It is usually accepted that deductions are non-informative and monotonic, inductions are informative and nonmonotonic, abductions create hypotheses but are epistemically irrelevant, and both deductions and inductions can’t provide new insights. In this article, I attempt to provide a more cohesive view of the subject with the following hypotheses: (1) the paradigmatic examples of deductions, such as modus ponens and hypothetical syllogism, are not inferential forms, but coherence requirements for inferences; (2) since any reasoner aims to be coherent, any inference (...) must be deductive; (3) a coherent inference is an intuitive process where the premises should be taken as sufficient evidence for the conclusion, which on its turn should be viewed as necessary evidence for the premises in some modal range; (4) inductions, properly understood, are abductions, but there are no abductions beyond the fact that in any inference the conclusion should be regarded as necessary evidence for the premises; (5) monotonicity is not only compatible with the retraction of past inferences given new information, but it is a requirement for it; (6) this explanation of inferences holds true for discovery processes, predictions and trivial inferences. (shrink)

In this article, I consider an important challenge to the popular theory of scientific inference commonly known as ‘inference to the best explanation’, one that has received scant attention.1 1 The problem is that there exists a wide array of rival models of explanation, thus leaving IBE objectionably indeterminate. First, I briefly introduce IBE. Then, I motivate the problem and offer three potential solutions, the most plausible of which is to adopt a kind of pluralism about the rival models of (...) explanation. However, I argue that how ranking explanations on this pluralistic account of IBE remains obscure and pluralism leads to contradictory results. In light of these objections, I attempt to dissolve the problem by showing why IBE does not require a ‘model’ of explanation and by giving an account of what explanation consists in within the context of IBE. (shrink)

Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: the details of their contents, calculations, (...) and procedures cannot be meaningfully understood by human practitioners. When AI systems reach this level of complexity, we can also speak of black-box medicine. In this paper, we want to argue that black-box medicine conflicts with core ideals of patient-centered medicine. In particular, we claim, black-box medicine is not conducive for supporting informed decision-making based on shared information, shared deliberation, and shared mind between practitioner and patient. (shrink)

While Plantinga has famously argued that acceptance of neo-Darwinian theory commits one to the rejection of naturalism, Plantinga’s argument is vulnerable to an objection developed by Evan Fales. Not only does Fales’ objection undermine Plantinga’s original argument, it establishes a general challenge which any attempt to revitalize Plantinga’s argument must overcome. After briefly laying out the contours of this challenge, we attempt to meet it by arguing that because a purely naturalistic account of our etiology cannot explain the correlation between (...) our preference for simplicity and simplicity’s ability to serve as a veridical method of theory selection, the scientific realist is committed to the rejection of naturalism. (shrink)

Reductive intellectualists about knowledge-how hold, contra Ryle, that knowing how to do something is just a kind of propositional knowledge. In a similar vein, traditional reductivists about understanding-why insist, in accordance with a tradition beginning with Aristotle, that the epistemic standing one attains when one understands why something is so is itself just a kind of propositional knowledge—viz., propositional knowledge of causes. A point that has been granted on both sides of these debates is that if these reductive proposals are (...) right, then knowledge-how and understanding-why should be susceptible to the same extent as knowledge-that is to being undermined by epistemic luck. This paper reports experimental results that test these luck-based predictions. Interestingly, these results suggest a striking positive correlation between self-reported philosophical expertise and attributions of knowledge-how, understanding-why and knowledge-that which run contrary to reductive proposals. We contextualize these results by showing how they align very well with a particular kind of overarching non-reductive proposal, one that two of the authors have defended elsewhere according to which knowledge-how and understanding-why, but not knowledge-that, essentially involve cognitive achievement. We conclude by situating the interpretive narrative advanced within contemporary discussions about the role of expertise in philosophical judgment. (shrink)

I evaluate Schurz's proposed meta-inductive justification of induction, a refinement of Reichenbach's pragmatic justification that rests on results from the machine learning branch of prediction with expert advice. My conclusion is that the argument, suitably explicated, comes remarkably close to its grand aim: an actual justification of induction. This finding, however, is subject to two main qualifications, and still disregards one important challenge. The first qualification concerns the empirical success of induction. Even though, I argue, Schurz's argument does not need (...) to spell out what inductive method actually consists in, it does need to postulate that there is something like the inductive or scientific prediction strategy that has so far been significantly more successful than alternative approaches. The second qualification concerns the difference between having a justification for inductive method and for sticking with induction for now. Schurz's argument can only provide the latter. Finally, the remaining challenge concerns the pool of alternative strategies, and the relevant notion of a meta-inductivist's optimality that features in the analytic step of Schurz's argument. Building on the work done here, I will argue in a follow-up paper that the argument needs a stronger dynamic notion of a meta-inductivist's optimality. (shrink)

