The evidential role of experience in justifying beliefs has been at the center of debate in philosophy in recent years. One view is that experience, or seeming, can confer immediate justification on belief in virtue of its representational phenomenology. Call this view “representational dogmatism.” Another view is that experience confers immediate justification on belief in virtue of its relational phenomenology. Call this view “relational dogmatism.” The goal of this paper is to pit these two versions of dogmatism against each other (...) in terms of their ability to account for ampliative, or non-deductive, inferential justification. I will argue that only the representational view can provide a plausible account of this type of justification. (shrink)

Wesley Salmon's account of induction in terms of Bayesian priors and account of Popper is criticized in terms of Joseph Agassi's account.

An inference to a new explanation may be both logically non-ampliative and epistemically ampliative. Included among the premises of the latter form is the explanadum--a unique premise which is capable of embodying what we do not know about the matter in question, as well as legitimate aspects of what we do know. This double status points to a resolution of the Meno paradox. Ampliative inference of this sort, it is argued, has much in common with (...) Nickles' idea of discoverability and, together with the mapping and correction procedures (briefly summarized) required for such inference, may suggest a broadening of the concept of justification which would incorporate much of what has been defended in theories of discovery. (shrink)

Let two events A, B be given. We consider probability distributions over the partition P = {A ∩ B, A ∩ ¯ B, ¯ A ∩ B, ¯ A ∩ ¯ B}. By a “constraint” is meant a probabilistically coherent set of statements each of the form Prob(E) = x, where E is a subset of P . Let C be the class of constraints. By a “method of ampliative inference” is meant any total function M from C (...) to the class of probability distributions over P , provided that M has the following property. (shrink)

The ampliativity of deduction has been defended in several ways—such as the semi-decidability of the theories, the surprise of unexpected consequences, the need of new individuals in deduction, or ampliative inference as deduction with suppressed premises (Dummett, Frege. Philosophy of mathematics. Duckworth, London, 1991; Hintikka, Logic, language-games and information. Oxford University Press, Oxford, 1973; Musgrave, Imre Lakatos and theories of scientific change. Kluwer, Boston, 1989; Rota, Indiscrete thoughts. Birkhäuser, Boston, 1997). These lines of defensive arguments fail if we (...) characterize ampliativity in a strong way, that is, in terms of ‘novelty’ stricto sensu, as an inferential process producing genuinely new pieces of information in the conclusion of a reasoning (Cellucci, Rethinking logic. Springer, Dordrecht, 2013; Ippoliti, Heuristic reasoning. Springer, Basel, 2015). Nevertheless, it is possible to defend a weaker stance of the ampliativity of deduction and its usefulness. This requires interpreting novelty more loosely, that is, as the inferential production of new relations among known entities. This stance maintains that, in this sense, deduction can provide us with new knowledge. Thus, a typical deductive activity, as re-proving theorems, can be thought as heuristic and ampliative because it establishes new relations between known elements (e.g. between given axioms or properties and the statement of the theorem). I argue that also this line of defence is defective for it does not account for the necessity and usefulness of reproving theorems. In particular, a foundationalist, axiomatic-deductive viewpoint does not fully account for the usefulness and the weak ampliative power of deduction. (shrink)

Abstract In Peirce's and Hanson's characterization of abductive inference, the abducted hypothesis (but not others) is present in the premises, so that the inference can hardly be taken as ampliative. Abduction has consequently been treated as part of the process whereby already generated hypotheses are judged in terms of their plausibility, simplicity, etc. I propose an interpretation of abduction which supports an ampliative view. It relies on a distinction between two logical stages in the generation of (...) hypotheses, one ?factual? and one ?explanatory?. I also indicate how we may reconstruct Peirce's and Hanson's original inference in an ampliative form. (shrink)

In previous work, we studied four well known systems of qualitative probabilistic inference, and presented data from computer simulations in an attempt to illustrate the performance of the systems. These simulations evaluated the four systems in terms of their tendency to license inference to accurate and informative conclusions, given incomplete information about a randomly selected probability distribution. In our earlier work, the procedure used in generating the unknown probability distribution (representing the true stochastic state of the world) tended (...) to yield probability distributions with moderately high entropy levels. In the present article, we present data charting the performance of the four systems when reasoning in environments of various entropy levels. The results illustrate variations in the performance of the respective reasoning systems that derive from the entropy of the environment, and allow for a more inclusive assessment of the reliability and robustness of the four systems. (shrink)

