The epistemic probability of A given B is the degree to which B evidentially supports A, or makes A plausible. This paper is a first step in answering the question of what determines the values of epistemic probabilities. I break this question into two parts: the structural question and the substantive question. Just as an object’s weight is determined by its mass and gravitational acceleration, some probabilities are determined by other, more basic ones. The structural question asks what probabilities are (...) not determined in this way—these are the basic probabilities which determine values for all other probabilities. The substantive question asks how the values of these basic probabilities are determined. I defend an answer to the structural question on which basic probabilities are the probabilities of atomic propositions conditional on potential direct explanations. I defend this against the view, implicit in orthodox mathematical treatments of probability, that basic probabilities are the unconditional probabilities of complete worlds. I then apply my answer to the structural question to clear up common confusions in expositions of Bayesianism and shed light on the “problem of the priors.”. (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)

Bradford Hill (1965) highlighted nine aspects of the complex evidential situation a medical researcher faces when determining whether a causal relation exists between a disease and various conditions associated with it. These aspects are widely cited in the literature on epidemiological inference as justifying an inference to a causal claim, but the epistemological basis of the Hill aspects is not understood. We offer an explanatory coherentist interpretation, explicated by Thagard's ECHO model of explanatory coherence. The ECHO model captures the complexity (...) of epidemiological inference and provides a tractable model for inferring disease causation. We apply this model to three cases: the inference of a causal connection between the Zika virus and birth defects, the classic inference that smoking causes cancer, and John Snow’s inference about the cause of cholera. (shrink)

Among philosophical analyses of Darwin’s Origin, a standard view says the theory presented there had no concrete observational consequences against which it might be checked. I challenge this idea with a new analysis of Darwin’s principal geographical distribution observations and how they connect to his common ancestry hypothesis.

I propose the next steps in the neuropragmatic approach to philosophy that has been advocated by Solymosi and Shook (2013). My focus is the initial process of inquiry implicit in addressing philosophical questions of cognition and mind by utilizing the tools of neuroscientific research. I combine John Dewey’s pattern of inquiry with Charles Peirce’s three forms of inference in order to outline a methodological schema for neuropragmatic inquiry. My goal is to establish ignorance and guessing as well-defined pillars of methodology (...) upon which to build a neuropragmatic approach to inquiry. First, I outline Dewey’s pattern of inquiry, highlighting the initial problematic phase in which recognized ignorance provides the basis upon which to frame a philosophical problem and initiate the trajectory by which philosophical questions may be addressed with the assistance of neuroscientific evidence. Second, I provide an outline of Peirce’s three forms of inference, focusing upon the first phase of abduction: guessing. Third, I explain the transition between ignorance and guessing, urging the benefit of attending to these two aspects of inquiry. Finally, I provide an initial sketch indicating the next steps concerning a pragmatic reconstruction of neurophilosophy, pointing towards the need for a more thorough examination of scientific methodology within and following analyses of philosophical problems and neuroscientific evidence. (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)

It is often argued that while biases routinely influence the generation of scientific theories, a subsequent rational evaluation of such theories will ensure that biases do not affect which theories are ultimately accepted. Against this line of thought, this paper shows that the existence of certain kinds of biases at the generation-stage implies the existence of biases at the evaluation-stage. The key argumentative move is to recognize that a scientist who comes up with a new theory about some phenomena has (...) thereby gained an unusual type of evidence, viz. information about the space of theories that could be true of the phenomena. It follows that if there is bias in the generation of scientific theories in a given domain, then the rational evaluation of theories with reference to the total evidence in that domain will also be biased. (shrink)

Although many aspects of Inference to the Best Explanation have been extensively discussed, very little has so far been said about what it takes for a hypothesis to count as a rival explanatory hypothesis in the context of IBE. The primary aim of this article is to rectify this situation by arguing for a specific account of explanatory rivalry. On this account, explanatory rivals are complete explanations of a given explanandum. When explanatory rivals are conceived of in this way, I (...) argue that IBE is a more plausible and defensible rule of inference than it would otherwise be. The secondary aim of the article is to demonstrate the importance of accounts of explanatory rivalry by examining a prominent philosophical argument in which IBE is employed, viz. the so-called Ultimate Argument for scientific realism. In short, I argue that a well-known objection to the Ultimate Argument due to Arthur Fine fails in virtue of tacitly assuming an account of explanatory rivalry that we have independent reasons to reject. (shrink)