What is medicine? One obvious answer in the context of the contemporary clinical tradition is that medicine is the process of curing sick people. However, this “curative thesis” is not satisfactory, even when “cure” is defined generously and even when exceptions such as cosmetic surgery are set aside. Historian of medicine Roy Porter argues that the position of medicine in society has had, and still has, little to do with its ability to make people better. Moreover, the efficacy of medicine (...) for improving population health has been famously doubted by historians and epidemiologists. The curative thesis demands that we have mostly been stupid, duped, or staggeringly hopeful, given that medicine has not until recently offered more than a handful of effective cures. I suggest, in this article, that the core medical competence is neither to cure, nor to prevent, disease, but to understand and to predict it. I argue that this approach does a better job than the curative thesis at explaining why not all medicine is concerned with curative efforts and that it enjoys historical support from the ancient entanglement of prophecy and medicine and from the fact that medicine thrived for centuries with almost no effective cures and continues to thrive today in various forms that are mostly without curative efficacy. I suggest that this approach grounds a fairer approach to alternative, traditional, and other medical practices, as well as some fresh lessons for the development of mainstream medicine. (shrink)

In the process of scientific discovery, knowledge ampliation is pursued by means of non-deductive inferences. When ampliative reasoning is performed, probabilities cannot be assigned objectively. One of the reasons is that we face the problem of the unconceived alternatives: we are unable to explore the space of all the possible alternatives to a given hypothesis, because we do not know how this space is shaped. So, if we want to adequately account for the process of knowledge ampliation, we need to (...) develop an account of the process of scientific discovery which is not exclusively based on probability calculus. We argue that the analytic view of the method of science advocated by Cellucci is interestingly suited to this goal, since it rests on the concept of plausibility. In this perspective, in order to account for how probabilities are in fact assigned in uncertain contexts and knowledge ampliation is really pursued, we have to take into account plausibility-based considerations. (shrink)

Duncan Pritchard argues that a feature that sets understanding-why apart from knowledge-why is that whereas (I) understanding-why is a kind of cognitive achievement in a strong sense, (II) knowledge-why is not such a kind. I argue that (I) is false and that (II) is true. (I) is false because understanding-why featuring rudimentary explanations and understanding-why concerning very simple causal connections are not cognitive achievements in a strong sense. Knowledge-why is not a kind of cognitive achievement in a strong sense for (...) the same reason knowledge-that is not. The latter thesis requires showing that having (p because q) information is not equivalent to having information about facts or principles that establish the explanatory connections between the phenomena in question. I make a positive case for this claim and defend it against objections. Based on this argument, I identify an alternative feature that sets understanding-why apart from knowledge-why: The minimal condition for understanding-why and knowledge-why with respect to their contents is not identical. Knowing why p merely requires information that some explanatorily relevant dependency obtains. Understanding why p additionally requires information about facts or principles that establish the explanatory connections between the phenomena in question. (shrink)

This article casts light on the intimate relationship between metaphysics and science in Adam Smith’s thought. Understanding this relationship can help in resolving an enduring dispute or misreading concerning the status and role of natural theology and the ‘invisible hand’ doctrine. In Smith’s scientific realism, ontological issues are necessary prerequisites for scientific inquiry, and metaphysical ideas thus play an organizing and regulatory role. Smith also recognized the importance of scientifically informed metaphysics in science’s historical development. In this sense, for Smith, (...) the metaphysico-scientific link, was a basic criterion of scientific validation by Inference to the Best Explanation. Furthermore, Smith’s comments implicitly suggest that in scientific progress there is a dialectic between metaphysics and science. These themes are illustrated primarily through his writings on the history of astronomy. (shrink)

Structural realists claim that we should endorse only what our scientific theories say about the structure of the unobservable world. But according to Newman’s Objection, the structural realist’s claims about unobservables are trivially true. In recent years, several theorists have offered responses to Newman’s Objection. But a common complaint is that these responses “give up the spirit” of the structural realist position. In this paper, I will argue that the simplest way to respond to Newman’s Objection is to return to (...) one of the standard motivations for adopting structural realism in the first place: the No Miracles Argument. Far from betraying the spirit of structural realism, the solution I present is available to any theorist who endorses this argument. (shrink)

