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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:

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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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Duflo, Esther. Field Experiments in Development Economics
2006, Advances in Economics and Econometrics: Theory and Applications, Ninth World Congress (Econometric Society Monographs), R. Blundell, W. Newey, & T. Persson (eds.), 322-348
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Added by: Björn Freter, Contributed by: Johanna Thoma
Abstract: There is a long tradition in development economics of collecting original data to test specific hypotheses. Over the last 10 years, this tradition has merged with an expertise in setting up randomized field experiments, resulting in an increasingly large number of studies where an original experiment has been set up to test economic theories and hypotheses. This paper extracts some substantive and methodological lessons from such studies in three domains: incentives, social learning, and time-inconsistent preferences. The paper argues that we need both to continue testing existing theories and to start thinking of how the theories may be adapted to make sense of the field experiment results, many of which are starting to challenge them. This new framework could then guide a new round of experiments.

Comment: Duflo, of the MIT Poverty Action Lab and recent Nobel Prize Winner, summarizes some of the successes of randomized field evaluations in development economics. She then argues that the way forward for development economics should indeed involve some theorizing, but theorizing on the basis of our new empirical evidence - which might end up looking quite different from standard economic theory. This is a very useful (opinionated) introduction to field experiments for a week on field experiments in a philosophy of economics or philosophy of the social sciences course.

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Franklin, L. R.. Exploratory Experiments
2005, Philosophy of Science 72(5): 888-899.
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Added by: Nick Novelli
Abstract: Philosophers of experiment have acknowledged that experiments are often more than mere hypothesis-tests, once thought to be an experiment's exclusive calling. Drawing on examples from contemporary biology, I make an additional amendment to our understanding of experiment by examining the way that `wide' instrumentation can, for reasons of efficiency, lead scientists away from traditional hypothesis-directed methods of experimentation and towards exploratory methods.

Comment: Good exploration of the role of experiments, challenging the idea that they are solely useful for testing clearly defined hypotheses. Uses many practical examples, but is very concise and clear. Suitable for undergraduate teaching in an examination of scientific methods in a philosophy of science course.

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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
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
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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Okasha, Samir. Experiment, observation and the confirmation of laws
2011, Analysis 71(2): 222-232.
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Added by: Laura Jimenez
Summary: It is customary to distinguish experimental from purely observational sciences. The former include physics and molecular biology, the latter astronomy and palaeontology. Surprisingly, mainstream philosophy of science has had rather little to say about the observational/experimental distinction. For example, discussions of confirmation usually invoke a notion of 'evidence', to be contrasted with 'theory' or 'hypothesis'; the aim is to understand how the evidence bears on the hypothesis. But whether this 'evidence' comes from observation or experiment generally plays no role in the discussion; this is true of both traditional and modern confirmation theories, Bayesian and non-Bayesian. In this article, the author sketches one possible explanation, by suggesting that observation and experiment will often differ in their confirmatory power. Based on a simple Bayesian analysis of confirmation, Okasha argues that universal generalizations (or 'laws') are typically easier to confirm by experimental intervention than by pure observation. This is not to say that observational confirmation of a law is impossible, which would be flatly untrue. But there is a general reason why confirmation will accrue more easily from experimental data, based on a simple though oft-neglected feature of Bayesian conditionalization.

Comment: Previous knowledge of Bayesian conditioning might be needed. The article is suitable for postgraduate courses in philosophy of science focusing in the distinction between observational and experimental science.

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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
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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Parker, Wendy. Model Evaluation: An Adequacy-for-Purpose View
2020, Philosophy of Science 87 (3):457-477
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Added by: Simon Fokt

Abstract: According to an adequacy-for-purpose view, models should be assessed with respect to their adequacy or fitness for particular purposes. Such a view has been advocated by scientists and philosophers alike. Important details, however, have yet to be spelled out. This article attempts to make progress by addressing three key questions: What does it mean for a model to be adequate-for-purpose? What makes a model adequate-for-purpose? How does assessing a model’s adequacy-for-purpose differ from assessing its representational accuracy? In addition, responses are given to some objections that might be raised against an adequacy-for-purpose view.

Comment: A good overview (and a defence) of the adequacy-for-purpose view on models. Makes the case that models should be assessed with respect to their adequacy for particular purposes.

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Rochberg, Francesca. Before Nature: Cuneiform Knowledge and the History of Science
2016, Chicago University Press
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, Contributed by: Quentin Pharr
Publisher’s Note: In the modern West, we take for granted that what we call the “natural world” confronts us all and always has—but Before Nature explores that almost unimaginable time when there was no such conception of “nature”—no word, reference, or sense for it. Before the concept of nature formed over the long history of European philosophy and science, our ancestors in ancient Assyria and Babylonia developed an inquiry into the world in a way that is kindred to our modern science. With Before Nature, Francesca Rochberg explores that Assyro-Babylonian knowledge tradition and shows how it relates to the entire history of science. From a modern, Western perspective, a world not conceived somehow within the framework of physical nature is difficult—if not impossible—to imagine. Yet, as Rochberg lays out, ancient investigations of regularity and irregularity, norms and anomalies clearly established an axis of knowledge between the knower and an intelligible, ordered world. Rochberg is the first scholar to make a case for how exactly we can understand cuneiform knowledge, observation, prediction, and explanation in relation to science—without recourse to later ideas of nature. Systematically examining the whole of Mesopotamian science with a distinctive historical and methodological approach, Before Nature will open up surprising new pathways for studying the history of science.

Comment: For students wondering whether or not "philosophy" was done before Socrates and the Pre-Socratics, this text is a fairly comprehensive overview of how ancient Assyro-Babylonians conceived of "nature," their place within it, studied it, and recorded their findings about it. But, more than anything else, this text also shows that ancient Near Eastern cuneiform texts are not to be ignored by budding scholars of ancient philosophy or historians and philosophers of the sciences and their methodologies. Some prior engagement with ancient Greek philosophy, as well as the history and philosophy of science, will help to understand this text.

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Secco, Gisele Dalva, Pereira, Luiz Carlos. Proofs Versus Experiments: Wittgensteinian Themes Surrounding the Four-Color Theorem
2017, in How Colours Matter to Philosophy, Marcos Silva (ed.). Springer, Cham.
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Added by: Fenner Stanley Tanswell
Abstract: The Four-Colour Theorem (4CT) proof, presented to the mathematical community in a pair of papers by Appel and Haken in the late 1970's, provoked a series of philosophical debates. Many conceptual points of these disputes still require some elucidation. After a brief presentation of the main ideas of Appel and Haken’s procedure for the proof and a reconstruction of Thomas Tymoczko’s argument for the novelty of 4CT’s proof, we shall formulate some questions regarding the connections between the points raised by Tymoczko and some Wittgensteinian topics in the philosophy of mathematics such as the importance of the surveyability as a criterion for distinguishing mathematical proofs from empirical experiments. Our aim is to show that the “characteristic Wittgensteinian invention” (Mühlhölzer 2006) – the strong distinction between proofs and experiments – can shed some light in the conceptual confusions surrounding the Four-Colour Theorem.

Comment (from this Blueprint): Secco and Pereira discuss the famous proof of the Four Colour Theorem, which involved the essential use of a computer to check a huge number of combinations. They look at whether this constitutes a real proof or whether it is more akin to a mathematical experiment, a distinction that they draw from Wittgenstein.

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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
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
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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