Scientific discourse is rife with passages that appear to be ordinary descriptions of systems of interest in a particular discipline. Equally, the pages of textbooks and journals are filled with discussions of the properties and the behavior of those systems. Students of mechanics investigate at length the dynamical properties of a system consisting of two or three spinning spheres with homogenous mass distributions gravitationally interacting only with each other. Population biologists study the evolution of one species procreating at a constant (...) rate in an isolated ecosystem. And when studying the exchange of goods, economists consider a situation in which there are only two goods, two perfectly rational agents, no restrictions on available information, no transaction costs, no money, and dealings are done immediately. Their surface structure notwithstanding, no competent scientist would mistake descriptions of such systems as descriptions of an actual system: we know very well that there are no such systems. These descriptions are descriptions of a model-system, and scientists use model-systems to represent parts or aspects of the world they are interested in. Following common practice, I refer to those parts or aspects as target-systems. What are we to make of this? Is discourse about such models merely a picturesque and ultimately dispensable façon de parler? This was the view of some early twentieth century philosophers. Duhem (1906) famously guarded against confusing model building with scientific theorizing and argued that model building has no real place in science, beyond a minor heuristic role. The aim of science was, instead, to construct theories, with theories understood as classificatory or representative structures systematically presented and formulated in precise symbolic.. (shrink)

What drives much of the current philosophical interest in the idea of group cognition is its appeal to the manifestation of psychological properties—understood broadly to include states, processes, and dispositions—that are in some important yet elusive sense emergent with respect to the minds of individual group members. Our goal in this paper is to address a set of related, conditional questions: If human mentality is real yet emergent in a modest metaphysical sense only, then: (i) What would it mean for (...) a group to have emergent cognitive states? (ii) Is this even a metaphysically coherent view? (iii) Relative to which notion of emergence do we have reason to believe that certain groups in fact have emergent cognitive states? We shall argue that evidence from a wide variety of social science domains makes it plausible that there are group cognitive states and processes no less metaphysically emergent than human cognitive (and other special science) states and processes. (shrink)

And this paper is an attempt to say precisely how, thus addressing a philosophical problem which is commonly taken to be a serious one. It does so, however, in quite an idiosyncratic way. It is based on the account of inductive schemes I have given in (1988) and (1990a) and on the conception of causation I have presented in (1980), (1983), and (1990b), and it intends to fill one of many gaps which have been left by these papers. Still, I (...) have tried to make this paper self-contained. Section 1 explains the philosophical question this paper is about; in more general terms it asks what might be meant by objectifying epistemic states or features of them and to which extent epistemic states can be objectified. The next sections introduce the basis I rely on with formal precision and some explanation; section 2 deals with induction and section 3 with causation. Within these confines, section 4 attempts to give an explication of the relevant sense of objectification and section 5 investigates the extent to which various features of epistemic states are objectifiable. The two most salient results are roughly that the relation "A is a reason for B" cannot be objectified at all and that the relation "A is a cause of B" can be objectified only under substantial, though reasonable restrictions. What has all of this to do with probability? A lot. The paper trades on a pervasive duality between probabilistic and deterministic epistemology, between a probabilistic representation of epistemic states together with a theory of probabilistic causation and another representation of epistemic states which I call deterministic because it lends itself, in a perfectly parallel fashion, to a theory of deterministic causation. Here I explicitly deal only with the deterministic side, but the duality should pave the way for further conclusions concerning objective probabilities and statistical laws. This outlook is briefly expanded in the final section 6. (shrink)

RésuméJe me penche sur un aspect de la philosophie sociale de Popper, à savoir les principes d'évaluation des interprétations historiques. Ma thèse globale est que suivant la perspective poppèrienne, notre choix parmi des interprétations historiques doit user d'au moins deux des critères qu'applique Popper au choix parmi diverses théories scientifiques : une interprétation devrait logiquement se prêter à une réfutation et elle devrait être consistante. Afin de montrer la pertinence et la fécondité de cette approche, je me concentre sur l'interprétation (...) historique des causes de la montée du nazisme que propose Erich Fromm, en particulier dansEscape from Freedom.Je montrerai que l'application de notions psychanalytiques dans le cadre de son interprétation historique a une valeur explicative faible, voire nulle. Son échec à expliquer certaines questions sociales tient à plusieurs raisons. Premièrement, l'auteur ne fournit pas, quoi qu'il en dise, d'explication causale convaincante. Ensuite, les concepts et les multiples hypotheèsesad hocauxquels il a recours tendent è rendre son interprétation irréfutable. Enfin, Fromm s'appuie sur des assomptions théoriques contradictoires. Mon analyse est basée sur la notion fondamentale de Popper voulant que la connaissance scientifique empirique exige au strict minimum une ouverture des interprétations historiques à la critique intersubjective. C'est cette exigence qui permet de les critiquer — c'est-à-dire les accepter, les réfuter et les corriger — sur une base rationnelle. (shrink)