Systematicity theory—developed and articulated by Paul Hoyningen-Huene—and scientific realism constitute separate encompassing and empirical accounts of the nature of science. Standard scientific realism asserts the axiological thesis that science seeks truth and the epistemological thesis that we can justifiably believe our successful theories at least approximate that aim. By contrast, questions pertaining to truth are left “outside” systematicity theory’s “intended scope” ; the scientific realism debate is “simply not” its “focus”. However, given the continued centrality of that debate in the (...) general philosophy of science literature, and given that scientific realists also endeavor to provide an encompassing empirical account of science, I suggest that these two contemporary accounts have much to offer one another. Overlap for launching a discussion of their relations can be found in Nicholas Rescher’s work. Following through on a hint from Rescher, I embrace a non-epistemic, purely axiological scientific realism—what I have called, Socratic scientific realism. And, bracketing the realist’s epistemological thesis, I put forward the axiological tenet of scientific realism as a needed supplement to systematicity theory. There are two broad components to doing this. First, I seek to make clear that axiological realism and systematicity theory accord with one another. Toward that end, after addressing Hoyningen-Huene’s concerns about axiological analysis, I articulate a refined axiological realist meta-hypothesis: it is, in short, that the end toward which scientific inquiry is directed is an increase in a specific subclass of true claims. I then identify a key feature of scientific inquiry, not generally flagged explicitly, that I take to stand as shared terrain for the two empirical meta-hypotheses. And I argue that this feature can be informatively accounted for by my axiological meta-hypothesis. The second broad component goes beyond mere compatibility between the two positions: I argue that, in want of a systematic account of science, we are prompted to find an end toward which scientific inquiry is directed that is deeper than what systematicity theory offers. Specifically, I argue that my refined axiological realist meta-hypothesis is required to both explain and justify key dimensions of systematicity in science. To the quick question, what is it that the scientific enterprise is systematically doing? My quick answer is that it is systematically seeking to increase a particular subclass of true claims. (shrink)

Two apparently mutually exclusive ideas about the relation between contrastive and non-contrastive explanations can be found in the literature. According to contrastivists, all explanation is contrastive explanation and the supposed existence of non-contrastive explanations can be revealed to be an illusion. According to non-contrastivists, on the other hand, contrastive explanation can be fully analysed in terms of non-contrastive explanation, and is thus not of fundamental importance. In the current article, I discuss the main arguments in favour of and against each (...) of the two positions. This discussion leads to the idea that contrastive explanations are to be understood as parts of a bigger, more complete non-contrastive explanation; but that all actual explanations explain only a limited set of contrasts. I conclude that, once the relation between contrastive and non-contrastive explanations is understood correctly, there remains no substantial issue to divide contrastivism and non-contrastivism. (shrink)

In Denis Walsh’s Organisms, Agency, and Evolution, he argues that new developments in the science of biology motivate a radical change to our metaphysical picture of life: what he calls ‘Situated Darwinism’. The central claim is that we should take the biological world to be at base about organisms, and organisms in a fundamentally teleological sense. We critically examine Walsh’s arguments and suggest further developments.

Proponents of the no-miracles argument contend that scientific realism is “the only philosophy that doesn’t make the success of science a miracle.” Bas van Fraassen argued, however, that the success of our best theories can be explained in Darwinian terms—by the fact they are survivors of a winnowing process in which unsuccessful theories are rejected. Critics of this selectionist explanation complain that while it may account for the fact we have chosen successful theories, it does not explain why any particular (...) one of those theories succeeds. Against this I defend the claim that if selectionists manage to account for the former, they have no burden to account for the latter; the success of any particular one of our best theories might as well be an extraordinary coincidence. I refer to this enhanced selectionist reply as “coincidentalism” and argue that it is a serious but underappreciated response to the no-miracles argument. More generally, I argue the considerations raised in favor of this response show that versions of the no-miracles argument focusing on the success of particular theories are misguided. (shrink)

Most philosophers agree that abduction (in the sense of Inference to the Best Explanation) is a type of inference that is frequently employed, in some form or other, both in everyday and in scientific reasoning. However, the exact form as well as the normative status of abduction are still matters of controversy. This entry contrasts abduction with other types of inference; points at prominent uses of it, both in and outside philosophy; considers various more or less precise statements of it; (...) discusses its normative status; and highlights possible connections between abduction and Bayesian confirmation theory. (shrink)

Scientists often use aesthetic values in the evaluation and choice of theories. Aesthetic values are not only regarded as leading to practically more useful theories but are often taken to stand in a special epistemic relation to the truth of a theory such that the aesthetic merit of a theory is evidence of its truth. This paper explores what aesthetic considerations influence scientists' reasoning, how such aesthetic values relate to the utility of a scientific theory, and how one can justify (...) the epistemic role for such values. The paper examines ways in which the link between beauty and truth can be defended, the challenges facing such accounts, and explores alternative epistemic roles for aesthetic values in scientific practice. (shrink)