Explanations in genetics have intriguing aspects to both biologists and philosophers, and there is no account that satisfactorily elucidates such explanations. The aim of this article is to analyze the kind of explanations usually given in Classical (Transmission) Genetics (CG) and to present in detail the application of an account of explanation as ampliative, specialized nomological embedding to elucidate the such explanations. First, we present explanations in CG in the classical format of inferences with the explanans as the premises (...) and the explanandum as the conclusion and compare them with explanations in other paradigmatic explanatory fields such as Classical Mechanics. Second, we summarize the main aspects discussed in the literature with regard the peculiarities of genetic explanations. Third, we introduce the account of scientific explanation as ampliative, specialized nomological embedding making use of Sneedian structuralism, in particular the notions of theory-net, fundamental law or guiding principle, specialization, and special laws. Finally, we apply this account to the case of CG and show that this analysis sheds light to the intriguing aspects of genetic explanations and remove most of their alleged oddities. (shrink)

Inference to the Best Explanation (IBE) is widely criticized for being an unreliable form of ampliative inference – partly because the explanatory hypotheses we have considered at a given time may all be false, and partly because there is an asymmetry between the comparative judgment on which an IBE is based and the absolute verdict that IBE is meant to license. In this paper, I present a further reason to doubt the epistemic merits of IBE and argue (...) that it motivates moving to an inferential pattern in which IBE emerges as a degenerate limiting case. Since this inferential pattern is structurally similar to an argumentative strategy known as Inferential Robustness Analysis (IRA), it effectively combines the most attractive features of IBE and IRA into a unified approach to non-deductive inference. (shrink)

Our purpose in this paper is to contribute to a practice-based characterization of scientific inference. We want to explore whether Brandom’s pragmatist–inferentialist framework can suitably accommodate several types of ampliative inference common in scientific reasoning and explanation (probabilistic reasoning, abduction and idealisation). First, we argue that Brandom’s view of induction in terms of merely permissive inferences is inadequate; in order to overcome the shortcoming of Brandom’s proposal, we put forward an alternative conception of inductive, probabilistic reasoning by (...) appeal to the notion of degrees of commitment. Moreover, we examine the sorts of inferential commitments operative in other types of ampliative inferences, such as abduction or reasoning involving idealizations and assumptions. We suggest that agents engaging in these forms of reasoning often undertake restricted inferential commitments, whose scope and reach are more limited that in the case of the commitments associated with full beliefs. (shrink)

Our purpose in this paper is to contribute to a practice-based characterization of scientific inference. We want to explore whether Brandom’s pragmatist–inferentialist framework can suitably accommodate several types of ampliative inference common in scientific reasoning and explanation (probabilistic reasoning, abduction and idealisation). First, we argue that Brandom’s view of induction in terms of merely permissive inferences is inadequate; in order to overcome the shortcoming of Brandom’s proposal, we put forward an alternative conception of inductive, probabilistic reasoning by (...) appeal to the notion of degrees of commitment. Moreover, we examine the sorts of inferential commitments operative in other types of ampliative inferences, such as abduction or reasoning involving idealizations and assumptions. We suggest that agents engaging in these forms of reasoning often undertake restricted inferential commitments, whose scope and reach are more limited that in the case of the commitments associated with full beliefs. (shrink)

I argue against the tendency in the philosophy of science literature to link abduction to the inference to the best explanation (IBE), and in particular, to claim that Peireean abduction is a conceptual predecessor to IBE. This is not to discount either abduction or IBE. Rather the purpose of this paper is to clarify the relation between Peireean abduction and IBE in accounting for ampliative inference in science. This paper aims at a proper classification—not justification—of types of (...) scientific reasoning. In particular, I claim that Peireean abduction is an in-depth account of the process of generating explanatory hypotheses, while IBE, at least in Peter Lipton's thorough treatment, is a more encompassing account of the processes both of generating and of evaluating scientific hypotheses. There is then a two-fold problem with the claim that abduction is IBE. On the one hand, it conflates abduction and induction, which are two distinct forms of logical inference, with two distinct aims, as shown by Charles S. Peirce; on the other hand it lacks a clear sense of the full scope of IBE as an account of scientific inference. (shrink)

For Peirce, logic is essentially illative, a relation of inferential growth. It follows that inference and argumentation are essentially ecstatic, an asymmetrical, ampliative movement from antecedent to consequent. It also follows that logic is inherently inductive. While deduction remains an essential and irreplaceable aspect of logic, it should be seen as a more abstract expression of the illative, semiological essence of inference as such.

