Success-to-truth inferences have been the realist stronghold for a long time. Scientific success is the parameter by which realists claim to discern approximately true theories from false ones. But scientific success needs to be probed a bit deeper. In this article, I tell three tales of scientific success, by considering in turn success from nowhere, success from here now, and success from within. I argue for a suitable version of (...) class='Hi'>success from within that can do justice to the historically situated nature of our scientific knowledge. The outcome is a new way of thinking about success-to-truth inferences along perspectivalist lines. (shrink)

Several metaphysical naturalists argue that the success of science, together with the claim that scientists adhere to methodological naturalism, amounts to strong evidence for metaphysical naturalism. I call this the scientific-success argument. It is argued that the scientific-success argument is similar to the no-miracles argument for realism in philosophy of science. On the no-miracles argument, the success of science is taken as strong evidence that scientific theories are true. Based on this similarity, some (...) considerations relevant to one argument may also be relevant to the other. One particular consideration is explored. The selectionist response to the no-miracles argument states that on an evolutionary model of science, in which scientific theories are accepted only after surviving a rigorous selection process, the no-miracles argument fails. The selectionist response also applies to the scientific-success argument. If scientific theories are selected for success, we do not need to explain the success of science by appealing to metaphysical naturalism. (shrink)

Two decades of critique have sensitized historians and philosophers of science to the inadequacies of conventional dichotomies between theory and practice, thereby prompting the search for new ways of writing about science that are less beholden than the old ways to the epistemological mores of theoretical physics, and more faithful to the actual practices not only of physics but of all the natural sciences. The need for alternative descriptions seems particularly urgent if one is to understand the place of theory (...) in contemporary molecular biology, a science where, until now, no division between theory and experiment has obtained, and where distinctions between representing and intervening, and more generally, between basic and applied science, are daily becoming more blurred.Indeed, the very division between theory and experiment threatens to slight the extensive and sophisticated theoretical analyses on which experimental work in contemporary molecular biology so often depends. My aim in this paper is to find a way of talking about theoretical practices in biology that is directly rooted in the mix of conceptual and material work that biologists do. As an example of such theoretical practices, I choose for the focus of my analysis the development of a model for gene regulation out of the experimental work of Eric Davidson and his colleagues at Cal Tech. (shrink)

The COVID-19 vaccine has been a miraculous, life-saving advance, offering staggering efficacy in adults, and was developed with astonishing speed. The time from sequencing the virus to authorizing the first COVID-19 vaccine was so brisk even the optimists appear close-minded. Yet, simultaneously, United States’ COVID-19 vaccination roll-out and related policies have contained missed opportunities, errors, run counter to evidence-based medicine, and revealed limitations in the judgment of public policymakers. Misplaced utilization, contradictory messaging, and poor deployment in those who would benefit (...) most—the elderly and high-risk—alongside unrealistic messaging, exaggeration, and coercion in those who benefit least—young, healthy Americans—is at the heart. It is important to consider the history of COVID-19 vaccines to identify where we succeeded and where we failed, and the effects that these errors may have more broadly on vaccination hesitancy and routine childhood immunization programs in the decades to come. (shrink)

Empirically successful scientific theories are intellectual hurricanes. They flood lowlands set aside for worries about definitions. They carry away philosophical reflections that are less dense than the accumulated scientific findings that give these storms their strength, and they fundamentally reshape the conceptual landscape. The history of scholarship reveals that once an empirically corroborated scientific theory explains and predicts phenomena in some domain noticeably better than the available alternatives (whether those alternatives are scientific theories or not), among (...) experts at least, the process of conceptualizing those phenomena, thereafter, mostly floats along on the surface of debates about the comparative scientific merits of that theory and its competitors. Earlier debates about definitions lose most of their interest until new theories arise that generate new, less easily managed empirical findings in the pertinent domains. Across the centuries, the fates of such concepts as ‘inertia’ and ‘planet’ are fitting illustrations of these patterns, as are, more recently, the fates of such concepts as ‘gene’ and ‘deciding’ (aka “decision making”). (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)