An influential suggestion about the relationship between Bayesianism and inference to the best explanation holds that IBE functions as a heuristic to approximate Bayesian reasoning. While this view promises to unify Bayesianism and IBE in a very attractive manner, important elements of the view have not yet been spelled out in detail. I present and argue for a heuristic conception of IBE on which IBE serves primarily to locate the most probable available explanatory hypothesis to serve as a working hypothesis (...) in an agent’s further investigations. Along the way, I criticize what I consider to be an overly ambitious conception of the heuristic role of IBE, according to which IBE serves as a guide to absolute probability values. My own conception, by contrast, requires only that IBE can function as a guide to the comparative probability values of available hypotheses. This is shown to be a much more realistic role for IBE given the nature and limitations of the explanatory considerations with which IBE operates. (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)

Explanatory realism is the position that all explanations give information about whatever metaphysically determines the explanandum. This view is popular and plays a central role in metaphysics, but in this paper I argue that explanatory realism is false. In Sect. 1 I introduce explanatory realism in its weak and strong versions, and discuss the argumentative work that explanatory realism is used for in contemporary metaphysics. In Sect. 2 I present a series of problem cases for explanatory realism, including explanation by (...) analogy, explanations involving rules, reduction ad absurdum explanations and certain statistical explanations. In Sect. 3 I consider and reject two modified versions of explanatory realism: the position that explanatory realism is true only of explanation in metaphysics, and the position that determinative explanation is the most complete form of explanation. In conclusion I consider explanatory antirealism and explanatory pluralism as alternatives to explanatory realism. (shrink)

In a recent paper, Jakob Hohwy argues that the emerging predictive processing perspective on cognition requires us to explain cognitive functioning in purely internalistic and neurocentric terms. The purpose of the present paper is to challenge the view that PP entails a wholesale rejection of positions that are interested in the embodied, embedded, extended, or enactive dimensions of cognitive processes. I will argue that Hohwy’s argument from analogy, which forces an evidentiary boundary into the picture, lacks the argumentative resources to (...) make a convincing case for the conceptual necessity to interpret PP in solely internalistic terms. For this reason, I will reconsider the postulation and explanatory role of the evidentiary boundary. I will arrive at an account of prediction error minimization and its foundation on the free energy principle that is fully consistent with approaches to cognition that emphasize the embodied and interactive properties of cognitive processes. This gives rise to the suggestion that explanatory pluralism about the application of PP is to be preferred over Hohwy’s explanatory monism that follows from his internalistic and neurocentric view of predictive cognitive systems. (shrink)

In this paper, I aim to provide access to the current debate on non-causal explanations in philosophy of science. I will first present examples of non-causal explanations in the sciences. Then, I will outline three alternative approaches to non-causal explanations – that is, causal reductionism, pluralism, and monism – and, corresponding to these three approaches, different strategies for distinguishing between causal and non-causal explanation. Finally, I will raise questions for future research on non-causal explanations.

Defenders of Inference to the Best Explanation claim that explanatory factors should play an important role in empirical inference. They disagree, however, about how exactly to formulate this role. In particular, they disagree about whether to formulate IBE as an inference rule for full beliefs or for degrees of belief, as well as how a rule for degrees of belief should relate to Bayesianism. In this essay I advance a new argument against non-Bayesian versions of IBE. My argument focuses on (...) cases in which we are concerned with multiple levels of explanation of some phenomenon. I show that in many such cases, following IBE as an inference rule for full beliefs leads to deductively inconsistent beliefs, and following IBE as a non-Bayesian updating rule for degrees of belief leads to probabilistically incoherent degrees of belief. (shrink)

It is argued that a popular way of accounting for the distinctive value of knowledge by appeal to the distinctive value of cognitive achievements fails because it is a mistake to identify knowledge with cognitive achievements. Nevertheless, it is claimed that understanding, properly conceived, is a type of cognitive achievement, and thus that the distinctive value of cognitive achievements can explain why understanding is of special value.

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)

Conspiracy theories are typically thought to be examples of irrational beliefs, and thus unlikely to be warranted. However, recent work in Philosophy has challenged the claim that belief in conspiracy theories is irrational, showing that in a range of cases, belief in conspiracy theories is warranted. However, it is still often said that conspiracy theories are unlikely relative to non-conspiratorial explanations which account for the same phenomena. However, such arguments turn out to rest upon how we define what gets counted (...) both as a ‘conspiracy’ and a ‘conspiracy theory’, and such arguments rest upon shaky assumptions. It turns out that it is not clear that conspiracy theories are prima facie unlikely, and so the claim that such theories do not typically appear in our accounts of the best explanations for particular kinds of events needs to be reevaluated. (shrink)

An exciting theory in neuroscience is that the brain is an organ for prediction error minimization. This theory is rapidly gaining influence and is set to dominate the science of mind and brain in the years to come. PEM has extreme explanatory ambition, and profound philosophical implications. Here, I assume the theory, briefly explain it, and then I argue that PEM implies that the brain is essentially self-evidencing. This means it is imperative to identify an evidentiary boundary between the brain (...) and its environment. This boundary defines the mind-world relation, opens the door to skepticism, and makes the mind transpire as more inferentially secluded and neurocentrically skull-bound than many would nowadays think. Therefore, PEM somewhat deflates contemporary hypotheses that cognition is extended, embodied and enactive; however, it can nevertheless accommodate the kinds of cases that fuel these hypotheses. (shrink)

I argue that understanding why p involves a kind of intellectual know how and differsfrom both knowledge that p and knowledge why p (as they are standardly understood).I argue that understanding, in this sense, is valuable.

