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Added by: Franci Mangraviti and Viviane FairbankAbstract:
The paper argues that science's focus on the ideal and stable hides, and thus contributes to the silencing of, the real and fluid, which corresponds to womanhood.Alexandrova, Anna, Robert Northcott. It’s just a feeling: why economic models do not explain2013, Journal of Economic Methodology, 20(3), 262-267-
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Added by: Simon Fokt, Contributed by: Patricia Rich
Abstract: Julian Reiss correctly identified a trilemma about economic models: we cannot maintain that they are false, but nevertheless explain and that only true accounts explain. In this reply we give reasons to reject the second premise – that economic models explain. Intuitions to the contrary should be distrusted.Comment: This is a good short article to read alongside Reiss' important paper on the explanation paradox, in the context of a philosophy of economics or social science class. It argues against Reiss' premise that economic models are explanatory. It draws on, but does not require, knowledge of anyone's positions in the larger debate on the status of formal models.
Nelson, Julie. Feminism and economics1995, Journal of Economic Perspectives, 9(2), 131-148.-
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Added by: Simon Fokt, Contributed by: Patricia Rich
Introduction: An article in The Chronicle of Higher Education of June 30, 1993, reported, “Two decades after it began redefining debates” in many other disciplines, “feminist thinking seems suddenly to have arrived in economics.” Many economists, of course, did not happen to be in the station when this train arrived, belated as it might be. Many who might have heard rumor of its coming have not yet learned just what arguments are involved or what it promises for the refinement of the profession. The purpose of this essay is to provide a low-cost way of gaining some familiarity.
Comment: This text provides a good overview, as well as an argument regarding how the field of economics reflects masculine values, and how the field could be improved by removing this bias. It makes sense to read the text with students who have some familiarity with economics itself. It should be noted that the field of economics actually has changed in some of the ways the author recommends, since the time of publication, but the article is still relevant and provokes plenty of discussion.
Potochnik, Angela. Feminist implications of model-based science2012, 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.Comment:
Parker, Wendy S.. When Climate Models Agree: The Significance of Robust Model Predictions2011, 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 secureComment:
Leonelli, Sabina. What distinguishes data from models?2019, European Journal for Philosophy of Science 9 (2):22.-
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Added by: Sara Peppe
Abstract: I propose a framework that explicates and distinguishes the epistemic roles of data and models within empirical inquiry through consideration of their use in scientific practice. After arguing that Suppes' characterization of data models falls short in this respect, I discuss a case of data processing within exploratory research in plant phenotyping and use it to highlight the difference between practices aimed to make data usable as evidence and practices aimed to use data to represent a specific phenomenon. I then argue that whether a set of objects functions as data or models does not depend on intrinsic differences in their physical properties, level of abstraction or the degree of human intervention involved in generating them, but rather on their distinctive roles towards identifying and characterizing the targets of investigation. The paper thus proposes a characterization of data models that builds on Suppes' attention to data practices, without however needing to posit a fixed hierarchy of data and models or a highly exclusionary definition of data models as statistical constructs.Comment: This article deepens the role of model an data in the scientific investigation taking into account the scientific practice. Obviously, a general framework of the themes the author takes into account is needed.
Blanchette, Patricia. Models and Modality2000, Synthese 124(1): 45-72.-
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Added by: Berta Grimau, Contributed by: Patricia Blanchette
Abstract: This paper examines the connection between model-theoretic truth and necessary truth. It is argued that though the model-theoretic truths of some standard languages are demonstrably "necessary" (in a precise sense), the widespread view of model-theoretic truth as providing a general guarantee of necessity is mistaken. Several arguments to the contrary are criticized.Comment: This text would be best used as secondary reading in an intermediate or an advanced philosophy of logic course. For example, it can be used as a secondary reading in a section on the connection between model-theoretic truth and necessary truth.
Morrison, Margaret. Spin: All is not what it seems2007, Studies in History and Philosophy of Science Part B 38(3): 529-55.-
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Added by: Laura Jimenez
Abstract: Spin is typically thought to be a fundamental property of the electron and other elementary particles. Although it is defined as an internal angular momentum much of our understanding of it is bound up with the mathematics of group theory. This paper traces the development of the concept of spin paying particular attention to the way that quantum mechanics has influenced its interpretation in both theoretical and experimental contexts. The received view is that electron spin was discovered experimentally by Stern and Gerlach in 1921, 5 years prior to its theoretical formulation by Goudsmit and Uhlenbeck. However, neither Goudsmit nor Uhlenbeck, nor any others involved in the debate about spin cited the Stern-Gerlach experiment as corroborating evidence. In fact, Bohr and Pauli were emphatic that the spin of a single electron could not be measured in classical experiments. In recent years experiments designed to refute the Bohr-Pauli thesis and measure electron spin have been carried out. However, a number of ambiguities surround these results - ambiguities that relate not only to the measurements themselves but to the interpretation of the experiments. After discussing these various issues the author raises some philosophical questions about the ontological and epistemic status of spin.Comment: The goal of the paper is to uncover and isolate how spin presents problems for traditional realism and to illustrate the power that theories like quantum mechanics have for shaping both philosophical questions and answers. It is adequate for higher-level postgraduate courses in Philosophy of Science.
Elgin, Catherine. Understanding and The Facts2007, Philosophical Studies 132: 33-42.-
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Added by: Giada Fratantonio
Abstract: If understanding is factive, the propositions that express an understanding are true. I argue that a factive conception of understanding is unduly restrictive. It neither reflects our practices in ascribing understanding nor does justice to contemporary science. For science uses idealizations and models that do not to mirror the facts. Strictly speaking, they are false. By appeal to exemplification, I devise a more generous, flexible conception of understanding that accommodates science, reflects our practices, and shows a sufficient but not slavish sensitivity to the facts.Comment: This paper could be used in an undergraduate or graduate course on epistemology, philosophy of science, or any area in which the nature of understanding is at issue. The paper is quite brief and not particularly technical. It makes a good case for a claim that initially sounds very counterintuitive, so can serve as a good prompt for a discussion.
Nersessian, Nancy. Creating Scientific Concepts2008, 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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Irigaray, Luce. The “Mechanics” of Fluids
1985, In This Sex Which Is Not One, trans. C. Porter and C. Burke
Comment:
available in this Blueprint