Research on the media representations of nanotechnology have flourished during the last decennium. However, most of the projects were focused on Western Europe and North America, especially the English speaking countries. This paper aims to move the focus towards Poland - a Central European country that has not been studied in this context before. This study looks at the frames, themes and tone used in the Polish coverage of nanotechnology between 2004 and 2009. Other issues, such as main actors in (...) the debate or articles’ geographical focus have also been considered. (shrink)

A scientific community can be modeled as a collection of epistemic agents attempting to answer questions, in part by communicating about their hypotheses and results. We can treat the pathways of scientific communication as a network. When we do, it becomes clear that the interaction between the structure of the network and the nature of the question under investigation affects epistemic desiderata, including accuracy and speed to community consensus. Here we build on previous work, both our own and (...) others’, in order to get a firmer grasp on precisely which features of scientific communities interact with which features of scientific questions in order to influence epistemic outcomes. (shrink)

In this way Dilworth succeeds in providing a conception of science in which scientific progress is based on both rational and empirical considerations.

In this essay, I critically evaluate the approaches to explaining the success of science in Kuhn and the works of inference-to-the-best-explanation scientific realists. Kuhn ’s challenge to realists, who invoke the truth of theories to explain their success, is two-fold. His paradigm-account of success confronts realists with the problem of theory change, and the historical fact of successful theories later rejected as false. Secondly, Kuhn ’s account of the success of science has no need to (...) bring truth into the explanation. In turn, I argue that weakness in Kuhn and the prevailing forms of scientific realism motivate a better account of realism which I characterize as ‘best current theory realism’ and defend against the pessimistic meta-induction and the problem of theory-change. This realism argues that the best explanation of the success of current and past scientific theories only requires the simple claim that our best current theories are true. Kuhn ’s account can explain how normal science succeeds but cannot account for why its problem solutions work where they do and why they fail for other puzzles. (shrink)

Selective scientific realists disagree on which theoretical posits should be regarded as essential to the empirical success of a scientific theory. A satisfactory account of essentialness will show that the (approximate) truth of the selected posits adequately explains the success of the theory. Therefore, (a) the essential elements must be discernible prospectively; (b) there cannot be a priori criteria regarding which type of posit is essential; and (c) the overall success of a theory, or ‘cluster’ (...) of propositions, not only individual derivations, should be explicable. Given these desiderata, I propose a “unification criterion” for identifying essential elements. (shrink)

Scientific realists have claimed that the posit that our theories are (approximately) true provides the best or the only explanation for their success . In response, I revive two non-realists explanations. I show that realists, in discarding them, have either misconstrued the phenomena to be explained or mischaracterized the relationship between these explanations and their own. I contend nonetheless that these non-realist competitors, as well as their realist counterparts, should be rejected; for none of them succeed in explaining (...) a significant list of successes. I propose a related non-realist explanation of success that appears to be the most suitable among those considered. (shrink)

Scientists often diverge widely when choosing between research programs. This can seem to be rooted in disagreements about which of several theories, competing to address shared questions or phenomena, is currently the most epistemically or explanatorily valuable—i.e. most successful. But many such cases are actually more directly rooted in differing judgments of pursuit-worthiness, concerning which theory will be best down the line, or which addresses the most significant data or questions. Using case studies from 16th-century astronomy and 20th-century geology and (...) biology, I argue that divergent theory choice is thus often driven by considerations of scientific process, even where direct epistemic or explanatory evaluation of its final products appears more relevant. Broadly following Kuhn’s analysis of theoretical virtues, I suggest that widely shared criteria for pursuit-worthiness function as imprecise, mutually-conflicting values. However, even Kuhn and others sensitive to pragmatic dimensions of theory ‘acceptance’, including the virtue of fruitfulness, still commonly understate the role of pursuit-worthiness—especially by exaggerating the impact of more present-oriented virtues, or failing to stress how ‘competing’ theories excel at addressing different questions or data. This framework clarifies the nature of the choice and competition involved in theory choice, and the role of alternative theoretical virtues. (shrink)

