Because Francis Galton (1822-1911) was a well-connected gentleman scientist with substantial private means, the importance of the role he played in the professionalization of the Victorian life-sciences has been considered anomalous. In contrast to the X-clubbers, he did not seem to have any personal need for the reforms his Darwinist colleagues were advocating. Nor for making common cause with individuals haling from social strata clearly inferior to his own. However, in this paper I argue that Galton quite realistically discerned in (...) the reforming endeavors of the 1860s, and beyond, the potential for considerably enhancing his own reputation and standing within both the scientific community and the broader Victorian culture. In addition, his professionalizing aspirations, and those of his reformist allies, were fully concordant with the interests, ambitions and perceived opportunities of his elite social group during the Victorian period. Professionalization appealed to gentlemen of Galton's status and financial security as much as it did to the likes of Thomas Huxley and John Tyndall, primarily because it promised to confer on the whole scientific enterprise an unprecedented level of social prestige. (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)
Discussions over whether these natural kinds exist, what is the nature of their existence, and whether natural kinds are themselves natural kinds aim to not only characterize the kinds of things that exist in the world, but also what can knowledge of these categories provide. Although philosophically critical, much of the past discussions of natural kinds have often answered these questions in a way that is unresponsive to, or has actively avoided, discussions of the empirical use of natural kinds and (...) what I dub “activities of natural kinding” and “natural kinding practices”. The natural kinds of a particular discipline are those entities, events, mechanisms, processes, relationships, and concepts that delimit investigation within it—but we might reasonably ask: How are these natural kinds discovered?, How are they made?, Are they revisable?, and Where do they come from? A turn to natural kinding practices reveals a new set of questions open for investigation: How do natural kinds explain through practice?, What are natural kinding practices and classifications and why should we care?, What is the nature of natural kinds viewed as a set of activities?, and How do practice approaches to natural kinds shape and reconfigure scientific disciplines? -/- Natural kinds have traditionally been discussed in terms of how they classify the contents of the world. The metaphysical project has been one which identifies essences, laws, sameness relations, fundamental properties, and clusters of family resemblances and how these map out the ontological space of the world. But actually how this is done has been less important in the discussion than the resultant categories that are produced. I aim to rectify these omissions and suggest a new metaphysical project investigating kinds in practice. (shrink)
According to the semantic view of scientific theories, theories are classes of models. I show that this view -- if taken seriously as a formal explication -- leads to absurdities. In particular, this view equates theories that are truly distinct, and it distinguishes theories that are truly equivalent. Furthermore, the semantic view lacks the resources to explicate interesting theoretical relations, such as embeddability of one theory into another. The untenability of the semantic view -- as currently formulated -- threatens (...) to undermine scientific structuralism. (shrink)
Scientific realism is the view that our best scientific theories can be regarded as (approximately) true. This is connected with the view that science, physics in particular, and metaphysics could (and should) inform one another: on the one hand, science tells us what the world is like, and on the other hand, metaphysical principles allow us to select between the various possible theories which are underdetermined by the data. Nonetheless, quantum mechanics has always been regarded as, at best, (...) puzzling, if not contradictory. As such, it has been considered for a long time at odds with scientific realism, and thus a naturalized quantum metaphysics was deemed impossible. Luckily, now we have many quantum theories compatible with a realist interpretation. However, scientific realists assumed that the wave-function, regarded as the principal ingredient of quantum theories, had to represent a physical entity, and because of this they struggled with quantum superpositions. In this paper I discuss a particular approach which makes quantum mechanics compatible with scientific realism without doing that. In this approach, the wave-function does not represent matter which is instead represented by some spatio-temporal entity dubbed the primitive ontology: point-particles, continuous matter fields, space-time events. I argue how within this framework one develops a distinctive theory-construction schema, which allows to perform a more informed theory evaluation by analyzing the various ingredients of the approach and their inter-relations. (shrink)
Just before the Scientific Revolution, there was a "Mathematical Revolution", heavily based on geometrical and machine diagrams. The "faculty of imagination" (now called scientific visualization) was developed to allow 3D understanding of planetary motion, human anatomy and the workings of machines. 1543 saw the publication of the heavily geometrical work of Copernicus and Vesalius, as well as the first Italian translation of Euclid.