The axiological tenet of scientific realism, “science seeks true theories,” is generally taken to rest on a corollary epistemological tenet, “we can justifiably believe that our successful theories achieve (or approximate) that aim.” While important debates have centered on, and have led to the refinement of, the epistemological tenet, the axiological tenet has suffered from neglect. I offer what I consider to be needed refinements to the axiological postulate. After showing an intimate relation between the refined postulate and ten theoretical (...) desiderata, I argue that the axiological postulate does not depend on its epistemological counterpart; epistemic humility can accompany us in the quest for truth. Upon contrasting my axiological postulate against the two dominant non-realist alternatives and the standard realist postulate, I contend that its explanatory and justificatory virtues render it, among the axiologies considered, the richest account of the scientific enterprise. (shrink)

This chapter examines the status of inference to the best explanation in naturalistic metaphysics. The methodology of inference to the best explanation in metaphysics is studied from the perspective of contemporary views on scientific explanation and explanatory inferences in the history and philosophy of science. This reveals serious shortcomings in prevalent attempts to vindicate metaphysical "explanationism" by reference to similarities between science and naturalistic metaphysics. This critique is brought out by considering a common gambit of methodological unity: (1) Both metaphysics (...) and science employ inference to the best explanation. (2) One has no reason to think that if explanationism is truth-conducive in science, it is not so in metaphysics. (3) One has a positive reason to think that if explanationism is truth-conducive in science, it is also so in metaphysics. (shrink)

The centerpiece of the scientific study of consciousness is the search for the neural correlates of consciousness. Yet science is typically interested not only in discovering correlations, but also – and more deeply – in explaining them. When faced with a correlation between two phenomena in nature, we typically want to know why they correlate. The purpose of this chapter is twofold. The first half attempts to lay out the various possible explanations of the correlation between consciousness and its neural (...) correlate – to provide a sort of “menu” of options from which we probably would ultimately have to choose. The second half raises considerations suggesting that, under certain reasonable assumptions, the choice among these various options may be in principle underdetermined by the relevant scientific evidence. (shrink)

In his seminal Inference to the Best Explanation, Peter Lipton adopted a causal view of explanation and a broadly Millian view of how causal knowledge is obtained. This made his account vulnerable to critics who charged that Inference to the Best Explanation is merely a dressed-up version of Mill’s methods, which in the critics’ view do the real inductive work. Lipton advanced two arguments to protect Inference to the Best Explanation against this line of criticism: the problem of multiple differences (...) and the problem of inferred differences. Lipton claimed that these two problems show Mill’s method of difference to be largely unworkable unless it is embedded in an explanationist framework. Here I consider both arguments as well as the best Millian defense against them. Since the existing Millian defense is only partially successful, I will develop a new and improved account. As an integral part of the argument, I show that my solutions to the problems of multiple and inferred differences offer new insight into Lipton’s main case study: Ignaz Semmelweis’s discovery of the cause of childbed fever. I conclude that the method of difference can overcome Lipton’s challenges outside an explanationist framework. (shrink)

It has been common wisdom for centuries that scientific inference cannot be deductive; if it is inference at all, it must be a distinctive kind of inductive inference. According to demonstrative theories of induction, however, important scientific inferences are not inductive in the sense of requiring ampliative inference rules at all. Rather, they are deductive inferences with sufficiently strong premises. General considerations about inferences suffice to show that there is no difference in justification between an inference construed demonstratively or ampliatively. (...) The inductive risk may be shouldered by premises or rules, but it cannot be shirked. Demonstrative theories of induction might, nevertheless, better describe scientific practice. And there may be good methodological reasons for constructing our inferences one way rather than the other. By exploring the limits of these possible advantages, I argue that scientific inference is neither of essence deductive nor of essence inductive. (shrink)

