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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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Parker, Wendy S.. When Climate Models Agree: The Significance of Robust Model Predictions
2011, Philosophy of Science 78 (4):579-600.
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Added by: Clotilde Torregrossa, Contributed by: Simon Fokt
Abstract: This article identifies conditions under which robust predictive modeling results have special epistemic significance---related to truth, confidence, and security---and considers whether those conditions hold in the context of present-day climate modeling. The findings are disappointing. When today's climate models agree that an interesting hypothesis about future climate change is true, it cannot be inferred---via the arguments considered here anyway---that the hypothesis is likely to be true or that scientists' confidence in the hypothesis should be significantly increased or that a claim to have evidence for the hypothesis is now more secure

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Potochnik, Angela. Feminist implications of model-based science
2012, Studies in History and Philosophy of Science Part A 43 (2):383-389.
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Added by: Clotilde Torregrossa, Contributed by: Simon Fokt
Abstract: Recent philosophy of science has witnessed a shift in focus, in that significantly more consideration is given to how scientists employ models. Attending to the role of models in scientific practice leads to new questions about the representational roles of models, the purpose of idealizations, why multiple models are used for the same phenomenon, and many more besides. In this paper, I suggest that these themes resonate with central topics in feminist epistemology, in particular prominent versions of feminist empiricism, and that model-based science and feminist epistemology each has crucial resources to offer the other's project.

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Sterrett, Susan G.. The morals of model-making
2014, Studies in History and Philosophy of Science 26: 31- 45.
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Added by: Helen Morley
Abstract: I address questions about values in model-making in engineering, specifically: Might the role of values be attributable solely to interests involved in specifying and using the model? Selected examples illustrate the surprisingly wide variety of things one must take into account in the model-making itself. The notions of system , and physically similar systems are important and powerful in determining what is relevant to an engineering model. Another example illustrates how an idea to completely re-characterize, or reframe, an engineering problem arose during model-making.I employ a qualitative analogue of the notion of physically similar systems. Historical cases can thus be drawn upon; I illustrate with a comparison between a geoengineering proposal to inject, or spray, sulfate aerosols, and two different historical cases involving the spraying of DDT . The current geoengineering proposal is seen to be like the disastrous and counterproductive case, and unlike the successful case, of the spraying of DDT. I conclude by explaining my view that model-making in science is analogous to moral perception in action, drawing on a view in moral theory that has come to be called moral particularism.

Comment: Further reading, particulary in relation to geoengineering responses to climate change. Also of interest in relation to engineering & technology ethics.

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