biology as a (...) unifying perspective on life that complements that of evolutionary biology. His focus is on molecular biology, but the overriding question behind these papers is what molecular biology contributes to all traditional areas of biological research.Molecular biology -- described with some foresight in a 1938 Rockefeller Foundation report as a branch of science in which "delicate modern techniques are being used to investigate ever more minute details" -- and its modeling strategies apparently argue in favor of physical reductionism. Sarkar's first three chapters explore reductionism -- defending it, but cautioning that reduction to molecular interactions is not necessarily a reduction to genetics. The next sections of the book discuss function, exploring how functional explanations pose a problem for reductionism; the informational interpretation of biology and how it interacts with reductionism; and the tension between the unifying framework of molecular biology and the received framework of evolutionary theory. The concluding chapter is an essay in the emerging field of developmental evolution, exploring what molecular biology may contribute to the transformation of evolutionary theory as evolutionary theory takes into account morphogenetic development. (shrink)

An elaboration and defense of the “interaction view of metaphor” introduced in the author's earlier study, “Metaphor” . Special attention is paid to the explication of the metaphors used in the earlier account.The topics discussed include: selection of the “targets” of the theory; classification of metaphors; how metaphorical statements work; relations between metaphors and similes; metaphorical thought; criteria of recognition; the “creative” aspects of metaphors; the ontological status of metaphors.Metaphors are found to be more closely connected with background models than (...) has previously been recognized. (shrink)

Scientific Change How do scientific theories, concepts and methods change over time? Answers to this question have historical parts and philosophical parts. There can be descriptive accounts of the recorded differences over time of particular theories, concepts, and methods—what might be called the shape of scientific change. Many stories of scientific change attempt to give […].

Standard microbial evolutionary ontology is organized according to a nested hierarchy of entities at various levels of biological organization. It typically detects and defines these entities in relation to the most stable aspects of evolutionary processes, by identifying lineages evolving by a process of vertical inheritance from an ancestral entity. However, recent advances in microbiology indicate that such an ontology has important limitations. The various dynamics detected within microbiological systems reveal that a focus on the most stable entities (or features (...) of entities) over time inevitably underestimates the extent and nature of microbial diversity. These dynamics are not the outcome of the process of vertical descent alone. Other processes, often involving causal interactions between entities from distinct levels of biological organisation, or operating at different time scales, are responsible not only for the destabilisation of pre-existing entities, but also for the emergence and stabilisation of novel entities in the microbial world. In this article we consider microbial entities as more or less stabilised functional wholes, and sketch a network-based ontology that can represent a diverse set of processes including, for example, as well as phylogenetic relations, interactions that stabilise or destabilise the interacting entities, spatial relations, ecological connections, and genetic exchanges. We use this pluralistic framework for evaluating (i) the existing ontological assumptions in evolution (e.g. whether currently recognized entities are adequate for understanding the causes of change and stabilisation in the microbial world), and (ii) for identifying hidden ontological kinds, essentially invisible from within a more limited perspective. We propose to recognize additional classes of entities that provide new insights into the structure of the microbial world, namely “processually equivalent” entities, “processually versatile” entities, and “stabilized” entities. (shrink)

This is an important book precisely because there is none other quite like it.

Philosophy can shed light on mathematical modeling and the juxtaposition of modeling and empirical data. This paper explores three philosophical traditions of the structure of scientific theory—Syntactic, Semantic, and Pragmatic—to show that each illuminates mathematical modeling. The Pragmatic View identifies four critical functions of mathematical modeling: (1) unification of both models and data, (2) model fitting to data, (3) mechanism identification accounting for observation, and (4) prediction of future observations. Such facets are explored using a recent exchange between two groups (...) of mathematical modelers in plant biology. Scientific debate can arise from different modeling philosophies. (shrink)

A high profile context in which physics and biology meet today is in the new field of systems biology. Systems biology is a fascinating subject for sociological investigation because the demands of interdisciplinary collaboration have brought epistemological issues and debates front and centre in discussions amongst systems biologists in conference settings, in publications, and in laboratory coffee rooms. One could argue that systems biologists are conducting their own philosophy of science. This paper explores the epistemic aspirations of the field by (...) drawing on interviews with scientists working in systems biology, attendance at systems biology conferences and workshops, and visits to systems biology laboratories. It examines the discourses of systems biologists, looking at how they position their work in relation to previous types of biological inquiry, particularly molecular biology. For example, they raise the issue of reductionism to distinguish systems biology from molecular biology. This comparison with molecular biology leads to discussions about the goals and aspirations of systems biology, including epistemic commitments to quantification, rigor and predictability. Some systems biologists aspire to make biology more similar to physics and engineering by making living systems calculable, modelable and ultimately predictable—a research programme that is perhaps taken to its most extreme form in systems biology’s sister discipline: synthetic biology. Other systems biologists, however, do not think that the standards of the physical sciences are the standards by which we should measure the achievements of systems biology, and doubt whether such standards will ever be applicable to ‘dirty, unruly living systems’. This paper explores these epistemic tensions and reflects on their sociological dimensions and their consequences for future work in the life sciences. (shrink)

Philosophers of science increasingly recognize the importance of idealization: the intentional introduction of distortion into scientific theories. Yet this recognition has not yielded consensus about the nature of idealization. e literature of the past thirty years contains disparate characterizations and justifications, but little evidence of convergence towards a common position.