In this paper, I argue for a distinction between two scales of coordination in scientific inquiry, through which I reassess Georg Simon Ohm’s work on conductivity and resistance. Firstly, I propose to distinguish between measurement coordination, which refers to the specific problem of how to justify the attribution of values to a quantity by using a certain measurement procedure, and general coordination, which refers to the broader issue of justifying the representation of an empirical regularity by means of abstract (...) mathematical tools. Secondly, I argue that the development of Ohm’s measurement practice between the first and the second experimental phase of his work involved the change of the measurement coordination on which he relied to express his empirical results. By showing how Ohm relied on different calibration assumptions and practices across the two phases, I demonstrate that the concurrent change of both Ohm’s experimental apparatus and the variable that Ohm measured should be viewed based on the different form of measurement coordination. Finally, I argue that Ohm’s assumption that tension is equally distributed in the circuit is best understood as part of the general coordination between Ohm’s law and the empirical regularity that it expresses, rather than measurement coordination. (shrink)

A success-to-truth inference has always been at the heart of scientific realist positions. But all attempts to articulate the inference have met with very significant challenges. This paper reconstructs the evolution of this inference, and brings together a number of qualifications in an attempt to articulate a contemporary success-to-truth inference which is realistic. I argue that this contemporary version of the inference has a chance, at least, of overcoming the historical challenges which have been proffered to date. (...) However, there is a price to pay: the developments which help the realist answer the historical challenges also serve to increase the number of non-historical challenges. (shrink)

review and discussion of: John Wright: Explaining science’s success: Understanding how scientific knowledge works. Durham: Acumen, 2012.

Making sense of why something succeeded or failed is central to scientific practice: it provides an interpretation of what happened, i.e. an hypothesized explanation for the results, that informs scientists’ deliberations over their next steps. In philosophy, the realism debate has dominated the project of making sense of scientists’ success and failure claims, restricting its focus to whether truth or reliability best explain science’s most secure successes. Our aim, in contrast, will be to expand and advance the practice-oriented (...) project sketched by Arthur Fine in his work on the Natural Ontological Attitude. An important obstacle to articulating a positive program, we suggest, has been overlooking how scientists adopt standardized rules and procedures in order to define and operationalize meanings for success and failure relative to their situated goals. To help fill this gap, we introduce two new ideas, design specifications and track records, and show how they advance our ability to make sense of scientific modeling practices while maintaining a deflationary stance toward the realism debate. (shrink)

According to the no miracles argument, scientific realism provides the only satisfactory explanation of the predictive success of science. It is argued in the present article that a different explanatory strategy, based on the posit of limitations to the underdetermination of scientific theory building by the available empirical data, offers a more convincing understanding of scientific success.

Paul Feyeraband famously asked, what's so great about science? One answer is that it has been surprisingly successful in getting things right about the natural world, more successful than non-scientific or pre-scientific systems, religion or philosophy. Science has been able to formulate theories that have successfully predicted novel observations. It has produced theories about parts of reality that were not observable or accessible at the time those theories were first advanced, but the claims about those inaccessible areas have (...) since turned out to be true. And science has, on occasion, advanced on more or less a priori grounds theories that subsequently turned out to be highly empirically successful. In this book the philosopher of science, John Wright delves deep into science's methodology to offer an explanation for this remarkable success story. (shrink)

This is a book review of Wright's Explaining Science's Success.

Isaac Newton's Scientific Method examines Newton's argument for universal gravity and his application of it to resolve the problem of deciding between geocentric and heliocentric world systems by measuring masses of the sun and planets. William L. Harper suggests that Newton's inferences from phenomena realize an ideal of empirical success that is richer than prediction. Any theory that can achieve this rich sort of empirical success must not only be able to predict the phenomena it purports to (...) explain, but also have those phenomena accurately measure the parameters which explain them. Harper explores the ways in which Newton's method aims to turn theoretical questions into ones which can be answered empirically by measurement from phenomena, and to establish that propositions inferred from phenomena are provisionally accepted as guides to further research. This methodology, guided by its rich ideal of empirical success, supports a conception of scientific progress that does not require construing it as progress toward Laplace's ideal limit of a final theory of everything, and is not threatened by the classic argument against convergent realism. Newton's method endorses the radical theoretical transformation from his theory to Einstein's. Harper argues that it is strikingly realized in the development and application of testing frameworks for relativistic theories of gravity, and very much at work in cosmology today. (shrink)