International Relations's intellectual history is almost always treated as a history of ideas in isolation from both those discursive and political economies which provide its disciplinary and wider context. This paper contributes to this wider analysis by focusing on the impact of the field's discursive economy. Specifically, using Foucaultian archaeologico-genealogical strategy of problematization to analyse the emergence and disciplinary trajectories of Constructivism in IR, this paper argues that Constructivism has been brought gradually closer to its mainstream Neo-utilitarian counterpart through a (...) process of normalization, and investigates how it was possible for Constructivism to be purged of its early critical potential, both theoretical and practical. The first part of the paper shows how the intellectual configuration of Constructivism and its disciplinary fortunes are inseparable from far-from-unproblematic readings of the Philosophy of Social Science: the choices made at this level are neither as intellectually neutral nor as disciplinarily inconsequential as they are presented. The second and third parts chart the genealogies of Constructivism, showing how its overall normalization occurred in two stages, each revolving around particular practices and events. The second part concentrates on older genealogies, analysing the politics of early classificatory practices regarding Constructivism, and showing how these permitted the distillation and immunization of Constructivism – and thus of the rest of the mainstream scholarship which it was depicted as compatible with – against more radical Postmodernist/Post-structuralist critiques. Finally, the third part focuses attention on recent genealogies, revealing new attempts to reconstruct and reformulate Constructivism: here, indirect neutralization practices such as the elaboration of ‘Pragmatist’ Constructivism, as well as the direct neutralization such as the formulation of ‘Realist’ Constructivism, are key events in Constructivism's normalization. These apparently ‘critical’ alternatives that aim to ‘provide the identity variable’ in fact remain close to Neo-utilitarianism, but their successful representation as ‘critical’ help neutralize calls for greater openness in mainstream IR. Rather than a simple intellectual history, it is this complex process of reading and producing that counts as ‘Constructivism’, which explains both the normalization of Constructivism and the continued marginalization of Postmodernist/Post-structuralist approaches in mainstream IR's infra-disciplinary balance of intellectual power. (shrink)

En este trabajo hago una comparación sistemática entre las dos teorías de la confirmación más populares en la actualidad: el método hipotético-deductivo y el bayesianismo. En primer lugar, enumero los cinco problemas fundamentales de la teoría hipotético-deductivista. Estos son el problema de las hipótesis estadísticas, el del grado de confirmación, el de la conjunción irrelevante, el del holismo epistemológico y el de las hipótesis alternativas. Luego, hago una presentación general de la epistemología bayesiana y muestro de qué manera estos problemas (...) resultan tratables en el marco bayesiano. Finalmente, concluyo que los tres primeros admiten una solución satisfactoria, sobre la base de algunos supuestos razonables. Los dos últimos, en cambio, todavía son problemas abiertos para la teoría bayesiana de la confirmación. Bayesians often affirm they have produced the best available theory of confirmation. In particular, they claim to have superseded the venerable hypothetico-deductive method. In this paper I intend to assess that claim by making a systematic comparison between both theories of confirmation. I begin by listing the main problems of hypothetico-deductive confirmation. I then show that this conception is incompatible with Hempel's conditions of adequacy for qualitative confirmation. I expound the Bayesian theory of confirmation with some detail in order to show that this theory is able to solve three out of the five fundamental problems of hypothetico-deductive confirmation. largue that the remaining two problems are still open questions for the Bayesians. (shrink)

Rationalism, my target, says that in order to have perceptual knowledge, such as that your hand is making a fist, you must “antecedently” (or “independently”) know that skeptical scenarios don’t obtain, such as the skeptical scenario that you are in the Matrix. I motivate the specific form of Rationalism shared by, among others, White (Philos Stud 131:525–557, 2006) and Wright (Proc Aristot Soc Suppl Vol 78:167–212, 2004), which credits us with warrant to believe (or “accept”, in Wright’s terms) that our (...) senses are reliably veridical, where that warrant is one we enjoy by default, that is, without relying on any evidence or engaging in any positive argument. The problem with this form of Rationalism is that, even if you have default knowledge that your senses are reliable, this is not adequate to rule out every kind of skeptical scenario. The problem is created by one-off skeptical scenarios, scenarios that involve a highly reliable perceiver who, by a pure fluke, has a one-off, non-veridical experience. I claim you cannot infer that your present perceptual experience is veridical just on the basis of knowledge of your general reliability. More generally, if you infer that the present F is G, just on the basis of your knowledge that most Fs are Gs, this is what I call statistical inference, and, as I argue, statistical inference by itself does not generate knowledge. I defend this view of statistical inference against objections, including the objection that radical skepticism about our ordinary inductive knowledge will follow unless statistical inference generates knowledge. (shrink)

