For the last forty years, two claims have been at the core of disputes about scientific change: that scientists reason rationally and that science is progressive. For most of this time discussions were polarized between philosophers, who defended traditional Enlightenment ideas about rationality and progress, and sociologists, who espoused relativism and constructivism. Recently, creative new ideas going beyond the polarized positions have come from the history of science, feminist criticism of science, psychology of science, and anthropology of science. Addressing the (...) traditional arguments as well as building on these new ideas, Miriam Solomon constructs a new epistemology of science. After discussions of the nature of empirical success and its relation to truth, Solomon offers a new, social account of scientific rationality. She shows that the pursuit of empirical success and truth can be consistent with both dissent and consensus, and that the distinction between dissent and consensus is of little epistemic significance. In building this social epistemology of science, she shows that scientific communities are not merely the locus of distributed expert knowledge and a resource for criticism but also the site of distributed decision making. Throughout, she illustrates her ideas with case studies from late-nineteenth- and twentieth-century physical and life sciences. Replacing the traditional focus on methods and heuristics to be applied by individual scientists, Solomon emphasizes science funding, administration, and policy. One of her goals is to have a positive influence on scientific decision making through practical social recommendations. (shrink)

Robustness is a common platitude: hypotheses are better supported with evidence generated by multiple techniques that rely on different background assumptions. Robustness has been put to numerous epistemic tasks, including the demarcation of artifacts from real entities, countering the “experimenter’s regress,” and resolving evidential discordance. Despite the frequency of appeals to robustness, the notion itself has received scant critique. Arguments based on robustness can give incorrect conclusions. More worrying is that although robustness may be valuable in ideal evidential circumstances (i.e., (...) when evidence is concordant), often when a variety of evidence is available from multiple techniques, the evidence is discordant. †To contact the author, please write to: Jacob Stegenga, Department of Philosophy, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093; e‐mail: [email protected]. (shrink)

Epistemic diversity is widely approved of by social epistemologists. This paper asks, more specifi cally, how much epistemic diversity, and what kinds of epistemic diversity are normatively appropriate? Both laissez-faire and highly directive approaches to epistemic diversity are rejected in favor of the claim that diversity is a blunt epistemic tool. There are typically a number of diff erent options for adequate diversifi cation. The paper focuses on scientifi c domains, with particular attention to recent theories of smell.

Epistemic diversity is widely approved of by social epistemologists. This paper asks, more specifically, how much epistemic diversity, and what kinds of epistemic diversity are normatively appropriate? Bothlaissez-faireand highly directive approaches to epistemic diversity are rejected in favor of the claim that diversity is a blunt epistemic tool. There are typically a number of different options for adequate diversification. The paper focuses on scientific domains, with particular attention to recent theories of smell.

This essay offers some reflections on the recent history of the disputes about the relation between history and philosophy of science (HPS) and the merits and prospects of HPS as an intellectual endeavor. As everyone knows, the issue was hotly debated in the 1960s and 1970s. That was the hey-day of the slogan "history without philosophy of science is blind, philosophy without history of science is empty" as well as of the many variations on the theme of HPS as a (...) "marriage of convenience," "intimate relation," or "marriage for the sake of reason." There was a flurry of interest in the early 1990s, as evidenced by sections in the 1992 and 1994 issues of PSA, entitled: "Do the History of Science and the Philosophy of .. (shrink)

This article identifies a fundamental distinction in scientific practice: the mismatch between what scientists do and what they state they did when they communicate their findings in their publications. The insight that such a mismatch exists is not new. It was already implied in Hans Reichenbach's distinction between the contexts of discovery and justification, and it is taken for granted across the board in philosophy of science and science studies. But while there is general agreement that the mismatch exists, the (...) epistemological implications of that mismatch are not at all clear. Philosophers, historians, and sociologists of different stripes have expressed widely different views about how one should understand and interpret the relation between what scientists do and what they state they did. This article surveys a number of approaches to the mismatch. Based on this survey, I offer an assessment of the epistemological significance of the mismatch and identify the major meta-epistemological challenges that it poses for the analysis of scientific practice. *Received May 2007; revised April 2008. †To contact the author, please write to: Department of History and Philosophy of Science, 1011 East Third Street, Goodbody Hall 130, Indiana University, Bloomington, IN 47405; e-mail: [email protected]. (shrink)