Classifying is a fundamental operation in the acquisition of knowledge. Taxonomic theory can help students of cognition, evolutionary psychology, ethology, anatomy, and sociobiology to avoid serious mistakes, both practical and theoretical. More positively, it helps in generating hypotheses useful to a wide range of disciplines. Composite wholes, such as species and societies, are “individuals” in the logical sense, and should not be treated as if they were classes. A group of analogous features is a natural kind, but a group of (...) homologous features is not. Imposing hypotheses justified only on the basis of nominalist, realist, phenomenalist, or conceptualist metaphysics upon the neurophysiology of organisms or upon the causes of behavior exemplifies the “psychologist's fallacy” of William James. Levels should be distinguished from their members and from classes of levels, and the ontological status of entities ranked at levels should be made clear. It is important not to confuse such categories as substance and process with one another. Several genetical terms, such as “gene” and chromosome,” are even more equivocal than has been realized. Discussions about units of selection, behavior, and thinking suffer from the ambiguity of a “unit of” an entity. An important source of misunderstanding about natural selection is the habit of treating it as an “agent”: in an important sense, natural selection does not “act” at all. (shrink)

This is an introduction to the volume "Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations", edited by A. Reutlinger and J. Saatsi (OUP, forthcoming in 2017). -/- Explanations are very important to us in many contexts: in science, mathematics, philosophy, and also in everyday and juridical contexts. But what is an explanation? In the philosophical study of explanation, there is long-standing, influential tradition that links explanation intimately to causation: we often explain by providing accurate information about the causes of the (...) phenomenon to be explained. Such causal accounts have been the received view of the nature of explanation, particularly in philosophy of science, since the 1980s. However, philosophers have recently begun to break with this causal tradition by shifting their focus to kinds of explanation that do not turn on causal information. The increasing recognition of the importance of such non-causal explanations in the sciences and elsewhere raises pressing questions for philosophers of explanation. What is the nature of non-causal explanations - and which theory best captures it? How do non-causal explanations relate to causal ones? How are non-causal explanations in the sciences related to those in mathematics and metaphysics? This volume of new essays explores answers to these and other questions at the heart of contemporary philosophy of explanation. The essays address these questions from a variety of perspectives, including general accounts of non-causal and causal explanations, as well as a wide range of detailed case studies of non-causal explanations from the sciences, mathematics and metaphysics. (shrink)

Abductive reasoning assigns special status to the explanatory power of a hypothesis. But how do people make explanatory judgments? Our study clarifies this issue by asking: How does the explanatory power of a hypothesis cohere with other cognitive factors? How does probabilistic information affect explanatory judgments? In order to answer these questions, we conducted an experiment with 671 participants. Their task was to make judgments about a potentially explanatory hypothesis and its cognitive virtues. In the responses, we isolated three constructs: (...) Explanatory Value, Rational Acceptability, and Entailment. Explanatory judgments strongly cohered with judgments of causal relevance and with a sense of understanding. Furthermore, we found that Explanatory Value was sensitive to manipulations of statistical relevance relations between hypothesis and evidence, but not to explicit information about the prior probability of the hypothesis. These results indicate that probabilistic information about statistical relevance is a strong determinant of Explanatory Value. More generally, our study suggests that abductive and probabilistic reasoning are two distinct modes of inference. (shrink)