According to a causal model of explanation, we explain phenomena by giving their causes or, where the phenomena are themselves causal regularities, we explain them by giving a mechanism linking cause and effect. If we explain why smoking causes cancer, we do not give the cause of this causal connection, but we do give the causal mechanism that makes it. The claim that to explain is to give a cause is not only natural and plausible, but it also avoids many (...) of the objections to other accounts of explanation, such as the views that to explain is to give a reason to believe the phenomenon occurred, to somehow make the phenomenon familiar, or to give a Deductive-Nomological argument. Unlike the reason for belief account, a causal model makes a clear distinction between understanding why a phenomenon occurs and merely knowing that it does, and the model does so in a way that makes understanding unmysterious and objective. Understanding is not some sort of super-knowledge, but simply more knowledge: knowledge of the phenomenon and knowledge of its causal history. A causal model makes it clear how something can explain without itself being explained, and so avoids the regress of whys, since we can know a phenomenon's cause without knowing the cause of the cause. It also accounts for legitimate self-evidencing explanations, explanations where the phenomenon is an essential part of the evidence that the explanation is correct, so the explanation can not supply a non-circular reason for believing the phenomenon occurred. There is no barrier to knowing a cause through its effects and also knowing that it is their cause. The speed of recession of a star explains its observed red-shift, even though the shift is an essential part of the evidence for its speed of recession. The model also avoids the most serious objection to the familiarity view, which is that some phenomena are familiar yet not understood, since a phenomenon can be perfectly familiar, such as the blueness of the sky or the fact that the same side of the moon always faces the earth, even if we do not know its cause. Finally, a causal model avoids many of the objections to the Deductive-Nomological model. Ordinary explanations do not have to meet the requirements of the Deductive-Nomological model, because one does not need to give a law to give a cause, and one does not need to know a law to have good reason to believe that a cause is a cause. As for the notorious over-permissiveness of the Deductive-Nomological model, the reason recession explains red-shift but not conversely, is simply that causes explain effects but not conversely, and the reason a conjunction of laws does not explain its conjuncts is that conjunctions do not cause their conjuncts. (shrink)

Edgar Allan Poe’s standing as a literary figure, who drew on (and sometimes dabbled in) the scientific debates of his time, makes him an intriguing character for any exploration of the historical interrelationship between science, literature and philosophy. His sprawling ‘prose-poem’ Eureka (1848), in particular, has sometimes been scrutinized for anticipations of later scientific developments. By contrast, the present paper argues that it should be understood as a contribution to the raging debates about scientific methodology at the time. This methodological (...) interest, which is echoed in Poe’s ‘tales of ratiocination’, gives rise to a proposed new mode of—broadly abductive—inference, which Poe attributes to the hybrid figure of the ‘poet-mathematician’. Without creative imagination and intuition, Science would necessarily remain incomplete, evenby its own standards. This concern with imaginative (abductive) inference ties in nicely with his coherentism, which grants pride of place to the twin virtues of Simplicity and Consistency, which must constrain imagination lest it degenerate into mere fancy. (shrink)

Kuhn’s famous thesis that there is ‘no unique algorithm’ for choosing between rival scientific theories is analysed using the machinery of social choice theory. It is shown that the problem of theory choice as posed by Kuhn is formally identical to a standard social choice problem. This suggests that analogues of well-known results from the social choice literature, such as Arrow’s impossibility theorem, may apply to theory choice. If an analogue of Arrow’s theorem does hold for theory choice this would (...) refute Kuhn’s thesis, but it would also pose a threat to the rationality of science, a threat that is if anything more worrying than that posed by Kuhn. Various possible ‘escape routes’ from Arrow’s impossibility result are examined, in particular Amartya Sen’s idea of ‘enriching the informational basis’. It is shown that Sen’s idea can be applied to the problem of theory choice in science. This in turn sheds light on two well-known approaches to inductive inference in philosophy of science: Bayesianism and statistical model selection. (shrink)

Abductivists claim that explanatory considerations (e.g., simplicity, parsimony, explanatory breadth, etc.) favor belief in the external world over skeptical hypotheses involving evil demons and brains in vats. After showing how most versions of abductivism succumb fairly easily to obvious and fatal objections, I explain how rationalist versions of abductivism can avoid these difficulties. I then discuss the most pressing challenges facing abductivist appeals to the a priori and offer suggestions on how to overcome them.

Nineteenth-century medical advances were entwined with a conceptual innovation: the idea that many cases of disease which were previously thought to have diverse causes could be explained by the action of a single kind of cause, for example a certain bacterial or parasitic infestation. The focus of modern epidemiology, however, is on chronic non-communicable diseases, which frequently do not seem to be attributable to any single causal factor. This paper is an effort to resolve the resulting tension. The paper criticises (...) the monocausal model of disease, so successful in the nineteenth century. It also argues that a multifactorial model of disease can only be satisfactory if it amounts to more than a mere rejection of the monocausal model. A third alternative, the contrastive model, is proposed and defended on the grounds that it links the notions of disease and of general explanation, while avoiding the philosophical naiveties and practical difficulties of the monocausal model. (shrink)