Economic competitive advantage depends on innovation, which in turn requires pushing back the frontiers of various kinds of knowledge. Although understanding how knowledge grows ought to be a central topic of epistemology, epistemologists and philosophers of science have given it insufficient attention, even deliberately shunning the topic. Traditional confirmation theory and general epistemology offer little help at the frontier, because they are mostly retrospective rather than prospective. Nor have philosophers been highly visible in the science and technology policy realm, despite (...) philosophy’s being a normative discipline. This paper suggests a way to address both deficits. Creative scientists, technologists, business managers, and policy makers face similar problems of decision-making at their respective frontiers of knowledge. These areas should therefore be fertile ground for both epistemologists and philosophers concerned with policy. Here I call attention to the importance of heuristic appraisal for “frontier epistemology” and to policy formation. Evaluation of the comparative promise or expected fertility of available options comprises a cluster of activities that cut across traditional discovery/justification and descriptive/normative distinctions. The study of weak modes of reasoning and evaluation is especially relevant to socio-economic policy. (shrink)

Leplin attempts to reinstate the common sense idea that theoretical knowledge is achievable, indeed that its achievement is part of the means to progress in empirical knowledge. He sketches the genesis of the skeptical position, then introduces his argument for Minimalist Scientific Realism -- the requirement that novel predicitons be explained, and the claim that only realism about scientific theories can explain the importance of novel prediction.

This essay contains a partial exploration of some key concepts associated with the epistemology of realist philosophies of science. It shows that neither reference nor approximate truth will do the explanatory jobs that realists expect of them. Equally, several widely-held realist theses about the nature of inter-theoretic relations and scientific progress are scrutinized and found wanting. Finally, it is argued that the history of science, far from confirming scientific realism, decisively confutes several extant versions of avowedly 'naturalistic' forms of scientific (...) realism. (shrink)

A common method for warranting the historical adequacy of philosophical claims is that of relying on historical case studies. This paper addresses the question as to what evidential support historical case studies can provide to philosophical claims and doctrines. It argues that in order to assess the evidential functions of historical case studies, we first need to understand the methodology involved in producing them. To this end, an account of historical reconstruction that emphasizes the narrative character of historical accounts and (...) the theory-laden character of historical facts is introduced. The main conclusion of this paper is that historical case studies are able to provide philosophical claims with some evidential support, but that, due to theory-ladenness, their evidential import is restricted. (shrink)

Published research findings are sometimes refuted by subsequent evidence, says Ioannidis, with ensuing confusion and disappointment.

The simple question, what is empirical success? turns out to have a surprisingly complicated answer. We need to distinguish between meritorious fit and ‘fudged fit', which is akin to the distinction between prediction and accommodation. The final proposal is that empirical success emerges in a theory dependent way from the agreement of independent measurements of theoretically postulated quantities. Implications for realism and Bayesianism are discussed. ‡This paper was written when I was a visiting fellow at the Center for Philosophy of (...) Science at the University of Pittsburgh; I thank everyone for their support. †To contact the author, please write to: Department of Philosophy, University of Wisconsin–Madison, 5185 Helen C. White Hall, 600 North Park Street, Madison, WI 53706; e-mail: [email protected]. (shrink)

A number of scholars have recently drawn attention to the importance of iteration in scientific research. This paper builds on these previous discussions by drawing a distinction between epistemic and methodological forms of iteration and by clarifying the relationships between them. As defined here, epistemic iteration involves progressive alterations to scientific knowledge claims, whereas methodological iteration refers to an interplay between different modes of research practice. While distinct, these two forms of iteration are related in important ways. Contemporary research on (...) the biological effects of nanomaterials illustrates that methodological iteration can help to “initiate,” “equip,” and “stimulate” epistemic iteration. (shrink)

Against the well-known objection that in the history of science there are many theories that are successful but false, Psillos offers a three-pronged defense of scientific realism as the best explanation for the success of science. Focusing on these, I criticize Psillos’ defense, arguing that each prong is weakened when we recognize that according to realist rebuttals of the underdetermination argument and versions of empiricism, realists are committed to accounting for the explanatory success of theories, not their mere empirical adequacy (...) or instrumental reliability. I conclude by indicating how ‘explanationist’ realism might be recast to accommodate my arguments. (shrink)

The claims of randomized controlled trials to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This article describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. (...) It argues that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The article reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

This paper tells the story of G-protein coupled receptors, one of the most important scientific objects in contemporary biochemistry and molecular biology. By looking at how cell membrane receptors turned from a speculative concept into a central element in modern biochemistry over the past 40 years, we revisit the role of manipulability as a criterion for entity realism in wet-lab research. The central argument is that manipulability as a condition for reality becomes meaningful only once scientists have decided how to (...) conceptually coordinate measurable effects distinctly to a specific object. We show that a scientific entity, such as GPCRs, is assigned varying degrees of reality throughout different stages of its discovery. The criteria of its reality, we further claim, cannot be made independently of the question about how this object becomes a standard by which the reality of neighbouring elements of enquiry is evaluated. (shrink)