Broadly speaking, the contemporary scientific realist is concerned to justify belief in what we might call theoretical truth, which includes truth based on ampliative inference and truth about unobservables. Many, if not most, contemporary realists say scientific realism should be treated as ‘an overarching scientific hypothesis’ (Putnam 1978, p. 18). In its most basic form, the realist hypothesis states that theories enjoying general predictive success are true. This hypothesis becomes a hypothesis to be tested. To justify (...) our belief in the realist hypothesis, realists commonly put forward an argument known as the ‘no-miracles argument’. With respect to the basic hypothesis this argument can be stated as follows: it would be a miracle were our theories as successful as they are, were they not true; the only possible explanation for the general predictive success of our scientific theories is that they are true. (shrink)

Historical sciences like paleontology and archaeology have uncovered unimagined, remarkable and mysterious worlds in the deep past. How should we understand the success of these sciences? What is the relationship between knowledge and history? In Scientific Knowledge and the Deep Past: History Matters, Adrian Currie examines recent paleontological work on the great changes that occurred during the Cretaceous period - the emergence of flowering plants, the splitting of the mega-continent Gondwana, and the eventual fall of the dinosaurs - (...) to analyse the knowledge of historical scientists, and to reflect upon the nature of history. He argues that distinctively historical processes are 'peculiar': they have the capacity to generate their own highly specific dynamics and rules. This peculiarity, Currie argues, also explains the historian's interest in narratives and stories: the contingency, complexity and peculiarity of the past demands a narrative treatment. Overall, Currie argues that history matters for knowledge. (shrink)

A central component to scientific practice is the construction and use of scientific models. Scientists believe that the success of a model justifies making claims that go beyond the model itself. However, philosophical analysis of models suggests that drawing inferences about the world from successful models is more complex. In this dissertation I develop a framework that can help disentangle the related strands of evaluation of model success, model extendibility, and the ability to draw ampliative inferences (...) about the world from models. I present and critically assess two leading accounts of model assessment, arguing that neither is sufficient to provide a complete understanding of model evaluation. I introduce a more powerful framework incorporating elements of the two views, which can help answer these three questions: What is the target of evaluation in model assessment? How does that evaluation proceed? What licenses us in making inferences about the real world, based on the evaluation of our models as successful? The framework identifies two distinct targets of model evaluation: representational similarity between the model and target system, and the adequacy of the model as a tool to answer questions. Both assessments must be relativized to a purpose, of which there are three general kinds: descriptive, predictive, and explanatory. These purposes differ in the way they inform the similarity relation, which is relevant for the similarity assessment, and the output they produce, which is relevant for the adequacy assessment. Any model can be assessed relative to any purpose, however a model encodes certain decisions made during the model’s construction, which impact its ability to be applied to a new purpose or new domain. My framework shows that extending a model, and drawing inferences from it, depends on its representational similarity. I apply this framework to several examples taken from astrophysics showing in detail how it can help illuminate the structure of the models, as well as make the justification for inferences made from them clear. The final chapter is a detailed analysis of a contemporary debate surrounding the use of models in astrophysics, between proponents of MOND and the standard ΛCDM model. (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. 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 to modern sceptical empiricism. _Scientific Realism_ (...) explains that the history of science does not undermine the arguments for scientific realism, but instead makes it reasonable to accept scientific realism 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)