A general insight of 20th-century philosophy of science is that the acceptance of a scientific theory is grounded, not merely on a theory's relation to data, but on its status as having no, or being superior to its, competitors. I explore the ways in which scientific realists might be thought to utilise this insight, have in fact utilised it, and can legitimately utilise it. In more detail, I point out that, barring a natural but mistaken characterisation of scientific realism, traditional (...) realism has not utilised that insight regarding scientific theories, i.e., has not explicitly factored that insight into, and invoked it as justification for, what realists believe. Nonetheless, a new form of realism has. In response to a key historical threat, two of the most thoroughly developed contemporary versions of realism—one put forward by Jarrett Leplin, another by Stathis Psillos—are anchored on the sensible tactic of requiring that the theories to which realists commit themselves have no competitors. I argue, however, that the particular kind of non-competitor condition they invoke is illegitimate in the context of the realism debate. I contend further that invoking a non-competitor condition that is legitimate, sensible, and even, as it turns out, required in the context of the debate threatens to eliminate the possibility of scientific realism altogether. (shrink)

Roth's analysis of the Rationalitätstreit (i.e., the debate(s) about rationality) stands as one of the major works on how the debate affects a wide range of issues in the philosophy of science and the social sciences. His principal thesis is that the debate may be seen as a series of Quine-type "translation manuals," exhibiting characteristics of paradigms (following Kuhn 1970) that can be treated as testable scientific theories by adequate empirical tests. The author argues that Roth's notion of empirically testing (...) translation manuals is not possible given his criteria. He suggests a clearer definition of "methods" and develops a case whereby translation manuals can be adequately tested within an inductive model-but with rather severe restrictions. Implications are indicated. (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)

This position paper advocates combining formal epistemology and the new paradigm psychology of reasoning in the studies of conditionals and reasoning with uncertainty. The new paradigm psychology of reasoning is characterized by the use of probability theory as a rationality framework instead of classical logic, used by more traditional approaches to the psychology of reasoning. This paper presents a new interdisciplinary research program which involves both formal and experimental work. To illustrate the program, the paper discusses recent work on the (...) paradoxes of the material conditional, nonmonotonic reasoning, and Adams’ Thesis. It also identifies the issue of updating on conditionals as an area which seems to call for a combined formal and empirical approach. (shrink)

How is metaphysics related to the empirical sciences? Should metaphysics in general be guided by the sources, methods and results of the sciences? And what about the special case of the metaphysics of the social world: should it likewise be guided by the sources, methods and results of the social sciences? In her paper “Social Science as a Guide to Social Metaphysics?”, K. Hawley raises the question: If we are sympathetic to the project of naturalising metaphysics, how should we approach (...) the metaphysics of the social world? She proceeds by discussing three approaches to social metaphysics: inference to the best explanation from current social science, descriptive conceptual analysis, and normative, especially ‘ameliorative’ projects. At the end of her discussion, she reaches a rather pessimistic conclusion, especially as regards the IBE approach: “a number of phenomena indicate that the prospects for securely basing social metaphysics via inference to the best explanation from social science are currently faint. […] We need to look elsewhere if we are to develop a metaphysics of the social world.” In my comments on her paper, I try to re-animate the program of an inductive metaphysics by defending the idea that the method of inference to the best explanation should be the central method of justification for metaphysics in general and for social metaphysics in particular. (shrink)

It has recently been argued that a non-Bayesian probabilistic version of inference to the best explanation (IBE*) has a number of advantages over Bayesian conditionalization (Douven [2013]; Douven and Wenmackers [2017]). We investigate how IBE* could be generalized to uncertain evidential situations and formulate a novel updating rule IBE**. We then inspect how it performs in comparison to its Bayesian counterpart, Jeffrey conditionalization (JC), in a number of simulations where two agents, each updating by IBE** and JC, respectively, try to (...) detect the bias of a coin while they are only partially certain what side the coin landed on. We show that IBE** more often prescribes high probability to the actual bias than JC. We also show that this happens considerably faster, that IBE** passes higher thresholds for high probability, and that it in general leads to more accurate probability distributions than JC. (shrink)

We argued that explanatoriness is evidentially irrelevant in the following sense: Let H be a hypothesis, O an observation, and E the proposition that H would explain O if H and O were true. Then our claim is that Pr = Pr. We defended this screening-off thesis by discussing an example concerning smoking and cancer. Climenhaga argues that SOT is mistaken because it delivers the wrong verdict about a slightly different smoking-and-cancer case. He also considers a variant of SOT, called (...) “SOT*”, and contends that it too gives the wrong result. We here reply to Climenhaga’s arguments and suggest that SOT provides a criticism of the widely held theory of inference called “inference to the best explanation”. (shrink)