In this chapter, I argue that scientific practice in the neurosciences of cognition is not conducive to the discovery of natural kinds of cognitive capacities. The “neurosciences of cognition” include cognitive neuroscience and cognitive neurobiology, two research areas that aim to understand how the brain gives rise to cognition and behavior. Some philosophers of neuroscience have claimed that explanatory progress in these research areas ultimately will result in the discovery of the underlying mechanisms of cognitive capacities. Once such mechanistic (...) understanding is achieved, cognitive capacities purportedly will be relegated into natural kind categories that correspond to real divisions in the causal structure of the world. I provide reasons here, however, in support of the claim that the neurosciences of cognition currently are not on a trajectory for discovering natural kinds. As I explain, this has to do with how mechanistic explanations of cognitive capacities are developed. Mechanistic explanations and the kinds they explain are abstract representational byproducts of the conceptual, experimental and integrative practices of neuroscientists. If these practices are not coordinated towards developing mechanistic explanations that mirror the causal structure of the world, then natural kinds of cognitive capacities will not be discovered. I provide reasons to think that such coordination is currently lacking in the neurosciences of cognition and indicate where changes in these practices appropriate to the natural kinds ideal would be required if achieving this ideal is indeed the goal. However, I suggest that an evaluation of current practices in these research areas is suggestive that discovering natural kinds of cognitive capacities is not the goal. (shrink)
In this paper, I explore the purported conflict between science and common sense within the context of scientific realism. I argue for a version of scientific realism which retains commitment to realism about common sense rather than seeking to eliminate it.
According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of (...)scientific explanation. In C. G. Hempel (Ed.), Aspects of scientific explanation (pp. 331–496). New York: Free Press; Kitcher (1989); Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25). My concern is with the minimal suggestion that an adequate philosophical theory of scientific explanation can limit its attention to the format or structure with which theories are represented. The representational subsumption view is a plausible hypothesis about the psychology of understanding. It is also a plausible claim about how scientists present their knowledge to the world. However, one cannot address the central questions for a philosophical theory of scientific explanation without turning one’s attention from the structure of representations to the basic commitments about the worldly structures that plausibly count as explanatory. A philosophical theory of scientific explanation should achieve two goals. The first is explanatory demarcation. It should show how explanation relates with other scientific achievements, such as control, description, measurement, prediction, and taxonomy. The second is explanatory normativity. It should say when putative explanations succeed and fail. One cannot achieve these goals without undertaking commitments about the kinds of ontic structures that plausibly count as explanatory. Representations convey explanatory information about a phenomenon when and only when they describe the ontic explanations for those phenomena. (shrink)
Richard Boyd’s Homeostatic Property Cluster Theory is becoming the received view of natural kinds in the philosophy of science. However, a problem with HPC Theory is that it neglects many kinds highlighted by scientific classifications while at the same time endorsing kinds rejected by science. In other words, there is a mismatch between HPC kinds and the kinds of science. An adequate account of natural kinds should accurately track the classifications of successful science. We offer an alternative account of (...) natural kinds that better recognizes the diversity of epistemic aims scientists have for constructing classifications. That account introduces the idea of a classificatory program and provides criteria for judging whether a classificatory program identifies natural kinds. (shrink)
I argue for an intentional conception of representation in science that requires bringing scientific agents and their intentions into the picture. So the formula is: Agents (1) intend; (2) to use model, M; (3) to represent a part of the world, W; (4) for some purpose, P. This conception legitimates using similarity as the basic relationship between models and the world. Moreover, since just about anything can be used to represent anything else, there can be no unified ontology of (...) models. This whole approach is further supported by a brief exposition of some recent work in cognitive, or usage-based, linguistics. Finally, with all the above as background, I criticize the recently much discussed idea that claims involving scientific models are really fictions. (shrink)
This Target paper is about the hard problem of phenomenal consciousness (i.e., how is subjective experience possible given the scientific presumption that everything from molecules to minerals to minds is wholly physical?). I first argue that one of the most valuable tools in the scientific arsenal (metaphor) cannot be recruited to address the hard problem due to the inability to forge connections between the stubborn fact of subjective experience and physically grounded models of scientific explanation. I then (...) argue that adherence to the physicalist tenets of contemporary science has a limiting effect on a full appreciation of the phenomenon under discussion. (shrink)