In science and everyday life, we often infer that something is true because it would explain some set of facts better than any other hypothesis we can think of. But what if we have reason to believe that there is a better way to explain these facts that we just haven't thought of? Wouldn't that undermine our warrant for believing the best available explanation? Many philosophers have assumed that we can solve such underconsideration problems by stipulating that a hypothesis should (...) not only be 'the best' explanation available; rather, it should also be 'good enough'. Unfortunately, however, the only current suggestion for what it might mean to say that an explanation is 'good enough' is, well, not good enough. This paper aims to provide a better account of what is required for an explanatory hypothesis to be considered 'good enough'. In brief, the account holds that a `good enough' hypothesis is one that has gone through a process that I call explanatory consolidation, in which accumulating evidence and failed attempts to formulate better alternatives gradually make it more plausible that the explanation we currently have is better than any other that could be formulated. (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)

The state of computing science and, particularly, software engineering and knowledge engineering is generally considered immature. The best starting point for achieving a mature engineering discipline is a solid scientific theory, and the primary reason behind the immaturity in these fields is precisely that computing science still has no such agreed upon underlying theory. As theories in other fields of science do, this paper formally establishes the fundamental elements and postulates making up a first attempt at a theory in this (...) field, considering the features and peculiarities of computing science. The fundamental elements of this approach are informons and holons, and it is a general and comprehensive theory of software engineering and knowledge engineering that related disciplines (e.g., information systems) can particularise and/or extend to take benefit from it (Lakatos’ concepts of core theory and protective belt theories). (shrink)

Although the inferring of explanations plays an important role in both our everyday lives and in the workings of science, I argue that inference to the best explanation as it is commonly conceived is often not the best way to capture this sort of reasoning. I suggest that a different form of reasoning – so-called immediate explanatory inference – is instead often much better suited to this task. This is a form of inference in which we are justified in believing (...) explanations for the evidence before us purely in virtue of this evidence, and not in virtue of the evidence plus some general principle or rule of non-deductive reasoning. I defend the idea of such a notion of inference, and argue that it plays a central role in both ordinary life and science. (shrink)

Paleobiologists often provide simple narratives to explain complex, contingent episodes. These narratives are sometimes ‘one-shot hypotheses’ which are treated as being mutually exclusive with other possible explanations of the target episode, and are thus extended to accommodate as much about the episode as possible. I argue that a provisional preference for such hypotheses provides two kinds of productive scaffolding. First, they generate ‘hypothetical difference-makers’: one-shot hypotheses highlight and isolate empirically tractable dependencies between variables. Second, investigations of hypothetical difference-makers provision explanatory (...) resources, the ‘raw materials’ for constructing more complex—and likely more adequate—explanations. Provisional preferences for simple, one-shot hypotheses in historical science, then, is defeasibly justified on indirect—strategic—grounds. My argument is made in reference to recent developments regarding the K–Pg extinction. (shrink)

In this paper, I critically evaluate several related, provocative claims made by proponents of data-intensive science and “Big Data” which bear on scientific methodology, especially the claim that scientists will soon no longer have any use for familiar concepts like causation and explanation. After introducing the issue, in Section 2, I elaborate on the alleged changes to scientific method that feature prominently in discussions of Big Data. In Section 3, I argue that these methodological claims are in tension with a (...) prominent account of scientific method, often called “Inference to the Best Explanation”. Later on, in Section 3, I consider an argument against IBE that will be congenial to proponents of Big Data, namely, the argument due to Roche and Sober Analysis, 73:659–668, that “explanatoriness is evidentially irrelevant.” This argument is based on Bayesianism, one of the most prominent general accounts of theory-confirmation. In Section 4, I consider some extant responses to this argument, especially that of Climenhaga Philosophy of Science, 84:359–368,. In Section 5, I argue that Roche and Sober’s argument does not show that explanatory reasoning is dispensable. In Section 6, I argue that there is good reason to think explanatory reasoning will continue to prove indispensable in scientific practice. Drawing on Cicero’s oft-neglected De Divinatione, I formulate what I call the “Ciceronian Causal-nomological Requirement”, which states, roughly, that causal-nomological knowledge is essential for relying on correlations in predictive inference. I defend a version of the CCR by appealing to the challenge of “spurious correlations,” chance correlations which we should not rely upon for predictive inference. In Section 7, I offer some concluding remarks. (shrink)