The usual, comparative, conception of inference to the best explanation (IBE) takes it to be ampliative. In this paper I propose a conception of IBE ('Holmesian inference') that takes it to be a species of eliminative induction and hence not ampliative. This avoids several problems for comparative IBE (for example, how could it be reliable enough to generate knowledge?). My account of Holmesian inference raises the suspicion that it could never be applied, on the grounds (...) that scientific hypotheses are inevitably underdetermined by the evidence (i.e. are inevitably ampliative). I argue that this concern may be resisted by acknowledging, as Timothy Williamson has shown, that all knowledge is evidence. The latter suggests an approach to resisting scepticism different from those (e.g. the reliabilist approach) that embrace fallibilism. (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)

A possible way out to Kripke’s Puzzle About Belief could start from the rejection of the notion of epistemic transparency. Epistemic transparency seems, indeed, irremediably incompatible with an externalist conception of mental content. However, Brandom’s inferentialism could be considered a version of externalism that allows, at least in some cases, to save the principle of transparency. Appealing to a normative account of the content of our beliefs, from the inferentialist’s standpoint, it is possible to state that a content is transparent (...) when name-components of that content are a priori associated with some application conditions and, at the same time, reflection alone provides an a priori access to those application conditions, with no need of any empirical investigation. Nevertheless, such requirements are only met in trivial cases. The aim of this paper is to argue that some application conditions of that sort, albeit trivial, can be ontologically ampliative. As a result, the related contents can be regarded as transparent in a substantial and rich way. (shrink)

This book by one of the world's foremost philosophers in the fields of epistemology and logic offers an account of suppositional reasoning relevant to practical deliberation, explanation, prediction and hypothesis testing. Suppositions made 'for the sake of argument' sometimes conflict with our beliefs, and when they do, some beliefs are rejected and others retained. Thanks to such belief contravention, adding content to a supposition can undermine conclusions reached without it. Subversion can also arise because suppositional reasoning is ampliative. These (...) two types of nonmonotonic logic are the focus of this book. A detailed comparison of nonmonotonicity appropriate to both belief contravening and ampliative suppositional reasoning reveals important differences that have been overlooked. (shrink)

In this article, I explore the compatibility of inference to the best explanation (IBE) with several influential models and accounts of scientific explanation. First, I explore the different conceptions of IBE and limit my discussion to two: the heuristic conception and the objective Bayesian conception. Next, I discuss five models of scientific explanation with regard to each model’s compatibility with IBE. I argue that Kitcher’s unificationist account supports IBE; Railton’s deductive–nomological–probabilistic model, Salmon’s statistical-relevance model, and van Fraassen’s erotetic account (...) are incompatible with IBE; and Salmon’s causal–mechanical model is merely consistent with IBE. In short, many influential models of scientific explanation do not support IBE. I end by outlining three possible conclusions to draw: (1) either philosophers of science or defenders of IBE have seriously misconstrued the concept of explanation, (2) philosophers of science and defenders of IBE do not use the term ‘explanation’ univocally, and (3) the ampliative conception of IBE, which is compatible with any model of scientific explanation, deserves a closer look. (shrink)

This article examines the current justifications of deductive inferences, and finds them wanting. It argues that this depends on the fact that all such justification take no account of the role deductive inferences play in knowledge. Alternatively, the article argues that a justification of deductive inferences may be given in terms of the fact that they are non-ampliative, in the sense that the content of the conclusion is merely a reformulation of the content of the premises. Some possible objections (...) to this view are discussed and found inadequate. (shrink)

The paper begins by focusing the basic idea that Gestalt phenomena belong not only to the realm of perception but to the realm of inference. It is shown that Gestalt effects often occur both in counterfactual and in ampliative – i.e. inductive and abductive – reasoning. The main thesis of the paper is that the common feature of such forms of non-deductive reasoning is provided by a rational selection between incompatible conclusions, where rationality lies in the choice of (...) the alternative which preserves the maximum of background information. It is also stressed a distinction between a weak and a strong notion of incompatibility. Such distinction may help in giving account of some alleged Gestalt phenomena which have been recognized in theory construction and theory change. (shrink)