Stanford, in Exceeding Our Grasp , presents a powerful version of the pessimistic meta-induction. He claims that theories typically have empirically inequivalent but nonetheless well-confirmed, serious alternatives which are unconceived. This claim should be uncontroversial. But it alone is no threat to scientific realism. The threat comes from Stanford’s further crucial claim, supported by historical examples, that a theory’s unconceived alternatives are “radically distinct” from it; there is no “continuity”. A standard realist reply to the meta-induction is that past (...) failures do not imply present ones because present theories are more successful than past ones. I have preferred to emphasize that present methodology is better than past ones. Stanford’s response to the standard reply is surprisingly brief and inadequate. He defends the inference from the uncontroversial claim but not that from the crucial one. He does not show that past discontinuity implies present discontinuity. Realism survives. (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)
An essay that weighs the main factors that lead authors of academic and scientific books to consider conventional publication of their work, with realistic and practical recommendations for these authors so they may avoid the contractual “imprisonment” of their books after the period of initial active sales has passed.
Western philosophers have traditionally concentrated on theory as the means for expressing knowledge about a variety of phenomena. This absorbing book challenges this fundamental notion by showing how objects themselves, specifically scientific instruments, can express knowledge. As he considers numerous intriguing examples, Davis Baird gives us the tools to "read" the material products of science and technology and to understand their place in culture. Making a provocative and original challenge to our conception of knowledge itself, _Thing Knowledge _demands that (...) we take a new look at theories of science and technology, knowledge, progress, and change. Baird considers a wide range of instruments, including Faraday's first electric motor, eighteenth-century mechanical models of the solar system, the cyclotron, various instruments developed by analytical chemists between 1930 and 1960, spectrometers, and more. (shrink)
The aim of this paper is to revisit the phlogiston theory to see what can be learned from it about the relationship between scientific realism, approximate truth and successful reference. It is argued that phlogiston theory did to some extent correctly describe the causal or nomological structure of the world, and that some of its central terms can be regarded as referring. However, it is concluded that the issue of whether or not theoretical terms successfully refer is not the (...) key to formulating the appropriate form of scientific realism in response to arguments from theory change, and that the case of phlogiston theory is shown to be readily accommodated by ontic structural realism. (shrink)
In this paper, I argue that the ultimate argument for Scientific Realism, also known as the No-Miracles Argument (NMA), ultimately fails as an abductive defence of Epistemic Scientific Realism (ESR), where (ESR) is the thesis that successful theories of mature sciences are approximately true. The NMA is supposed to be an Inference to the Best Explanation (IBE) that purports to explain the success of science. However, the explanation offered as the best explanation for success, namely (ESR), fails to (...) yield independently testable predictions that alternative explanations for success do not yield. If this is correct, then there seems to be no good reason to prefer (ESR) over alternative explanations for success. (shrink)
Debates about scientific realism are closely connected to almost everything else in the philosophy of science, for they concern the very nature of scientific knowledge. Scientific realism is a positive epistemic attitude toward the content of our best theories and models, recommending belief in both observable and unobservable aspects of the world described by the sciences. This epistemic attitude has important metaphysical and semantic dimensions, and these various commitments are contested by a number of rival epistemologies of (...) science, known collectively as forms of scientific antirealism. This article explains what scientific realism is, outlines its main variants, considers the most common arguments for and against the position, and contrasts it with its most important antirealist counterparts. (shrink)
Scientists are constantly making observations, carrying out experiments, and analyzing empirical data. Meanwhile, scientific theories are routinely being adopted, revised, discarded, and replaced. But when are such changes to the content of science improvements on what came before? This is the question of scientific progress. One answer is that progress occurs when scientific theories ‘get closer to the truth’, i.e. increase their degree of truthlikeness. A second answer is that progress consists in increasing theories’ effectiveness for solving (...)scientific problems. A third answer is that progress occurs when the stock of scientific knowledge accumulates. A fourth and final answer is that scientific progress consists in increasing scientific understanding, i.e. the capacity to correctly explain and reliably predict relevant phenomena. This paper compares and contrasts these four accounts of scientific progress, considers some of the most prominent arguments for and against each account, and briefly explores connections to different forms of scientific realism. (shrink)