I argue against theories that attempt to reduce scientific representation to similarity or isomorphism. These reductive theories aim to radically naturalize the notion of representation, since they treat scientist's purposes and intentions as non-essential to representation. I distinguish between the means and the constituents of representation, and I argue that similarity and isomorphism are common but not universal means of representation. I then present four other arguments to show that similarity and isomorphism are not the constituents of scientific (...) representation. I finish by looking at the prospects for weakened versions of these theories, and I argue that only those that abandon the aim to radically naturalize scientific representation are likely to be successful. (shrink)

Successful Ageing A Survey of the Most Important Theories The issues of good and successful ageing are the subject of scientific research. Successful ageing is the attempt to achieve a state of inner satisfaction and happiness in spite of the negative effects associated with old age: loss, external and internal destabilization, etc. Successful development in old age has many forms. It can generally be defined as an attempt to achieve the greatest profit with the smallest loss. The problem is (...) establishing the universal criteria of successful ageing. It is possible to restrict the study to the observation of individual factors which are either objective or subjective, long-term or short-term, specific or universal or static versus dynamic. The problem is creating a theory that will explain all the processes and consequences of old age—none of the theories has so far succeeded in doing this. Life satisfaction as a subjective criterion of successful ageing has been most emphasized in two contradictory theories: activity theory and disengagement theory. Other theories are: growth theories, cognitive theories, dynamic theories, SOC model, cultural anthropological theories, the interaction model of longevity, etc. (shrink)

Scientific realism, the position that successful theories are likely to be approximately true, is threatened by the pessimistic induction according to which the history of science is full of suc- cessful, but false theories. I aim to defend scientific realism against the pessimistic induction. My main thesis is that our current best theories each enjoy a very high degree of predictive success, far higher than was enjoyed by any of the refuted theories. I support this thesis by (...) showing that both the amount, and quality, of scientific evidence has increased enormously in the recent past, resulting in a big boost of success for the best theories. (shrink)

In this paper, I propose that the debate in epistemology concerning the nature and value of understanding can shed light on the role of scientific idealizations in producing scientific understanding. In philosophy of science, the received view seems to be that understanding is a species of knowledge. On this view, understanding is factive just as knowledge is, i.e., if S knows that p, then p is true. Epistemologists, however, distinguish between different kinds of understanding. Among epistemologists, there are (...) those who think that a certain kind of understanding—objectual understanding—is not factive, and those who think that objectual understanding is quasi-factive. Those who think that understanding is not factive argue that scientific idealizations constitute cognitive success, which we then consider as instances of understanding, and yet they are not true. This paper is an attempt to draw lessons from this debate as they pertain to the role of idealizations in producing scientific understanding. I argue that scientific understanding is quasi-factive. (shrink)

Recent metaphysics of science has been fuelled significantly by an interest in causal powers or dispositions. A number of authors have made realism about dispositions central to their projects in the epistemology of science, suggesting that the existence of irreducible powers is a commitment entailed by taking scientific practice seriously. This paper strikes a cautionary note with respect to the two most common arguments for this view, concerning the putative requirement of dispositional properties in the contexts of scientific (...) explanation and scientific abstraction. I contend that neither argument is successful, but that nevertheless, realism about powers better accords with an arguably scientific consideration of property identity, thus affirming the importance of dispositions to the epistemology of science. (shrink)

An argument that what makes science distinctive is its emphasis on evidence and scientists' willingness to change theories on the basis of new evidence. Attacks on science have become commonplace. Claims that climate change isn't settled science, that evolution is “only a theory,” and that scientists are conspiring to keep the truth about vaccines from the public are staples of some politicians' rhetorical repertoire. Defenders of science often point to its discoveries (penicillin! relativity!) without explaining exactly why scientific claims (...) are superior. In this book, Lee McIntyre argues that what distinguishes science from its rivals is what he calls “the scientific attitude”—caring about evidence and being willing to change theories on the basis of new evidence. The history of science is littered with theories that were scientific but turned out to be wrong; the scientific attitude reveals why even a failed theory can help us to understand what is special about science. McIntyre offers examples that illustrate both scientific success (a reduction in childbed fever in the nineteenth century) and failure (the flawed “discovery” of cold fusion in the twentieth century). He describes the transformation of medicine from a practice based largely on hunches into a science based on evidence; considers scientific fraud; examines the positions of ideology-driven denialists, pseudoscientists, and “skeptics” who reject scientific findings; and argues that social science, no less than natural science, should embrace the scientific attitude. McIntyre argues that the scientific attitude—the grounding of science in evidence—offers a uniquely powerful tool in the defense of science. (shrink)