Systems of logico-probabilistic (LP) reasoning characterize inference from conditional assertions interpreted as expressing high conditional probabilities. In the present article, we investigate four prominent LP systems (namely, systems O, P, Z, and QC) by means of computer simulations. The results reported here extend our previous work in this area, and evaluate the four systems in terms of the expected utility of the dispositions to act that derive from the conclusions that the systems license. In addition to conforming to the (...) dominant paradigm for assessing the rationality of actions and decisions, our present evaluation complements our previous work, since our previous evaluation may have been too severe in its assessment of inferences to false and uninformative conclusions. In the end, our new results provide additional support for the conclusion that (of the four systems considered) inference by system Z offers the best balance of error avoidance and inferential power. Our new results also suggest that improved performance could be achieved by a modest strengthening of system Z. (shrink)

As it is standardly conceived, Inference to the Best Explanation (IBE) is a form of ampliative inference in which one infers a hypothesis because it provides a better potential explanation of one’s evidence than any other available, competing explanatory hypothesis. Bas van Fraassen famously objected to IBE thus formulated that we may have no reason to think that any of the available, competing explanatory hypotheses are true. While revisionary responses to the Bad Lot Objection concede that IBE (...) needs to be reformulated in light of this problem, reactionary responses argue that the Bad Lot Objection is fallacious, incoherent, or misguided. This paper shows that the most influential reactionary responses to the Bad Lot Objection do nothing to undermine the original objection. This strongly suggests that proponents of IBE should focus their efforts on revisionary responses, i.e. on finding a more sophisticated characterization of IBE for which the Bad Lot Objection loses its bite. (shrink)

Dogmatism holds that an experience or seeming that p can provide prima facie immediate justification for believing p in virtue of its phenomenology. Dogmatism about perceptual justification has appealed primarily to proponents of representational theories of perceptual experience. Call dogmatism that takes perceptual experience to be representational "representational phenomenal dogmatism." As we show, phenomenal seemings play a crucial role in dogmatism of this kind. Despite its conventional appeal to representational theorists, dogmatism is not by definition committed to any particular view (...) of perceptual experience. Naive realists and disjunctivists who hold that perceptual experience is a perceptual relation of direct acquaintance can also endorse dogmatism. Indeed, we argue that they ought to do so. Otherwise, they cannot maintain that relationalism about perceptual experience has an epistemic advantage compared to the representational view. We then show that even if we grant that relationalism has this advantage, only dogmatism that takes perceptual experience to be representational can be extended to account for non-deductive inferential justification. As an account of the latter is required to avoid succumbing to skepticism, relationalism, we argue, does not have the epistemic advantage its defenders claim it has. (shrink)

This paper considers how explanatory factors can play a role in our ampliative inferential practices. Van Fraassen has argued that there is no possible rational rule that governs ampliative inferences and includes weightings for explanatory beauty. In opposition to van Fraassen, Douven has argued that ampliative inferential rules that include weightings for explanatory factors can be rationally followed. There is, however, a crucial difficulty with Douven's approach: applying the ampliative rule that he suggests leads into irrational (...) belief states. A way to remove the difficulties with Douven's account is suggested. The implications of rationally including explanatory factors in ampliative inferences are then considered. Introduction The proposed interpretations Van Fraassen's justification of the Bayesian approach A rational non-Bayesian interpretation? Further restrictions on D(A,B) Conclusion. (shrink)

In ‘Induction and Natural Kinds’, I proposed a solution to the problem of induction according to which our use of inductive inference is reliable because it is grounded in the natural kind structure of the world. When we infer that unobserved members of a kind will have the same properties as observed members of the kind, we are right because all members of the kind possess the same essential properties. The claim that the existence of natural kinds is what (...) grounds reliable use of induction is based on an inference to the best explanation of the success of our inductive practices. As such, the argument for the existence of natural kinds employs a form of ampliative inference. But induction is likewise a form of ampliative inference. Given both of these facts, my account of the reliability of induction is subject to the objection that it provides a circular justification of induction, since it employs an ampliative inference to justify an ampliative inference. In this paper, I respond to the objection of circularity by arguing that what justifies induction is not the inference to the best explanation of its reliability. The ground of induction is the natural kinds themselves. (shrink)