Reasons can play a variety of roles in a variety of contexts. For instance, reasons can motivate and guide us in our actions (and omissions), in the sense that we often act in the light of reasons. And reasons can be grounds for beliefs, desires and emotions and can be used to evaluate, and sometimes to justify, all these. In addition, reasons are used in explanations: both in explanations of human actions, beliefs, desires, emotions, etc., and in explanations of a (...) wide range of phenomena involving all sorts of animate and inanimate substances. This diversity has encouraged the thought that the term 'reason' is ambiguous or has different senses in different contexts. Moreover, this view often goes hand in hand with the claim that reasons of these different kinds belong to different ontological categories: to facts (or something similar) in the case of normative/justifying reasons, and to mental states in the case of motivating/explanatory reasons. In this paper I shall explore some of the main roles that reasons play and, on that basis, I shall offer a classification of kinds of reasons. As will become clear, my classification of reasons is at odds with much of the literature in several respects: first, because of my views about how we should understand the claim that reasons are classified into different kinds; second, because of the kinds into which I think reasons should be classified; and, finally, because of the consequences I think this view has for the ontology of reasons. (shrink)

Complex systems are to be seen as typically having multiple levels of organization. For instance, in the behavioural and cognitive sciences, there has been a long lasting trend, promoted by the seminal work of David Marr, putting focus on three distinct levels of analysis: the computational level, accounting for the What and Why issues, the algorithmic and the implementational levels specifying the How problem. However, the tremendous developments in neuroscience knowledge about processes at different scales of organization together with the (...) complexity of today cognitive theories suggest that there will hardly be only three levels of explanation. Instead, there will be many different degrees of commitments corresponding to the different granularities—from high-level (behavioural) models to low-level (neural and molecular) models of the cognitive research program. For instance, Bayesian approaches, that are usually advocated for formalizing Marr’s computational level and rational behaviour, have even been adopted to model synaptic plasticity and axon guidance by molecular gradients. As a result, we can consider the behavioural scientist as dealing with models at a multiplicity of levels. The purpose of this Research Topic in Frontiers in Theoretical and Philosophical Psychology is to promote an approach to the role of the levels and explanation and models which is of interest for cognitive scientists, neuroscientists, psychologists, behavioural scientists, and philosophers of science. (shrink)

This paper argues that the form of explanation at issue in the hard problem of consciousness is scientifically irrelevant, despite appearances to the contrary. In particular, it is argued that the 'sense of understanding' that plays a critical role in the form of explanation implicated in the hard problem provides neither a necessary nor a sufficient condition on satisfactory scientific explanation. Considerations of the actual tools and methods available to scientists are used to make the case against it being a (...) necessary condition, and work by J.D. Trout that exploits psychological research on the hindsight and overconfidence biases is used to show that it is not a sufficient condition. It is argued, however, that certain intellectual and moral concerns give us good reason to still try to meet the hard problem's explanatory challenge, despite its extrascientific nature. (shrink)

This article defends the use of interventionist counterfactuals to elucidate causal and explanatory claims against criticisms advanced by James Bogen and Peter Machamer. Against Bogen, I argue that counterfactual claims concerning what would happen under interventions are meaningful and have determinate truth values, even in a deterministic world. I also argue, against both Machamer and Bogen, that we need to appeal to counterfactuals to capture the notions like causal relevance and causal mechanism. Contrary to what both authors suppose, counterfactuals are (...) not "unscientific" - a substantial tradition within statistics and the causal modelling literature makes heavy use of them. (shrink)

What is understanding? My goal in this paper is to lay out a new approach to this question and clarify how that approach deals with certain issues. The claim is that understanding is a matter of compressing information about the understood so that it can be mentally useful. On this account, understanding amounts to having a representational kernel and the ability to use it to generate the information one needs regarding the target phenomenon. I argue that this ambitious new account (...) can accommodate much of the data that has motivated theories of understanding in philosophy of science, and can also be generally applicable in epistemology and daily life as well. (shrink)

Do component forces exist in conjoined circumstances? Cartwright (1980) says no; Creary (1981) says yes. I'm inclined towards Cartwright's side in this matter, but find several problems with her argumentation. My primary aim here is to present a better, distinctly causal, argument against component forces: very roughly, I argue that the joint posit of component and resultant forces in conjoined circumstances gives rise to a threat of causal overdetermination, avoidance of which best proceeds via eliminativism about component forces. A secondary (...) aim is to show that rejecting component forces does not require, pace Cartwright, rejecting certain attractive theses about what laws of nature express and the role such laws play in scientific explanations. (shrink)