In contemporary philosophy of science, the no-miracles argument and the pessimistic induction are regarded as the strongest arguments for and against scientific realism, respectively. In this paper, I construct a new argument for scientific realism which I call the anti-induction for scientific realism. It holds that, since past theories were false, present theories are true. I provide an example from the history of science to show that anti-inductions sometimes work in science. The anti-induction for scientific realism (...) has several advantages over the no-miracles argument as a positive argument for scientific realism. (shrink)
It has often been argued that Humean accounts of natural law cannot account for the role played by laws in scientific explanations. Loewer (Philosophical Studies 2012) has offered a new reply to this argument on behalf of Humean accounts—a reply that distinguishes between grounding (which Loewer portrays as underwriting a kind of metaphysical explanation) and scientific explanation. I will argue that Loewer’s reply fails because it cannot accommodate the relation between metaphysical and scientific explanation. This relation also (...) resolves a puzzle about scientific explanation that Hempel and Oppenheim (Philosophy of Science 15:135–75, 1948) encountered. (shrink)
Both science and philosophy are interested in questions of ontology- questions about what exists and what these things are like. Science and philosophy, however, seem like very different ways of investigating the world, so how should one proceed? Some defer to the sciences, conceived as something apart from philosophy, and others to metaphysics, conceived as something apart from science, for certain kinds of answers. This book contends that these sorts of deference are misconceived. A compelling account of ontology must appreciate (...) the ways in which the sciences incorporate metaphysical assumptions and arguments. At the same time, it must pay careful attention to how observation, experience, and the empirical dimensions of science are related to what may be viewed as defensible philosophical theorizing about ontology. The promise of an effectively naturalized metaphysics is to encourage beliefs that are formed in ways that do justice to scientific theorizing, modeling, and experimentation. But even armed with such a view, there is no one, uniquely rational way to draw lines between domains of ontology that are suitable for belief, and ones in which it would be better to suspend belief instead. In crucial respects, ontology is in the eye of the beholder: it is Informed by underlying commitments with implications for the limits of inquiry, which inevitably vary across rational inquirers. As a result, the proper scope of ontology is subject to a striking form of voluntary choice, yielding a new and transformative conception of scientific ontology. (shrink)
We report the results of a study that investigated the views of researchers working in seven scientific disciplines (physics, chemistry, biology, economics, psychology, sociology, and anthropology) and in HPS (N = 1,798) in regard to four hypothesized dimensions of scientific realism. Among other things, we found (i) that natural scientists tended to express more strongly realist views than social scientists, (ii) that social scientists working in fields where quantitative methods predominate tended to express more strongly realist views than (...) social scientists working in fields where qualitative methods are more common, (iii) that HPS scholars tended to express more anti-realist views than natural scientists, aligning themselves with social scientists working in fields where qualitative methods are more common, (iv) that van Fraassen’s characterization of scientific realism failed to cluster with more standard characterizations, (v) that a van Fraassen-style anti-realism is significantly more popular among scientists and HPS scholars than more standard forms of anti-realism, and (vi) that while those who endorsed the No-Miracles Argument were more likely to endorse scientific realism, those who endorsed the Pessimistic Induction were no more or less likely to endorse anti-realism. (shrink)
Bird argues that scientific progress consists in increasing knowledge. Dellsén objects that increasing knowledge is neither necessary nor sufficient for scientific progress, and argues that scientific progress rather consists in increasing understanding. Dellsén also contends that unlike Bird’s view, his view can account for the scientific practices of using idealizations and of choosing simple theories over complex ones. I argue that Dellsén’s criticisms against Bird’s view fail, and that increasing understanding cannot account for scientific progress, (...) if acceptance, as opposed to belief, is required for scientific understanding. (shrink)
If scientists embrace scientific realism, they can use a scientific theory to explain and predict observables and unobservables. If, however, they embrace scientific antirealism, they cannot use a scientific theory to explain observables and unobservables, and cannot use a scientific theory to predict unobservables. Given that explanation and prediction are means to make scientific progress, scientists can make more scientific progress, if they embrace scientific realism than if they embrace scientific antirealism.