This monograph attempts to clarify one significant but much neglected aspect of Peirce's contribution to the philosophy of science. It was written in 1963 as my M. A. thesis at the Uni versity of Illinois. Since the topic is still neglected it is hoped that its pUblication will be of use to Peirce scholars. I should like to acknowledge my indebtedness to Dr. Max Fisch who broached this topic to me and who advised me con tinuously through its development, assisting (...) generously with his own insights and unpublished Peirce manuscripts. TABLE OF CONTENTS INTRODUCTION 1. A Current Issue in the Philosophy of Science 1 2. Peirce and His Theory of Abduction 5 3. The General Character of Abduction 7 PART I: THE EARLY THEORY 1. Peirce's Earliest Conception of Inference 11 2. Three Kinds of Inference and Three Figures of Syllogism 13 3. Ampliative Inference and Cognition 17 4. Induction and Hypothesis 20 5. The Method of Methods 23 PART II: THE LATER THEORY 1. The Transitional Period 28 2. Three Stages of Inquiry 31 3. Abduction and Guessing Instinct 35 4. Logic as a Normative Science 38 5. Hypothesis Construction and Selection 41 6. Abduction and Pragmatism 44 7. Economy of Research 47 8. Justification of Abduction 51 CONCLUSION 55 61 BIBLIOGRAPHY INTRODUCTION 1. (shrink)

There have recently been a number of strong claims that normative considerations, broadly construed, influence many philosophically important folk concepts and perhaps are even a constitutive component of various cognitive processes. Many such claims have been made about the influence of such factors on our folk notion of causation. In this paper, we argue that the strong claims found in the recent literature on causal cognition are overstated, as they are based on one narrow type of data about a particular (...) type of causal cognition; the extant data do not warrant any wide-ranging conclusions about the pervasiveness of normative considerations in causal cognition. Of course, almost all empirical investigations involve some manner of ampliative inference, and so we provide novel empirical results demonstrating that there are types of causal cognition that do not seem to be influenced by moral considerations. (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)

This book explores new findings on the long-neglected topic of theory construction and discovery, and challenges the orthodox, current division of scientific development into discrete stages: the stage of generation of new hypotheses; the stage of collection of relevant data; the stage of justification of possible theories; and the final stage of selection from among equally confirmed theories. The chapters, written by leading researchers, offer an interdisciplinary perspective on various aspects of the processes by which theories rationally should, and descriptively (...) are, built. They address issues such as the role of problem-solving and heuristic reasoning in theory-building; how inferences and models shape the pursuit of scientific knowledge; the relation between problem-solving and scientific discovery; the relative values of the syntactic, semantic, and pragmatic view of theories in understanding theory construction; and the relation between ampliative inferences, heuristic reasoning, and models as a means for building new theories and knowledge. Through detailed arguments and examinations, the volume collectively challenges the orthodox view’s main tenets by characterizing the ways in which the different “stages” are logically, temporally, and psychologically intertwined. As a group, the chapters provide several attempts to answer long-standing questions about the possibility of a unified conceptual framework for building theories and formulating hypotheses. (shrink)

Second, there is a form of ampliative inference that has come to be called ‘inference to the best explanation,’ or more briefly ‘explanatory inference.’ Roughly: From the fact that a certain hypothesis would explain the data at hand better than any other available hypothesis, we infer with some degree of confidence that that leading hypothesis is correct. There is no question but that this inference is often performed. Arguably, every human being performs it many times (...) in a day, perhaps without letup. (shrink)

Arguably, Hume's greatest single contribution to contemporary philosophy of science has been the problem of induction (1739). Before attempting its statement, we need to spend a few words identifying the subject matter of this corner of epistemology. At a first pass, induction concerns ampliative inferences drawn on the basis of evidence (presumably, evidence acquired more or less directly from experience)—that is, inferences whose conclusions are not (validly) entailed by the premises. Philosophers have historically drawn further distinctions, often appropriating the (...) term “induction” to mark them; since we will not be concerned with the philosophical issues for which these distinctions are relevant, we will use the word “inductive” in a catch-all sense synonymous with “ampliative”. But we will follow the usual practice of choosing, as our paradigm example of inductive inferences, inferences about the future based on evidence drawn from the past and present. A further refinement is more important. Opinion typically comes in degrees, and this fact makes a great deal of difference to how we understand inductive inferences. For while it is often harmless to talk about the conclusions that can be rationally believed on the basis of some.. (shrink)