How should physical entities be characterized? Physicalists, who have most to do with the notion, usually characterize the physical by reference to two components: 1. The physical entities are the entities treated by fundamental physics with the proviso that 2. Physical entities are not fundamentally mental (that is, do not individually possess or bestow mentality) Here I explore the extent to which the appeals to fundamental physics and to the NFM (“no fundamental mentality”) constraint are appropriate for characterizing the physical, (...) especially for purposes of formulating physicalism. Ultimately, I motivate and defend a version of an account incorporating both components: The physics-based NFM account: An entity existing at a world w is physical iff (i) it is treated, approximately accurately, by current or future (in the limit of inquiry, ideal) versions of fundamental physics at w, and (ii) it is not fundamentally mental (that is, does not individually either possess or bestow mentality). (shrink)

Many philosophers now regard causal approaches to explanation as highly promising, even in physics. This is due in large part to James Woodward's influential argument that a wide variety of scientific explanations are causal, based on his interventionist approach to causation. This article argues that some derivations describing causal relations and satisfying Woodward's criteria for causal explanation fail to be explanatory. Further, causal relations are unnecessary for a range of explanations, widespread in physics, involving highly idealized models. These constitute significant (...) limitations on the scope of causal explanation. We have good reason to doubt that causal explanation is as widespread or important in physics as Woodward and other proponents maintain. (shrink)

Here I consider the relative merits of two recent models of explanation, James Woodward's interventionist-counterfactual model and the model model. According to the former, explanations are largely constituted by information about the consequences of counterfactual interventions. Problems arise for this approach because countless relevant interventions are possible in most cases and because it overlooks other kinds of equally relevant information. According the model model, explanations are largely constituted by cognitive models of actual mechanisms. On this approach, explanations tend not to (...) represent any of the aforementioned information explicitly but can instead be used to produce it on demand. The model model thus offers the more plausible account of the information of which we are aware when we have an explanation and of the ratiocinative process through which we derive many kinds of information that are relevant to the evaluation of explanations. (shrink)

Spinoza is most often seen as a stern advocate of mechanistic efficient causation, but examining his philosophy in relation to the Aristotelian tradition reveals this view to be misleading: some key passages of the Ethics resemble so much what Surez writes about emanation that it is most natural to situate Spinoza's theory of causation not in the context of the mechanical sciences but in that of a late scholastic doctrine of the emanative causality of the formal cause; as taking a (...) look at the seventeenth-century philosophy of mathematics reveals, this is in consonance also with Spinoza's geometrical cast of mind. Against this background, I examine Spinoza's essentialist model of causation according to which each thing has a formal character determined by the thing's essence and what follows from that essence. In the case of real things this essential causal architecture results in efficacy, i.e. in bringing about real effects, the key idea being that without the essential, formally structured causal thrust there would be no efficacy in the first place. I also explain how this model accounts for efficient causation taking place between finite things. (shrink)

Pluralism with respect to the structure of explanations of facts is not uncommon. Wesley Salmon, for instance, distinguished two types of explanation: causal explanations (which provide insight in the causes of the fact we want to explain) and unification explanations (which fit the explanandum into a unified world view). The pluralism which Salmon and others have defended is compatible with several positions about the exact relation between these two types of explanations. We distinguish four such positions, and argue in favour (...) of one of them. We also compare our results with the views of some authors who have recently written on this subject. (shrink)

I provide a brief history of pragmatics as it relates to explanation, highlighting the great neglect of pragmatics and pragmatic considerations in regard to explanation during the mid-twentieth century. In order to understand pragmatic considerations regarding explanation, I utilize the work of Bas C. van Fraassen, Peter Achinstein, and Jan Faye. These thinkers provide crucial tools for understanding pragmatics, especially with regard to concepts such as context and exigence. The work of these thinkers provides the platform from which I compose (...) a definition of pragmatic considerations. (shrink)

John Dewey provided a robust and thorough conception of scientific explanation within his philosophical writing. I provide an exegesis of Dewey's concept of scientific explanation and argue that this concept is important to contemporary philosophy of science for at least two reasons. First, Dewey's conception of scientific explanation avoids the reification of science as an entity separated from practical experience. Second, Dewey supplants the realist-antirealist debate within the philosophical literature concerning explanation, thus moving us beyond the current stalemate within philosophy (...) of science. (shrink)

Psychologists take two propositions for granted. Specifically, empirical verification of predictions derived from a theory support that the theory is more likely to be true and support that additional predictions derived from the theory have an increased probability of being sustained if subjected to empirical testing. In contrast, I argue that both propositions depend strongly on whether auxiliary assumptions are taken into account. When auxiliary assumptions are not taken into account, the first proposition is valid but the second is not. (...) When auxiliary assumptions are taken into account, the first proposition is not valid, and the second proposition encounters additional problems. I use Venn diagrams and Bayesian principles to demonstrate these conclusions. (shrink)