The aim of this essay is to argue for a new version of ‘inference-to-the-best-explanation’ scientific realism, which I characterize as Best Theory Realism or ‘BTR’. On BTR, the realist needs only to embrace a commitment to the truth or approximate truth of the best theories in a field, those which are unique in satisfying the highest standards of empirical success in a mature field with many successful but falsified predecessors. I argue that taking our best theories to be true (...) is justified because it provides the best explanation of the predictive success of their predecessors and their own special success. Against standard and especially structural realism, I argue against the claim that the best explanations of the success of theories is provided by identifying their true components, such as structural relations between unobservable, which are preserved across theory change. In particular, I criticize Ladyman's and Carrier’s structural account of the success of phlogiston theory, and Worrall's well-known structural account of the success of Fresnel’s theory of light. I argue that these accounts tacitly assume the truth of our best theories, which in any case provides a better explanation of these theories’ success than the structural account. Structural realism is now defended as the only version of realism that is able to surmount the pessimistic meta-induction and the general problem that successful theories involve ontological claims concerning unobservable entities that are abandoned and falsified in theory-change. I argue that Best Theory Realism can overcome the pessimistic meta-induction and this general problem posed by theory-change. Our best theories possess a characteristic which sharply distinguishes them from their successful but false predecessors. Furthermore ‘inference-to-the-best-explanation’ confirmation can establish the truth of our best theories and thus trumps the pessimistic inductive reasoning which is supposed to show that even our best theories are most likely false in their claims concerning unobservable entities and processes. (shrink)
This article endeavors to identify the strongest versions of the two primary arguments against epistemic scientific realism: the historical argument—generally dubbed “the pessimistic meta-induction”—and the argument from underdetermination. It is shown that, contrary to the literature, both can be understood as historically informed but logically validmodus tollensarguments. After specifying the question relevant to underdetermination and showing why empirical equivalence is unnecessary, two types of competitors to contemporary scientific theories are identified, both of which are informed by science itself. (...) With the content and structure of the two nonrealist arguments clarified, novel relations between them are uncovered, revealing the severity of their collective threat against epistemic realism and its “no-miracles” argument. The final section proposes, however, that the realist’s axiological tenet “science seeks truth” is not blocked. An attempt is made to indicate the promise for a nonepistemic, purely axiological scientific realism—here dubbed “Socratic scientific realism.”. (shrink)
A scientific community cannot practice its trade without some set of received beliefs. These beliefs form the foundation of the "educational initiation that prepares and licenses the student for professional practice". The nature of the "rigorous and rigid" preparation helps ensure that the received beliefs are firmly fixed in the student's mind. Scientists take great pains to defend the assumption that scientists know what the world is like...To this end, "normal science" will often suppress novelties which undermine its foundations. (...) Research is therefore not about discovering the unknown, but rather "a strenuous and devoted attempt to force nature into the conceptual boxes supplied by professional education". (shrink)
Described by the philosopher A.J. Ayer as a work of 'great originality and power', this book revolutionized contemporary thinking on science and knowledge. Ideas such as the now legendary doctrine of 'falsificationism' electrified the scientific community, influencing even working scientists, as well as post-war philosophy. This astonishing work ranks alongside The Open Society and Its Enemies as one of Popper's most enduring books and contains insights and arguments that demand to be read to this day.
