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Sterrett, Susan G.. Darwin’s analogy between artificial and natural selection: how does it go?
2002, Studies in History and Philosophy of Science Part C 33 (1):151-168.

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Added by: Chris Blake-Turner, Contributed by: Susan G. Sterrett

Abstract: The analogy Darwin drew between artificial and natural selection in "On the Origin of Species" has a detailed structure that has not been appreciated. In Darwin's analogy, the kind of artificial selection called Methodical selection is analogous to the principle of divergence in nature, and the kind of artificial selection called Unconscious selection is analogous to the principle of extinction in nature. This paper argues that it is the analogy between these two different principles familiar from his studies of artificial selection and the two different principles he claims are operative in nature that provides the main structure and force of the analogy he uses to make his case for the power of natural selection to produce new species. Darwin's statements explicitly distinguishing between these two kinds of principles at work in nature occur prominently in the text of the Origin. The paper also shows that a recent revisionist claim that Darwin did not appeal to the efficacy of artificial selection is mistaken

Comment: This paper is useful in discussing Darwin's theory as he presented it, i.e., without a knowledge of genetics. It could also be used in discussing analogy and/or metaphor in science.

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Nersessian, Nancy. Creating Scientific Concepts
2008, MIT Press.

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Added by: Laura Jimenez

Publisher's Note: How do novel scientific concepts arise? In Creating Scientific Concepts, Nancy Nersessian seeks to answer this central but virtually unasked question in the problem of conceptual change. She argues that the popular image of novel concepts and profound insight bursting forth in a blinding flash of inspiration is mistaken. Instead, novel concepts are shown to arise out of the interplay of three factors: an attempt to solve specific problems; the use of conceptual, analytical, and material resources provided by the cognitive-social-cultural context of the problem; and dynamic processes of reasoning that extend ordinary cognition. Focusing on the third factor, Nersessian draws on cognitive science research and historical accounts of scientific practices to show how scientific and ordinary cognition lie on a continuum, and how problem-solving practices in one illuminate practices in the other.

Comment: Nersessian’s book has a two-fold foundation, first, the empirical analysis of two cases of scientific thinking (one from Maxwell and one from a verbal protocol of a scientist); second, philosophical and cognitive analysis of the overall picture of meaning change in science that is the result of her work. The book presents her argument via an introductory chapter, followed by five chapters that develop the argument. Chapter 4 is particularly interesting for the cognitive-scientist: in this chapter Nersessian develops her account of the basic cognitive processes that underlie model-based reasoning. The new approach to mental modeling and analogy, together with Nersessian’s cognitive-historical approach, make Creating Scientific Concepts equally valuable to cognitive science and philosophy of science. The book is accessible and well-written, and should be a relatively quick read for anyone with a previous background in the mentioned fields. It is mainly recommended for postgraduate courses.

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Hesse, Mary. Models in Physics
1953, British Journal for the Philosophy of Science 4(15): 198-214.

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Added by: Laura Jimenez

Summary: In this article Hesse defends the idea that scientific theories are hypothetico-deductive in form. She examines this hypothetico-deductive method by considering some examples from nineteenth-century mathematical physics. By means of these examples she brings out two points about scientific hypothesis. The first is that mathematical formalisms, when used as hypotheses in the description of physical phenomena, may function like the mechanical models of an earlier stage in physics, without having in themselves any mechanical or other physical interpret. The second point is that most physicists do not regard models as literal descriptions of nature, but as standing in a relation of analogy to nature.

Comment: A really good paper about models in science, mathematical formalism and hypothesis. Highly recomended for postgraduates studying philosophy of physics, although it could also be readable by undergraduates (last years) with previous knowledge of scientific modelling.

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