In this paper I develop five worries concerning Cartwright’s realism about entities and capacities. The first is that while she was right to insist on the ontic commitment that flows from causal explanation, she was wrong to tie these commitments solely to the entities that do the causal explaining. This move obscured the nature of causal explanation and its connection to laws. The second worry is that when she turned her attention to causal inference, by insisting on the motto (...) of ‘the most likely cause’, she underplayed her powerful argument for realism. For she focused her attention on an extrinsic feature of causal inference (or, indeed, of any ampliative inference), that is the demand of high probability, leaving behind the intrinsic qualities that causal explanation should have in order to provide the required understanding. The third worry is that her objections to Inference to the Best Explanation were unnecessarily tied to her objections about the falsity of fundamental laws. The fourth worry is that though her argument for positing capacities and being realist about them was supposed to take strength from its parallel with Sellars’s powerful argument for the indispensable explanatory role of positing unobservable entities, there are important disanalogies between the two arguments which cast doubt on the indispensability of capacities. The final (fifth) worry is that laws—perhaps brute regularities—might well have to come back from the front door, since they are still the most plausible candidates for explaining why objects have the capacities to do what they can do. (shrink)

Three decades ago Laudan posed the challenge: Why should the logic of discovery be revived? This paper tries to answer this question arguing that the logic of discovery should be revived, on the one hand, because, by Gödel’s second incompleteness theorem, mathematical logic fails to be the logic of justification, and only reviving the logic of discovery logic may continue to have an important role. On the other hand, scientists use heuristic tools in their work, and it may be useful (...) to study such tools systematically in order to improve current heuristic tools or to develop new ones. As a step towards reviving the logic of discovery, the paper follows Aristotle in asserting that logic must be a tool for the method of science, and outlines an approach to the logic of discovery based on the analytic method and on ampliative inference rules. (shrink)

Carnap took the content of a particularsentence or set of sentences to consist in the set ofthe consequences of the sentence or set. This claimequates meaning with inferential role, but itrestricts the inferences to deductive or explicativeones. Here I reject a recent proposal by RobertBrandom, where inductive or ampliative inferences arealso meant to confer contents on expressions. I arguethat if Brandom's inferentialist picture is upheld, andboth explicative and ampliative inferences confermeaning, one consequence of this is that the contentof (...) a sentence is to be read off from our ways ofrationally altering our beliefs. Meaning and contentthen are largely concepts of pragmatics, with no cleartheoretical interest. My critique affects certainaspects of Dummett's meaning-theoretic picture too,and the discussion also links up with the developmentof `dynamic semantics'. (shrink)

Suppose a speaker S and an audience A are in a communication coordination problem. That is, for some proposition p, they each prefer that S mean that p and that A believe p in response. How do they coordinate their thought and action to solve the problem? The Gricean answer is that they reason their way to the solution. Pragmatics makes a similar assumption. “Pragmatics involves perception augmented by some species of ‘ampliative’ inference … a sort of reasoning”. (...) There are two objections. The first is that it is not plausible to attribute such reasoning to speakers and audiences. The second objection grants, for the sake of argument, that speakers and audiences reason in the required ways. The objection is that this is not sufficient to solve coordination problems since a speaker and an audience may not know how each has reasoned. The problem is well-known in game theory, which typically solves it by assuming the parties’ preferences are common knowledge. Common knowledge is the recursive belief state in which people are know something, know they know it, know they know they know it, ad infinitum. I propose a similar solution. When people interact as speaker and audience, common knowledge arises from their perceptions of each other as fulfilling the roles of speaker and audience. The account of how common knowledge arises entails Grice’s general characterization of conversational implicatures. More precisely, it entails speakers and audiences involved in communication coordination problems typically commonly know that a relevant instance of the conditions holds. The common knowledge approach requires attributing reasoning to speakers and audiences, but it keeps those attributions to a plausible minimum. Thus the common knowledge approach is a viable alternative to current approaches that attribute extensive reasoning to speakers and audiences.A common knowledge-based approach to pragmatics would answer at least the following question: What informative generalizations are possible about the role of contexts in generating common knowledge relevant to conversational implicatures? The question is important. “Much has been learned about these domains of psychology from a focus on the problem of altruistic cooperation and the mechanisms of reciprocity. We hope that comparable insights are waiting to be discovered by psychologists as they investigate the problem of mutualistic cooperation, and the mechanisms of common knowledge are—as we might say—put out there”. (shrink)