Scientific realism is the position that the aim of science is to advance on truth and increase knowledge about observable and unobservable aspects of the mind-independent world which we inhabit. This book articulates and defends that position. In presenting a clear formulation and addressing the major arguments for scientific realism Sankey appeals to philosophers beyond the community of, typically Anglo-American, analytic philosophers of science to appreciate and understand the doctrine. The book emphasizes the epistemological aspects of scientific (...) realism and contains an original solution to the problem of induction that rests on an appeal to the principle of uniformity of nature. (shrink)
Combining active externalism in the form of the extended and distributed cognition hypotheses with virtue reliabilism can provide the long sought after link between mainstream epistemology and philosophy of science. Specifically, by reading virtue reliabilism along the lines suggested by the hypothesis of extended cognition, we can account for scientific knowledge produced on the basis of both hardware and software scientific artifacts. Additionally, by bringing the distributed cognition hypothesis within the picture, we can introduce the notion of epistemic (...) group agents, in order to further account for collective knowledge produced on the basis of scientific research teams. (shrink)
Throughout more than two millennia philosophers adhered massively to ideal standards of scientific rationality going back ultimately to Aristotle’s Analytica posteriora . These standards got progressively shaped by and adapted to new scientific needs and tendencies. Nevertheless, a core of conditions capturing the fundamentals of what a proper science should look like remained remarkably constant all along. Call this cluster of conditions the Classical Model of Science . In this paper we will do two things. First of all, (...) we will propose a general and systematized account of the Classical Model of Science. Secondly, we will offer an analysis of the philosophical significance of this model at different historical junctures by giving an overview of the connections it has had with a number of important topics. The latter include the analytic-synthetic distinction, the axiomatic method, the hierarchical order of sciences and the status of logic as a science. Our claim is that particularly fruitful insights are gained by seeing themes such as these against the background of the Classical Model of Science. In an appendix we deal with the historiographical background of this model by considering the systematizations of Aristotle’s theory of science offered by Heinrich Scholz, and in his footsteps by Evert W. Beth. (shrink)
The book is a defence of scientific realism. Its primary aim is to argue that it is possible to establish scientific realism without Inference to the Best Explanation. The idea that plays the central role in the book is an "Eddington-inference". Arthur Eddington once considered a hypothetical ichthyologist who concluded from the fact that his net contained no fish smaller than the holes in his net that there were in the sea no fish smaller than the holes in (...) his net. Although Eddington himself defended the inference, the author of the present volume argues on probabilistic grounds that it is likely such an inference is flawed. He generalises the argument to develop a probabilistic justification for scientific realist claims about the existence of unobservable entities. (shrink)
REVIEW (1): "Jeff Kochan’s book offers both an original reading of Martin Heidegger’s early writings on science and a powerful defense of the sociology of scientific knowledge (SSK) research program. Science as Social Existence weaves together a compelling argument for the thesis that SSK and Heidegger’s existential phenomenology should be thought of as mutually supporting research programs." (Julian Kiverstein, in Isis) ---- REVIEW (2): "I cannot in the space of this review do justice to the richness and range of (...) Kochan's discussion [...]. There is a great deal in this foundational portion of Kochan's discussion that I find tremendously interesting and engaging [...]." (David R. Cerbone, in Studies in History and Philosophy of Science) ---- REVIEW (3): "Science as Social Existence will be of interest not only to Heidegger scholars but to anyone engaged in science and technology studies. [...] This is an informative and original book. Kochan should be praised for his clear, pleasant-to-read prose." (Michael Butler, in CHOICE). (shrink)
First, I argue that scientific progress is possible in the absence of increasing verisimilitude in science’s theories. Second, I argue that increasing theoretical verisimilitude is not the central, or primary, dimension of scientific progress. Third, I defend my previous argument that unjustified changes in scientific belief may be progressive. Fourth, I illustrate how false beliefs can promote scientific progress in ways that cannot be explicated by appeal to verisimilitude.
