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Cardona, Carlos Alberto, , . Kepler: Analogies in the search for the law of refraction
2016, Studies in History and Philosophy of Science Part A 59:22-35.
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Added by: Clotilde Torregrossa, Contributed by: Juan R. Loaiza

Publisher’s Note: This paper examines the methodology used by Kepler to discover a quantitative law of refraction. The aim is to argue that this methodology follows a heuristic method based on the following two Pythagorean principles: (1) sameness is made known by sameness, and (2) harmony arises from establishing a limit to what is unlimited. We will analyse some of the author’s proposed analogies to find the aforementioned law and argue that the investigation’s heuristic pursues such principles.

Comment: [This is a stub entry. Please add your comments to help us expand it]

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Douglas, Heather, , . Science, Policy, and the Value-Free Ideal
2009, University of Pittsburgh Press.
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Added by: Simon Fokt, Contributed by: Patricia Rich

Publisher’s Note: The role of science in policymaking has gained unprecedented stature in the United States, raising questions about the place of science and scientific expertise in the democratic process. Some scientists have been given considerable epistemic authority in shaping policy on issues of great moral and cultural significance, and the politicizing of these issues has become highly contentious.

Since World War II, most philosophers of science have purported the concept that science should be “value-free.” In Science, Policy and the Value-Free Ideal, Heather E. Douglas argues that such an ideal is neither adequate nor desirable for science. She contends that the moral responsibilities of scientists require the consideration of values even at the heart of science. She lobbies for a new ideal in which values serve an essential function throughout scientific inquiry, but where the role values play is constrained at key points, thus protecting the integrity and objectivity of science. In this vein, Douglas outlines a system for the application of values to guide scientists through points of uncertainty fraught with moral valence.

Following a philosophical analysis of the historical background of science advising and the value-free ideal, Douglas defines how values should-and should not-function in science. She discusses the distinctive direct and indirect roles for values in reasoning, and outlines seven senses of objectivity, showing how each can be employed to determine the reliability of scientific claims. Douglas then uses these philosophical insights to clarify the distinction between junk science and sound science to be used in policymaking. In conclusion, she calls for greater openness on the values utilized in policymaking, and more public participation in the policymaking process, by suggesting various models for effective use of both the public and experts in key risk assessments.

Comment: Chapter 5, ‘The structure of values in science’, is a good introduction to the topic of the role of values in science, while defending a particular perspective. Basic familiarity with philosophy of science or science itself should be enough to understand and engage with it.

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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, Contributed by:

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.

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Longino, Helen, , . The Social dimensions of scientific knowledge
2016, The Stanford Encyclopedia of Philosophy (Spring 2016 Edition), Edward N. Zalta (ed.)
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Added by: Laura Jimenez, Contributed by:

Summary: Attention to the social dimensions of scientific knowledge is a relatively recent focus of philosophers of science. While some earlier philosophers made contributions to the topic that are still of relevance today, modern interest was stimulated by historians and sociologists of science such as Thomas Kuhn and the growing role played by the sciences in society and, by extension, in the lives of its citizens. There are two main vectors of interest: internal relations within scientific communities, and relations between science and society. This article covers literature in both categories. It starts with work that functions as historical backdrop to current work. As a subfield within philosophy of science, this area is too recent to have dedicated journals and has only a few anthologies. Nevertheless, there are resources in both categories. The remainder of the article lists work in specific subareas.

Comment: A good introduction to the study of social dimensions of scientific knowledge. Recommended for anyone interested in the social direction of science. The paper is easy to comprehend so could be read by both postgraduates and undergraduates.

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Parke, Emily, , . Experiments, Simulations, and Epistemic Privilege
2014, Philosophy of Science 81(4): 516-536.
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Added by: Nick Novelli, Contributed by:

Abstract: Experiments are commonly thought to have epistemic privilege over simulations. Two ideas underpin this belief: first, experiments generate greater inferential power than simulations, and second, simulations cannot surprise us the way experiments can. In this article I argue that neither of these claims is true of experiments versus simulations in general. We should give up the common practice of resting in-principle judgments about the epistemic value of cases of scientific inquiry on whether we classify those cases as experiments or simulations, per se. To the extent that either methodology puts researchers in a privileged epistemic position, this is context sensitive.

Comment: Valuable in raising questions about preconceptions of “science experiments”. This article would be useful as part of a look at scientific methodology and the real value obtained from our scientific practices.

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Shrader-Frechette, Kristine, , . Tainted: How Philosophy of Science can expose bad science
2014, Oxford University Press USA.
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Added by: Laura Jimenez, Contributed by:

Abstract: Lawyers often work pro bono to liberate death-row inmates from flawed legal verdicts that otherwise would kill them. This is the first book on practical philosophy of science, how to practically evaluate scientific findings with life-and-death consequences. Showing how to uncover scores of scientific flaws – typically used by special interests who try to justify their pollution – this book aims to liberate many potential victims of environmentally induced disease and death.It shows how citizens can help uncover flawed science and thus liberate people from science-related societal harms such as pesticides, waste dumps, and nuclear power. It shows how flawed biology, economics, hydrogeology, physics, statistics, and toxicology are misused in ways that make life-and-death differences for humans. It thus analyzes science at the heart of contemporary controversies – from cell phones, climate change, and contraceptives, to plastic food containers and radioactive waste facilities. It illustrates how to evaluate these scientific findings, instead of merely describing what they are. Practical evaluation of science is important because, at least in the United States, 75 percent of all science is funded by special interests, to achieve specific practical goals, such as developing pharmaceuticals or showing some pollutant causes no harm. Of the remaining 25 percent of US science funding, more than half addresses military goals. This means that less than one-eighth of US science funding is for basic science; roughly seven-eighths is done by special interests, for practical projects from which they hope to profit. The problem, however, is that often this flawed, special-interest science harms the public.

Comment: Recommended for students in philosophy of science, environmental ethics or science policy. Could serve as an introductory reading for practical philosophy of science. It is easy to read and suitable for undergraduate students.

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Thalos, Mariam, , . Explanation is a genus: An essay on the varieties of scientific explanation
2002, Synthese 130(3): 317-354.
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Added by: Nick Novelli, Contributed by:

Abstract: I shall endeavor to show that every physical theory since Newton explainswithout drawing attention to causes-that, in other words, physical theories as physical theories aspire to explain under an ideal quite distinctfrom that of causal explanation. If I am right, then even if sometimes theexplanations achieved by a physical theory are not in violation ofthe standard of causal explanation, this is purely an accident. For physicaltheories, as I will show, do not, as such, aim at accommodating the goals oraspirations of causal explanation. This will serve as the founding insightfor a new theory of explanation, which will itself serve as the cornerstoneof a new theory of scientific method.

Comment: A striking argument that science does not employ causal explanations. Since this is a commonly-held assumption, this would be interesting to present in the context of scientific methodology, or in an exploration of causation as part of a challenge to whether the idea of causation is actually useful or necessary. Provides good historical context to support its claims. Best taught at an advanced or graduate level.

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