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Comparisons of rival explanations or theories often involve vague appeals to explanatory power. In this paper, we dissect this metaphor by distinguishing between different dimensions of the goodness of an explanation: non-sensitivity, cognitive salience, precision, factual accuracy and degree of integration. These dimensions are partially independent and often come into conflict. Our main contribution is to go beyond simple stipulation or description by explicating why these factors are taken to be explanatory virtues. We accomplish this by using the contrastive-counterfactual approach (...) |
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Levins and Lewontin have contributed significantly to our philosophical understanding of the structures, processes, and purposes of biological mathematical theorizing and modeling. Here I explore their separate and joint pleas to avoid making abstract and ideal scientific models ontologically independent by confusing or conflating our scientific models and the world. I differentiate two views of theorizing and modeling, orthodox and dialectical, in order to examine Levins and Lewontin’s, among others, advocacy of the latter view. I compare the positions of these (...) |
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I defend an account of explanatory depth according to which explanations in the non-fundamental sciences can be deeper than explanations in fundamental physics. |
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Theorizing in ecology and evolution often proceeds via the construction of multiple idealized models. To determine whether a theoretical result actually depends on core features of the models and is not an artifact of simplifying assumptions, theorists have developed the technique of robustness analysis, the examination of multiple models looking for common predictions. A striking example of robustness analysis in ecology is the discovery of the Volterra Principle, which describes the effect of general biocides in predator-prey systems. This paper details (...) |
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Evolutionary processes such as natural selection and random drift are commonly regarded as causes of population-level change. We respond to a recent challenge that drift and selection are best understood as statistical trends, not causes. Our reply appeals to manipulation as a strategy for uncovering causal relationships: if you can systematically manipulate variable A to bring about a change in variable B, then A is a cause of B. We argue that selection and drift can be systematically manipulated to produce (...) |
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The aim of this paper is to develop ideas about robustness analyses. I introduce a form of robustness analysis that I call sufficient parameter robustness, which has been neglected in the literature. I claim that sufficient parameter robustness is different from derivational robustness, the focus of previous research. My purpose is not only to suggest a new taxonomy of robustness, but also to argue that previous authors have concentrated on a narrow sense of robustness analysis, which they have inadequately distinguished (...) |
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The basic idea behind the Competitive Exclusion Principle is that species that have similar or identical niches cannot stably coexist in the same place for long periods of time when their common resources are limiting. A more exact definition of the CEP states that, in equilibrium, n number of sympatric species competing for a common set of limiting resources cannot stably coexist indefinitely on fewer than n number of resources. The magnitude or intensity of competition between species is proportional to (...) |
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It is often argued that biological generalizations have a distinctive and special status by comparison with the generalizations of other natural sciences, such as that biological generalizations are riddled with exceptions defying systematic and simple treatment. This special status of biology is used as a premise in arguments that posit a deprived explanatory, nomological, or methodological status in the biological sciences. I will discuss the traditional and still almost universally held idea that the biological sciences cannot deal with exceptions and (...) |
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How are scientific explanations possible in ecology, given that there do not appear to be many—if any—ecological laws? To answer this question, I present and defend an account of scientific causal explanation in which ecological generalizations are explanatory if they are invariant rather than lawlike. An invariant generalization continues to hold or be valid under a special change—called an intervention—that changes the value of its variables. According to this account, causes are difference-makers that can be intervened upon to manipulate or (...) |
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Ecologists attempt to understand the diversity of life with mathematical models. Often, mathematical models contain simplifying idealizations designed to cope with the blooming, buzzing confusion of the natural world. This strategy frequently issues in models whose predictions are inaccurate. Critics of theoretical ecology argue that only predictively accurate models are successful and contribute to the applied work of conservation biologists. Hence, they think that much of the mathematical work of ecologists is poor science. Against this view, I argue that model (...) |
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Reductionists in biology claim that all biological events can be explained in terms of genes and macromolecules alone, while antireductionists argue that some biological events must be explained at a higher level. The literature, however, does not distinguish between different kinds of molecular explanation. The goal of this article is to identify and analyze three such kinds. The analysis of molecular explanations herein carries an important philosophical implication; in shunning crude reductionism and extreme versions of holism, we can combine the (...) |
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The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory of computational explanation, I (...) |
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The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change. |
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Abstraction is seen as an active process which both enlightens and obscures. Abstractions are not true or false but relatively enlightening or obscuring according to the problem under study; different abstractions may grasp different aspects of a problem. Abstractions may be useless if they can answer questions only about themselves. A theoretical enterprise explores reality through acluster of abstractions that use different perspectives, temporal and horizontal scales, and assumes different givens. |
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Proponents of mechanistic explanation all acknowledge the importance of organization. But they have also tended to emphasize specificity with respect to parts and operations in mechanisms. We argue that in understanding one important mode of organization—patterns of causal connectivity—a successful explanatory strategy abstracts from the specifics of the mechanism and invokes tools such as those of graph theory to explain how mechanisms with a particular mode of connectivity will behave. We discuss the connection between organization, abstraction, and mechanistic explanation and (...) |
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We claim that the process of theoretical model refinement in economics is best characterised as robustness analysis: the systematic examination of the robustness of modelling results with respect to particular modelling assumptions. We argue that this practise has epistemic value by extending William Wimsatt's account of robustness analysis as triangulation via independent means of determination. For economists robustness analysis is a crucial methodological strategy because their models are often based on idealisations and abstractions, and it is usually difficult to tell (...) |
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This paper explores the fundamental ideas that have motivated the idea of emergence and the movement of emergentism. The concept of reduction, which lies at the heart of the emergence idea is explicated, and it is shown how the thesis that emergent properties are irreducible gives a unified account of emergence. The paper goes on to discuss two fundamental unresolved issues for emergentism. The first is that of giving a “positive” characterization of emergence; the second is to give a coherent (...) |
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The central aim of this paper is to shed light on the nature of explanation in computational neuroscience. I argue that computational models in this domain possess explanatory force to the extent that they describe the mechanisms responsible for producing a given phenomenon—paralleling how other mechanistic models explain. Conceiving computational explanation as a species of mechanistic explanation affords an important distinction between computational models that play genuine explanatory roles and those that merely provide accurate descriptions or predictions of phenomena. It (...) |
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The study of similarity is fundamental to biological inquiry. Many homology concepts have been formulated that function successfully to explain similarity in their native domains, but fail to provide an overarching account applicable to variably interconnected and independent areas of biological research despite the monistic standpoint from which they originate. The use of multiple, explicitly articulated homology concepts, applicable at different levels of the biological hierarchy, allows a more thorough investigation of the nature of biological similarity. Responsible epistemological pluralism as (...) |
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Non-reductive physicalists have long held that the special sciences offer explanations of some phenomena that are objectively superior to physical explanations. This explanatory “autonomy” has largely been based on the multiple realizability argument. Recently, in the face of the local reduction and disjunctive property responses to multiple realizability, some defenders of non-reductive physicalism have suggested that autonomy can be grounded merely in human cognitive limitations. In this paper, I argue that this is mistaken. By distinguishing between two kinds of abstraction (...) |
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