Thomas Kuhn had little to say about scientific change in biological science, and biologists are ambivalent about how applicable his framework is for their disciplines. We apply Kuhn’s account of paradigm change to evolutionary microbiology, where key Darwinian tenets are being challenged by two decades of findings from molecular phylogenetics. The chief culprit is lateral gene transfer, which undermines the role of vertical descent and the representation of evolutionary history as a tree of life. To assess Kuhn’s relevance to this (...) controversy, we add a social analysis of the scientists involved to the historical and philosophical debates. We conclude that while Kuhn’s account may capture aspects of the pattern of an episode of scientific change, he has little to say about how the process of generating new understandings is occurring in evolutionary microbiology. Once Kuhn’s application is limited to that of an initial investigative probe into how scientific problem-solving occurs, his disciplinary scope becomes broader. (shrink)

Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...

A scientific community cannot practice its trade without some set of received beliefs. These beliefs form the foundation of the "educational initiation that prepares and licenses the student for professional practice". The nature of the "rigorous and rigid" preparation helps ensure that the received beliefs are firmly fixed in the student's mind. Scientists take great pains to defend the assumption that scientists know what the world is like...To this end, "normal science" will often suppress novelties which undermine its foundations. Research (...) is therefore not about discovering the unknown, but rather "a strenuous and devoted attempt to force nature into the conceptual boxes supplied by professional education". (shrink)

With this manifesto, John Dupré systematically attacks the ideal of scientific unity by showing how its underlying assumptions are at odds with the central conclusions of science itself.

This paper attempts to elucidate three characteristics of causal relationships that are important in biological contexts. Stability has to do with whether a causal relationship continues to hold under changes in background conditions. Proportionality has to do with whether changes in the state of the cause “line up” in the right way with changes in the state of the effect and with whether the cause and effect are characterized in a way that contains irrelevant detail. Specificity is connected both to (...) David Lewis’ notion of “influence” and also with the extent to which a causal relation approximates to the ideal of one cause–one effect. Interrelations among these notions and their possible biological significance are also discussed. (shrink)

The volume is a collection of essays devoted to the analysis of scientific change and stability. It explores the balance and tension that exist between commensurability and continuity on the one hand, and incommensurability and discontinuity on the other. Moreover, it discusses some central epistemological consequences regarding the nature of scientific progress, rationality and realism. In relation to these topics, it investigates a number of new avenues, and revisits some familiar issues, with a focus on the history and philosophy of (...) physics, and an emphasis on developments in cognitive sciences as well as on the claims of “new experimentalists”. The book constitutes fully revised versions of papers which were originally presented at the international colloquium held at the University of Nancy, France, in June 2004. (shrink)

The philosophical theory of scientific explanation proposed here involves a radically new treatment of causality that accords with the pervasively statistical character of contemporary science. Wesley C. Salmon describes three fundamental conceptions of scientific explanation--the epistemic, modal, and ontic. He argues that the prevailing view is untenable and that the modal conception is scientifically out-dated. Significantly revising aspects of his earlier work, he defends a causal/mechanical theory that is a version of the ontic conception. Professor Salmon's theory furnishes a robust (...) argument for scientific realism akin to the argument that convinced twentieth-century physical scientists of the existence of atoms and molecules. To do justice to such notions as irreducibly statistical laws and statistical explanation, he offers a novel account of physical randomness. The transition from the "reviewed view" of scientific explanation to the causal/mechanical model requires fundamental rethinking of basic explanatory concepts. (shrink)

The sociological dimension of science is studied using the discovery of the Wasserman reaction and its accidental application as a test for syphilis as a basis, ...

The prehistory of science and technology studies -- The Kuhnian revolution -- Questioning functionalism in the sociology of science -- Stratification and discrimination -- The strong programme and the sociology of knowledge -- The social construction of scientific and technical realities -- Feminist epistemologies of science -- Actor-network theory -- Two questions concerning technology -- Studying laboratories -- Controversies -- Standardization and objectivity -- Rhetoric and discourse -- The unnaturalness of science and technology -- The public understanding of science -- (...) Expertise and public participation -- Political economies of knowledge. (shrink)

Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.

This is a comprehensive discussion of complexity as it arises in physical, chemical, and biological systems, as well as in mathematical models of nature. Common features of these apparently unrelated fields are emphasised and incorporated into a uniform mathematical description, with the support of a large number of detailed examples and illustrations. The quantitative study of complexity is a rapidly developing subject with special impact in the fields of physics, mathematics, information science, and biology. Because of the variety of the (...) approaches, no comprehensive discussion has previously been attempted. This book will be of interest to graduate students and researchers in physics (nonlinear dynamics, fluid dynamics, solid-state, cellular automata, stochastic processes, statistical mechanics and thermodynamics), mathematics (dynamical systems, ergodic and probability theory), information and computer science (coding, information theory and algorithmic complexity), electrical engineering and theoretical biology. (shrink)

In this book Bruno Latour brings together these different approaches to provide a lively and challenging analysis of science, demonstrating how social context..

Thomas S. Kuhn's classic book is now available with a new index.

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

In this paper I offer an analysis of causation based upon a theory of mechanisms-complex systems whose internal parts interact to produce a system's external behavior. I argue that all but the fundamental laws of physics can be explained by reference to mechanisms. Mechanisms provide an epistemologically unproblematic way to explain the necessity which is often taken to distinguish laws from other generalizations. This account of necessity leads to a theory of causation according to which events are causally related when (...) there is a mechanism that connects them. I present reasons why the lack of an account of fundamental physical causation does not undermine the mechanical account. (shrink)

The official model of explanation proposed by the logical empiricists, the covering law model, is subject to familiar objections. The goal of the present paper is to explore an unofficial view of explanation which logical empiricists have sometimes suggested, the view of explanation as unification. I try to show that this view can be developed so as to provide insight into major episodes in the history of science, and that it can overcome some of the most serious difficulties besetting the (...) covering law model. (shrink)