The present work explores various ways in which contingent evidence can impact metaphysics, while advocating that, just as a scientific realist allows for ampliative inferences to the unobservable, ampliative inferences from possible evidence can warrant possibility claims that lie beyond the reach of sensorial imagination. In slogan form: possible evidence is a guide to possibility. Drawing on Shoemaker’s (1969) argument for the possibility of time without change, I advocate the following principle: If there is a possible world at (...) which the observable facts make it objectively reasonable to conclude that p, then we should conclude that p is possibly true. This provides a route to contingentism in metaphysics, for, if one considers that there are worlds in which the observable facts make it objectively reasonable to conclude that p, and worlds in which the observable facts make it objectively reasonable to conclude that not-p, then my principle tells us that we should conclude that possibly-p and possibly not-p, i.e. that p is contingent. This contingency in what is reasonable to conclude, I suggest, occurs most saliently in debates where evidence of phenomenal experience and empirical science are marshalled to support one theory over another. I also explore some consequences of taking possible evidence to be a guide to possibility in this way, among them being an interesting modal analogue of the lottery paradox. (shrink)

I argue that mathematical representations can have heuristic power since their construction can be ampliative. To this end, I examine how a representation introduces elements and properties into the represented object that it does not contain at the beginning of its construction, and how it guides the manipulations of the represented object in ways that restructure its components by gradually adding new pieces of information to produce a hypothesis in order to solve a problem.In addition, I defend an ‘inferential’ (...) approach to the heuristic power of representations by arguing that these representations draw on ampliative inferences such as analogies and inductions. In effect, in order to construct a representation, we have to ‘assimilate’ diverse things, and this requires identifying similarities between them. These similarities form the basis for ampliative inferences that gradually build hypotheses to solve a problem.To support my thesis, I analyse two examples. The first one is intra-field, that is, the construction of an algebraic representation of 3-manifolds; the second is inter-fields, that is, the construction of a topological representation of DNA supercoiling. (shrink)

A central component to scientific practice is the construction and use of scientific models. Scientists believe that the success of a model justifies making claims that go beyond the model itself. However, philosophical analysis of models suggests that drawing inferences about the world from successful models is more complex. In this dissertation I develop a framework that can help disentangle the related strands of evaluation of model success, model extendibility, and the ability to draw ampliative inferences about the world (...) from models. I present and critically assess two leading accounts of model assessment, arguing that neither is sufficient to provide a complete understanding of model evaluation. I introduce a more powerful framework incorporating elements of the two views, which can help answer these three questions: What is the target of evaluation in model assessment? How does that evaluation proceed? What licenses us in making inferences about the real world, based on the evaluation of our models as successful? The framework identifies two distinct targets of model evaluation: representational similarity between the model and target system, and the adequacy of the model as a tool to answer questions. Both assessments must be relativized to a purpose, of which there are three general kinds: descriptive, predictive, and explanatory. These purposes differ in the way they inform the similarity relation, which is relevant for the similarity assessment, and the output they produce, which is relevant for the adequacy assessment. Any model can be assessed relative to any purpose, however a model encodes certain decisions made during the model’s construction, which impact its ability to be applied to a new purpose or new domain. My framework shows that extending a model, and drawing inferences from it, depends on its representational similarity. I apply this framework to several examples taken from astrophysics showing in detail how it can help illuminate the structure of the models, as well as make the justification for inferences made from them clear. The final chapter is a detailed analysis of a contemporary debate surrounding the use of models in astrophysics, between proponents of MOND and the standard ΛCDM model. (shrink)