Do sensory measurements deserve the label of “measurement”? We argue that they do. They fit with an epistemological view of measurement held in current philosophy of science, and they face the same kinds of epistemological challenges as physical measurements do: the problem of coordination and the problem of standardization. These problems are addressed through the process of “epistemic iteration,” for all measurements. We also argue for distinguishing the problem of standardization from the problem of coordination. To exemplify our claims, we (...) draw on olfactory performance tests, especially studies linking olfactory decline to neurodegenerative disorders. (shrink)

What does it take for a scientific model to represent? Scientific models have received a great deal of attention in recent philosophical literature. Following Morgan and Morrison’s account of “Models as Mediators”, analysis of how models represent has changed from questioning what properties of models can be said to correlate with the world to asking how models are used to relate to an intended target-system. This turn to a practice-oriented approach of understanding models was a response to a general philosophical (...) problem that attends the empirical application of scientific representations such as models. This problem is twofold. Models, on the one hand, are often said to make false claims about the world.. (shrink)

ISBN-13: 978-0-226-11360-9 (cloth : alk. paper) ISBN-10: 0-226-11360-4 ... HM651.C64 2007 158.1—dc22 2007022671 The paper used in this publication meets the minimum requirements of the American National Standard for Information ...

Machine generated contents note: -- Chapter 1. A Short View of Ignorance -- Chapter 2. Finding Out -- Chapter 3. Limits, Uncertainty, Impossibility, and Other Minor Problems -- Chapter 4. Unpredicting -- Chapter 5. The Quality of Ignorance -- Chapter 6. Ignorance in Action: Case Histories -- Chapter 7. Ignorance beyond the Lab.

This book presents the concept of “complementary science” which contributes to scientific knowledge through historical and philosophical investigations. It emphasizes the fact that many simple items of knowledge that we take for granted were actually spectacular achievements obtained only after a great deal of innovative thinking, painstaking experiments, bold conjectures, and serious controversies. Each chapter in the book consists of two parts: a narrative part that states the philosophical puzzle and gives a problem-centred narrative on the historical attempts to solve (...) the puzzle; and the analysis part which provides in-depth analyses of certain scientific, historical, and philosophical aspects of the story. (shrink)

This book offers a philosophy for error-prone humans trying to understand messy systems in the real world.

Do the sciences aim to uncover the structure of nature, or are they ultimately a practical means of controlling our environment? In Instrumental Biology, or the Disunity of Science, Alexander Rosenberg argues that while physics and chemistry can develop laws that reveal the structure of natural phenomena, biology is fated to be a practical, instrumental discipline. Because of the complexity produced by natural selection, and because of the limits on human cognition, scientists are prevented from uncovering the basic structure of (...) biological phenomena. Consequently, biology and all of the disciplines that rest upon it--psychology and the other human sciences--must aim at most to provide practical tools for coping with the natural world rather than a complete theoretical understanding of it. (shrink)

Scientific Realism is the optimistic view that modern science is on the right track: that the world really is the way our best scientific theories describe it to be. In his book, Stathis Psillos gives us a detailed and comprehensive study, which restores the intuitive plausibility of scientific realism. We see that throughout the twentieth century, scientific realism has been challenged by philosophical positions from all angles: from reductive empiricism, to instrumentalism and modern skeptical empiricism. Scientific Realism explains that the (...) history of science does not undermine the notion of scientific realism, and instead makes it reasonable to accept scientific as the best philosophical account of science, its empirical success, its progress and its practice. Anyone wishing to gain a deeper understanding of the state of modern science and why scientific realism is plausible, should read this book. (shrink)

The claims of RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This paper describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. It argues (...) that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The paper reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

The claims of RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This paper describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. It argues (...) that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The paper reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

Neurobiology studies mechanisms of cell signalling. A key question is how cells recognise specific signals. In this context, olfaction has become an important experimental system over the past 25 years. The olfactory system responds to an array of structurally diverse stimuli. The discovery of the olfactory receptors (ORs), recognising these stimuli, established the olfactory pathway as part of a greater group of signalling mechanisms mediated by G-protein-coupled receptors (GPCRs). GPCRs are the largest protein family in the mammalian genome and involved (...) in numerous fundamental physiological processes. The OR family exhibits two characteristics that make them an excellent model system to understand GPCRs: its size and the structural diversity of its members. Research on the OR binding site investigates what amino acid sequences determine the receptor-binding capacity. This promises a better understanding of how the basic genetic makeup of GPCRs relates to their diversification in ligand-binding capacities. (shrink)