Alexander Bird argues for an epistemic account of scientific progress, whereas Darrell Rowbottom argues for a semantic account. Both appeal to intuitions about hypothetical cases in support of their accounts. Since the methodological significance of such appeals to intuition is unclear, I think that a new approach might be fruitful at this stage in the debate. So I propose to abandon appeals to intuition and look at scientific practice instead. I discuss two cases that illustrate the way in (...) which scientists make judgments about progress. As far as scientists are concerned, progress is made when scientific discoveries contribute to the increase of scientific knowledge of the following sorts: empirical, theoretical, practical, and methodological. I then propose to articulate an account of progress that does justice to this broad conception of progress employed by scientists. I discuss one way of doing so, namely, by expanding our notion of scientific knowledge to include both know-that and know-how. (shrink)
The scientific realism debate has now reached an entirely new level of sophistication. Faced with increasingly focused challenges, epistemic scientific realists have appropriately revised their basic meta-hypothesis that successful scientific theories are approximately true: they have emphasized criteria that render realism far more selective and, so, plausible. As a framework for discussion, I use what I take to be the most influential current variant of selective epistemic realism, deployment realism. Toward the identification of new case studies that (...) challenge this form of realism, I break away from the standard list and look to the history of celestial mechanics, with an emphasis on twentieth century advances. I then articulate two purely deductive arguments that, I argue, properly capture the historical threat to realism. I contend that both the content and form of these novel challenges seriously threaten selective epistemic realism. I conclude on a positive note, however, arguing for selective realism at a higher level. Even in the face of threats to its epistemic tenet, scientific realism need not be rejected outright: concern with belief can be bracketed while nonetheless advocating core realist tenets. I show that, in contrast with epistemic deployment realism, a purely axiological scientific realism can account for key scientific practices made salient in my twentieth century case studies. And embracing the realists favored account of inference, inference to the best explanation, while pointing to a set of the most promising alternative selective realist meta-hypothesis, I show how testing the latter can be immensely valuable to our understanding of science. (shrink)
As the future of human development increasingly hinges on the need for sustainable education and science, this essay re-examines the imminent threats to humankind and the relevance of achieving the United Nations’ Sustainable Development Goals (SDGs) to science-technology research among today’s young scientists. It also discusses some socio-political and economic challenges to achieving sustainability and argues that developing sustainability science is difficult but not impossible. The hope lies in our current efforts to build productive and creative scientific communities through (...) nurturing youth engagement with science and the scientific mindset. (shrink)
Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization that was developed to address just this sort of epistemic opacity. The visualization (...) is unusual in that it depicts the dynamics and structure of a computer model instead of that model’s target system, and because it is generated algorithmically. Using considerations from epistemology and aesthetics, we explore how this new kind of visualization increases scientific understanding of the content and function of computer models in systems biology to reduce epistemic opacity. (shrink)
The debate about scientific realism is concerned with the relation between our scientific theories and the world. Scientific realists argue that our best theories or components of those theories correspond to the world. Anti-realists deny such a correspondence. Traditionally, this central issue in the philosophy of science has been approached by focusing on the theories themselves (e.g., by looking at theory change or the underlying experimental context). I propose a relatively unexplored way to approach this old debate. (...) In addition to focusing on the theory, we should focus on the theorizer. More precisely, in order to determine on which component of a theory we should hinge a realist commitment, we should analyze the cognitive processes underlying scientific theorizing. In this paper I do just that. Drawing from recent developments in the cognitive sciences and evolutionary epistemology, I formulate some tentative conclusions. The aim of this paper is not so much to defend a particular position in the debate on scientific realism but to showcase the value of taking a cognitive perspective in the debate. (shrink)