The main aim of this paper is to disentangle three senses in which we can say that a model represents a system—denotation epistemic representation, and successful epistemic representation--and to individuate what questions arise from each sense of the notion of representation as used in this context. Also, I argue that a model is an epistemic representation of a system only if a user adopts a general interpretation of the model in terms of a system. In the process, I hope to (...) clarify where those who, following Craig Callander and Jonathan Cohen, claim that there is no special problem about scientific representation go wrong. In the terminology adopted here, even if scientific representation is only an instance of epistemic representation, scientific representation should not be confounded with denotation. (shrink)

In this book K. Brad Wray provides a comprehensive survey of the arguments against scientific realism. In addition to presenting logical considerations that undermine the realists' inferences to the likely truth or approximate truth of our theories, he provides a thorough assessment of the evidence from the history of science. He also examines grounds for a defence of anti-realism, including an anti-realist explanation for the success of our current theories, an account of why false theories can be empirically (...) successful, and an explanation for why we should expect radical changes of theory in the future. His arguments are supported and illustrated by cases from the history of science, including a sustained study of the Copernican Revolution, and a study of the revolution in early twentieth century chemistry, when chemists came to classify elements by their atomic number rather than by their atomic weight. (shrink)

Assuming for the sake of discussion that there is an external world, The "core" thesis of scientific realism is that some of our empirical beliefs (including the so-Called theoretical beliefs) succeed in correctly describing, In some important measure, The external world. Classical scientific realism also asserts that we are able to say justifiably just "which" of our beliefs so succeed in correctly describing the external world. This paper does not examine this last claim. Rather it seeks to defend (...) the core thesis of scientific realism and will assume (for reasons of limited space) the existence of an external world. In defending the core thesis, This paper returns to and defends the explanationist defense which asserts that the core thesis offers the best available explanation for the long-Term predictive success of "some" empirical or scientific hypotheses. The defense consists in examining and rejecting all available alternative explanations as well as all objections to the explanationist defense as offered in this paper. (shrink)

The theory of concepts advanced in the present discussion aims at accounting for a) how a concept makes successful practice possible, and b) how a scientific concept can be subject to rational change in the course of history. To this end, I suggest that each scientific concept consists of three components of content: 1) the concept.

The Higgs model was developed using purely formal analogies to models of superconductivity. This is in contrast to historical case studies such as the development of electromagnetism, which employed physical analogies. As a result, quantum case studies such as the development of the Higgs model carry new lessons for the scientific realism--anti-realism debate. I argue that, by breaking the connection between success and approximate truth, the use of purely formal analogies is a counterexample to two prominent versions of (...) the 'No Miracles' Argument for scientific realism, Psillos' refined explanationist defence of realism and the Argument from History of Science for structural realism. The NMA is undermined, but the success of the Higgs model is not miraculous because there is a naturalistically acceptable explanation for its success that does not invoke approximate truth. I also suggest some possible strategies for adapting to the counterexample for scientific realists who wish to hold on to the NMA in some form. (shrink)

In its original form due to Ian Hacking, entity realism postulates a criterion of manipulative success which replaces explanatory virtue as the criterion of justified scientific belief. The article analyses the foundations on which this postulate rests and identifies the conditions on which one can derive a form of entity realism from it. It then develops in detail an extensive class of counterexamples, drawing on the notion of quasi-particles in condensed matter physics. While the phenomena associated with quasi-particles (...) pass the entity realist's criterion of manipulative success, quasi-particles themselves are illusions, and can be seen to be so even on the basis of the largely non-theoretical "home truths" that one must be ready to admit as background knowledge. Hence, Hacking's entity realism is shown to be incoherent. (shrink)