This paper develops an account of metaphysical explanation according to which metaphysical explanations are answers to what-makes-it-the-case-that questions. On this view, metaphysical explanations are not to be considered entirely objective, but are subject to epistemic constraints imposed by the context in which a relevant question is asked. The resultant account of metaphysical explanation is developed independently of any particular views about grounding. Toward the end of the paper an application of the view is proposed that takes metaphysical explanations conceived in (...) this way to characterize reality's structure. According to this proposal, reality's structure is partly constituted by a projection of our explanatory practices onto reality. (shrink)

Mechanistic explanation is at present the received view of scientific explanation. One of its central features is the idea that mechanistic explanations are both “downward looking” and “upward looking”: they explain by offering information about the internal constitution of the mechanism as well as the larger environment in which the mechanism is situated. That is, they offer both constitutive and contextual explanatory information. Adequate mechanistic explanations, on this view, accommodate the full range of explanatory factors both “above” and “below” the (...) target phenomenon. The aim of this paper is to demonstrate that mechanistic explanation cannot furnish both constitutive and contextual information simultaneously, because these are different types of explanation with distinctly different aims. Claims that they can, I argue, depend on several intertwined confusions concerning the nature of explanation. Particularly, such claims tend to conflate mechanistic and functional explanation, which I argue ought to be understood as distinct. Conflating them threatens to oversell the explanatory power of mechanisms and obscures the means by which they explain. I offer two broad reasons in favor of distinguishing mechanistic and functional explanation: the first concerns the direction of explanation of each, and the second concerns the type of questions to which these explanations offer answers. I suggest an alternative picture on which mechanistic explanation is understood as fundamentally constitutive, and according to which an adequate understanding of a phenomenon typically requires supplementing the mechanistic explanation with a functional explanation. (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)

My thesis is that you can lie with ‘ P therefore Q ’ without P or Q being lies. For you can lie by virtue of not believing that P supports Q. My thesis is reconciled with the principle that all lies are assertions through H. P. Grice’s account of conventional implicatures. These semantic cousins of conversational implicatures are secondary assertions that clarify the speaker’s attitude toward his primary assertions. The meaning of ‘therefore’ commits the speaker to an entailment thesis (...) even though the speaker does not enter that commitment into the text. Insincere conventional implicatures are akin to insincerely asserted footnotes. An absence of lies in the text is compatible with the presence of lies in the meta-text. (shrink)

Richard Boyd and Nicholas Sturgeon develop distinctive naturalistic arguments for scientific realism and moral realism. Each defends a realist position by an inference to the best explanation. In this paper, I suggest that these arguments for realism should be reformulated, with the law of likelihood replacing inference to the best explanation. The resulting arguments for realism do not work.

When philosophers discuss the topic of explanation, they usually have in mind the following question: given the beliefs one has and some proposition that one wishes to explain, which subset of the beliefs constitutes an explanation of the target proposition? That is, the philosophical ‘problem of explanation’ typically has bracketed the issue of how one obtains the beliefs; they are taken as given. The problem of explanation has been the problem of understanding the relation ‘x explains y’. Since Hempel did (...) so much to canonize this way of thinking about explanation, it deserves to be called ‘Hempel's problem’. (shrink)

?Those ice cubes melted because by melting total entropy increased and entropy increase has a very high objective chance.? What role does the chance in this explanation play? I argue that it contributes to the explanation by entailing that the melting was almost necessary, and defend the claim that the fact that some event was almost necessary can, in the right circumstances, constitute a causal explanation of that event.

Philosophers have proposed many alleged examples of non-causal explanations of particular events. I discuss several well-known examples and argue that they fail to be non-causal. 1 Questions2 Preliminaries3 Explanations That Cite Causally Inert Entities4 Explanations That Merely Cite Laws I5 Stellar Collapse6 Explanations That Merely Cite Laws II7 A Final Example8 Conclusion.

Philosophers have proposed many alleged examples of non-causal explana- tions of particular events. I discuss several well-known examples and argue that they fail to be non-causal.

In this paper I propose to examine, and in part revive, a time-honoured perspective to inquiry in general and scientific explanation in particular. The perspective is to view inquiry as a search for answers to questions. If there is anything that deserves to be called a working scientist's view of his or her daily work, it surely is that he or she phrases questions and attempts to find satisfactory answers to them.