In this article I take a loose, functional approach to defining induction: Inductive forms of reasoning include those prima facie reasonable inference patterns that one finds in science and elsewhere that are not clearly deductive. Inductive inference is often taken to be reasoning from the observed to the unobserved. But that is incorrect, since the premises of inductive inferences may themselves be the results of prior inductions. A broader conception of inductive inference regards any ampliative (...) class='Hi'>inference as inductive, where an ampliative inference is one where the conclusion ‘goes beyond’ the premises. ‘Goes beyond’ may mean (i) ‘not deducible from’ or (ii) ‘not entailed by’. Both of these are problematic. Regarding (i), some forms of reasoning might have a claim to be called ‘inductive’ because of their role in science, yet turn out to be deductive after all—for example eliminative induction (see below) or Aristotle’s ‘perfect induction’ which is an inference to a generalization from knowledge of every one of its instances. Interpretation (ii) requires that the conclusions of scientific reasoning are always contingent propositions, since necessary propositions are entailed by any premises. But there are good reasons from metaphysics for thinking that many general propositions of scientific interest and known by inductive inference (e.g. “all water is H2O”) are necessarily true. Finally, both (i) and (ii) fail to take account of the fact that there are many ampliative forms of inference one would not want to call inductive, such as counter-induction (exemplified by the ‘gambler’s fallacy’ that the longer a roulette wheel has come up red the more likely it is to come up black on the next roll). Brian Skyrms (1999) provides a useful survey of the issues involved in defining what is meant by ‘inductive argument’. Inductive knowledge will be the outcome of a successful inductive inference. But much discussion of induction concerns the theory of confirmation, which seeks to answer the question, “when and to what degree does evidence support an hypothesis?” Usually, this is understood in an incremental sense and in a way that relates to the rational credibility of a hypothesis: “when and by how much does e add to the credibility of h?”, although ‘confirms’ is sometimes used in an absolute sense to indicate total support that exceeds some suitably high threshold.. (shrink)

In this essay, I address an objection to inference to the best explanation due to Bas C. van Fraassen, according to which explanatory virtues cannot confirm a theory, since they make the theory more informative and thus less likely to be true given the probability axioms. I try to show that van Fraassen’s argument, once made precise, is deductively invalid, and that even an ampliative version of the argument (i) implies, absurdly, that no theory is confirmed by its (...) fit with empirical data; (ii) fails to account for confirmatory closure under deduction; and (iii) falsely presupposes that a theory and its sub-theories can be competing explanations. (shrink)

We can safely infer that a proposition is possible if p is the case. But, I argue, this inference from the actual to the possible is merely explicative in nature, though we employ it at times as if it were ampliative. To make this inference ampliative, we need to include an inference to the best explanation. Specifically, we can draw a substantive conclusion as to whether p is possible from the fact that p is the (...) case, if via our best explanation we can explain how p could occur again in the complete and coherent set of propositions that describes the actual world. (shrink)

(i) Scientific realism is primarily a metaphysical doctrine about the existence and nature of the unobservables of science. (ii) There are good explanationist arguments for realism, most famously that from the success of science, provided abduction is allowed. Abduction seems to be on an equal footing, at least, with other ampliative methods of inference. (iii) We have no reason to believe a doctrine of empirical equivalence that would sustain the underdetermination argument against realism. (iv) The key to defending (...) realism from the pessimistic meta-induction is that we have greatly improved our capacity to understand the unobservable world over recent centuries. (shrink)

Here we challenge the orthodoxy according to which abduction is an a posteriori mode of inference. We start by providing a case study illustrating how abduction can justify a philosophical claim not justifiable by empirical evidence alone. While many grant abduction's epistemic value, nearly all assume that abductive justification is a posteriori, on grounds that our belief in abduction's epistemic value depends on empirical evidence about how the world contingently is. Contra this assumption, we argue, first, that our belief (...) in abduction’s epistemic value is not and could not be justified a posteriori, and second, that attention to the roles experience plays in abductive justification supports taking abduction to be an a priori mode of inference. We close by highlighting how our strategy for establishing the a priority of abduction positively contrasts with strategies in Bonjour (1998), Swinburne (2001), and Peacocke (2004) aiming to establish the a priority of certain ampliative modes of inference or abductive principles. (shrink)

A minimal essentialism (‘intrinsic biological essentialism’) about natural kinds is required to explain the projectability of human science terms. Human classifications that yield robust and ampliative projectable inferences refer to biological kinds. I articulate this argument with reference to an intrinsic essentialist account of HPC kinds. This account implies that human sciences (e.g., medicine, psychiatry) that aim to formulate predictive kind categories should classify biological kinds. Issues concerning psychiatric classification and pluralism are examined.