This paper traces how media representations encouraged enthusiasts, youth and skilled volunteers to participate actively in science and technology during the twentieth century. It assesses how distinctive discourses about scientific amateurs positioned them with respect to professionals in shifting political and cultural environments. In particular, the account assesses the seminal role of a periodical, Scientific American magazine, in shaping and championing an enduring vision of autonomous scientific enthusiasms. Between the 1920s and 1970s, editors Albert G. Ingalls and (...) Clair L. Stong shepherded generations of adult ‘amateur scientists’. Their columns and books popularized a vision of independent nonprofessional research that celebrated the frugal ingenuity and skills of inveterate tinkerers. Some of these attributes have found more recent expression in present-day ‘maker culture’. The topic consequently is relevant to the historiography of scientific practice, science popularization and science education. Its focus on independent nonprofessionals highlights political dimensions of agency and autonomy that have often been implicit for such historical (and contemporary) actors. The paper argues that the Scientific American template of adult scientific amateurism contrasted with other representations: those promoted by earlier periodicals and by a science education organization, Science Service, and by the national demands for recruiting scientific labour during and after the Second World War. The evidence indicates that advocates of the alternative models had distinctive goals and adapted their narrative tactics to reach their intended audiences, which typically were conceived as young persons requiring instruction or mentoring. By contrast, the monthly Scientific American columns established a long-lived and stable image of the independent lay scientist. (shrink)
Scientific realists believe both what a scientific theory says about observables and unobservables. In contrast, scientific antirealists believe what a scientific theory says about observables, but not about unobservables. I argue that scientific realism is a more useful doctrine than scientific antirealism in science classrooms. If science teachers are antirealists, they are caught in Moore’s paradox when they help their students grasp the content of a scientific theory, and when they explain a phenomenon (...) in terms of a scientific theory. Teachers ask questions to their students to check whether they have grasped the content of a scientific theory. If the students are antirealists, they are also caught in Moore’s paradox when they respond positively to their teachers’ questions, and when they explain a phenomenon in terms of a scientific theory. Finally, neither teachers nor students can understand phenomena in terms of scientific theories, if they are antirealists. (shrink)
In the Principles, Descartes explains several observable phenomena showing that they are caused by special arrangements of unobservable microparticles. Despite these microparticles being unobservable, many passages suggest that he was very confident that these explanations were correct. In other passages, however, Descartes points out that these explanations merely hold the status of ‘suppositions’ or ‘conjectures’ that could be wrong. The aim of this chapter is to clarify this apparent conflict. I argue that the possibility of natural explanations being wrong should (...) be understood as these explanations not being absolutely certain, but as being morally certain. Cartesian explanations rely on what Ernan McMullin calls retroduction, which is a mode of inference that justifies beliefs in concrete unobservable entities and processes. I use as a foil the debate in contemporary philosophy of science between scientific realism and instrumentalism, and argue that for Descartes we could indeed have knowledge of the unobservable world. In that sense, he was closer to being a scientific realist. (shrink)
There are nine antirealist explanations of the success of science in the literature. I raise difficulties against all of them except the latest one, and then construct a pessimistic induction that the latest one will turn out to be problematic because its eight forerunners turned out to be problematic. This pessimistic induction is on a par with the traditional pessimistic induction that successful present scientific theories will be revealed to be false because successful past scientific theories were revealed (...) to be false. (shrink)
I claim that one way thought experiments contribute to scientific progress is by increasing scientific understanding. Understanding does not have a currently accepted characterization in the philosophical literature, but I argue that we already have ways to test for it. For instance, current pedagogical practice often requires that students demonstrate being in either or both of the following two states: 1) Having grasped the meaning of some relevant theory, concept, law or model, 2) Being able to apply that (...) theory, concept, law or model fruitfully to new instances. Three thought experiments are presented which have been important historically in helping us pass these tests, and two others that cause us to fail. Then I use this operationalization of understanding to clarify the relationships between scientific thought experiments, the understanding they produce, and the progress they enable. I conclude that while no specific instance of understanding (thus conceived) is necessary for scientific progress, understanding in general is. (shrink)