Darwin'suse of final cause accords with the Aristotelian idea of finalcauses as explanatory types – as opposed to mechanical causes, which arealways particulars. In Wright's consequence etiology, anadaptation is explained by particular events, namely, its past consequences;hence, that etiology is mechanistic at bottom. This justifies Ghiselin'scharge that such versions of teleology trivialize the subject, But a purelymechanistic explanation of an adaptation allows it to appear coincidental.Patterns of outcome, whether biological or thermodynamic, cannot be explainedbytracing causal chains, even were that possible. (...) They are explicanda of aspecialkind. The form of their explanation, in statistical mechanics or by naturalselection, is not captured by statistical variants of the covering-law model orrelated models of explanation. In them as in classical teleology, types ofoutcome are cited to explain why there are outcomes of those types. But onlywhen types are explanatory by being selected for, as inexplanations of animal and human behavior as well as in Darwin's theory ofnatural selection, but not in statistical mechanics, is the explanationteleological. Darwin's theory is nontrivially teleological. (shrink)

Various claims regarding intertheoretic reduction, weak and strong notions of emergence, and explanatory fictions have been made in the context of first-order thermodynamic phase transitions. By appealing to John Norton’s recent distinction between approximation and idealization, I argue that the case study of anyons and fractional statistics, which has received little attention in the philosophy of science literature, is more hospitable to such claims. In doing so, I also identify three novel roles that explanatory fictions fulfill in science. Furthermore, I (...) scrutinize the claim that anyons, as they are ostensibly manifested in the fractional quantum Hall effect, are emergent entities and urge caution. Consequently, it is suggested that a particular notion of strong emergence signals the need for the development of novel physical–mathematical research programs. (shrink)

ENGLISH ABSTRACT: Basic statements play a central role in Popper's "The Logic of Scientific Discovery", since they permit a distinction between empirical and non-empirical theories. A theory is empirical iff it consists of falsifiable statements, and statements (of any kind) are falsifiable iff they are inconsistent with at least one basic statement. Popper obviously presupposes that basic statements are themselves empirical and hence falsifiable; at any rate, he claims several times that they are falsifiable. In this paper we prove that (...) no basic statement is falsifiable, if the term 'basic statement' is to be understood according to Popper's definitions of that term. More precisely, we prove not only that no Popperian basic statement in the narrow sense of the word is falsifiable, but also that no Popperian basic statement in the broader sense, and even in the broadest possible sense, is falsifiable. This leads to the paradoxical result that, according to Popper's definitions of 'basic statement', the basis of the empirical sciences is not itself empirical. Furthermore, we point out a similar paradox as regards Popper's falsifiability scheme for theories. We close with a look at possibilities for overcoming these paradoxes. DEUTSCHE ZUSAMMENFASSUNG: Basissätze spielen eine zentrale Rolle in Poppers Logik der Forschung, denn sie erlauben die Unterscheidung zwischen empirischen und nichtempirischen Theorien: Eine Theorie ist empirisch genau dann, wenn sie aus falsifizierbaren Aussagesätzen besteht, und Aussagesätze (beliebiger Art) sind falsifizierbar genau dann, wenn sie mindestens einem Basissatz widersprechen. Popper setzt offensichtlich voraus, dassŸ die Basissätze selbst empirisch und somit falsifizierbar sind. Jedenfalls behauptet er mehrmals ihre Falsifizierbarkeit. Wir beweisen in unserem Aufsatz, dassŸ die Basissätze nicht falsifizierbar sind, und wir beweisen dies nicht nur für Poppersche Basissätze im engeren Sinn, sondern auch für Poppersche Basissätze im weiteren Sinn und schlieߟlich für Poppersche Basissätze im weitesten, mit den Vorstellungen Poppers gerade noch verträglichen Sinn. Dies führt zu dem paradoxen Ergebnis, dass nach Poppers eigenen methodologischen Postulaten die Basis der empirischen Wissenschaften nicht selbst empirisch ist. Darüber hinaus entwickeln wir ein ähnliches Paradoxon bezüglich Poppers Falsifizierbarkeitsschema für Theorien. Zum AbschlussŸ unseres Aufsatzes betrachten wir einige Möglichkeiten, die von uns entdeckten Paradoxa zu überwinden. (shrink)