In this paper, I discuss the ways in which epistemic anxiety promotes well-being, specifically by examining the positive contributions that feelings of epistemic anxiety make toward intellectually virtuous inquiry. While the prospects for connecting the concept of epistemic anxiety to the two most prominent accounts of intellectual virtue, i.e., “virtue-reliabilism” and “virtue-responsibilism”, are promising, I primarily focus on whether the capacity for epistemic anxiety counts as an intellectual virtue in the reliabilist sense. As I argue, there is a close yet (...) unexplored connection between feelings of epistemic anxiety and the form of inference commonly known as “Inference to the Best Explanation” (IBE). Specifically, I argue that both the recognition that some fact requires an explanation—a necessary first step in applying IBE—and the subsequent motivation to employ IBE are typically facilitated by feelings of epistemic anxiety. So, provided IBE is truth-conducive the capacity for epistemic anxiety should count as an intellectual virtue in the reliabilist sense. After outlining my main argument, I address the challenge that the capacity for epistemic anxiety has the potential to be misleading. To respond to this challenge, I discuss how our recognition that a fact requires an explanation must in part be a species of practical knowledge, rather than theoretical knowledge. For the agent to skillfully distinguish between facts that require an explanation and facts that do not, she must develop the virtuous disposition to feel the appropriate amount of epistemic anxiety. Despite the many negative aspects associated with anxiety, as I conclude, being disposed to feel the appropriate amount of epistemic anxiety is ultimately good for us. (shrink)

In this paper, I examine Cicero’s oft-neglected De Divinatione, a dialogue investigating the legitimacy of the practice of divination. First, I offer a novel analysis of the main arguments for divination given by Quintus, highlighting the fact that he employs two logically distinct argument forms. Next, I turn to the first of the main arguments against divination given by Marcus. Here I show, with the help of modern probabilistic tools, that Marcus’ skeptical response is far from the decisive, proto-naturalistic assault (...) on superstition that it is sometimes portrayed to be. Then, I offer an extended analysis of the second of the main arguments against divination given by Marcus. Inspired by Marcus’ second main argument, I formulate, explicate, and defend a substantive principle of scientific methodology that I call the “Ciceronian Causal-Nomological Requirement” (CCR). Roughly, this principle states that causal knowledge is essential for relying on correlations in predictive inference. Although I go on to argue that Marcus’ application of the CCR in his debate with Quintus is dialectically inadequate, I conclude that De Divinatione deserves its place in Cicero’s philosophical corpus, and that ultimately, its significance for the history and philosophy of science ought to be recognized. (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)

In this critical notice, I focus my attention on the chapters that deal with the explanationist response to skepticism.

Here, I consider the recent application of phylogenetic methods in historical linguistics. After a preliminary survey of one such method, i.e. cladistic parsimony, I respond to two common criticisms of cultural phylogenies: that cultural artifacts cannot be modeled as tree-like because of borrowing across lineages, and that the mechanism of cultural change differs radically from that of biological evolution. I argue that while perhaps remains true for certain cultural artifacts, the nature of language may be such as to side-step this (...) objection. Moreover, I explore the possibility that cladistic parsimony can be justified even if is true by appealing to the inference pattern known among philosophers as ‘Inference to the Best Explanation’. (shrink)

In this paper, I consider the relationship between Inference to the Best Explanation and Bayesianism, both of which are well-known accounts of the nature of scientific inference. In Sect. 2, I give a brief overview of Bayesianism and IBE. In Sect. 3, I argue that IBE in its most prominently defended forms is difficult to reconcile with Bayesianism because not all of the items that feature on popular lists of “explanatory virtues”—by means of which IBE ranks competing explanations—have confirmational import. (...) Rather, some of the items that feature on these lists are “informational virtues”—properties that do not make a hypothesis \ more probable than some competitor \ given evidence E, but that, roughly-speaking, give that hypothesis greater informative content. In Sect. 4, I consider as a response to my argument a recent version of compatibilism which argues that IBE can provide further normative constraints on the objectively correct probability function. I argue that this response does not succeed, owing to the difficulty of defending with any generality such further normative constraints. Lastly, in Sect. 5, I propose that IBE should be regarded, not as a theory of scientific inference, but rather as a theory of when we ought to “accept” H, where the acceptability of H is fixed by the goals of science and concerns whether H is worthy of commitment as research program. In this way, IBE and Bayesianism, as I will show, can be made compatible, and thus the Bayesian and the proponent of IBE can be friends. (shrink)

L’objectif de ce texte est double: expliquer certaines limitations des approches traditionnelles du succès des théories, et esquisser un critère pour l’évaluation comparative des succès empiriques d’une théorie. On insiste sur les points suivants: a) la supériorité de la prédiction sur l’adaptation, b) la résolution des anomalies non-réfutantes et c) l’utilisation limitée d’hypothèses ad hoc. Après une première partie consacrée à lever les ambiguïtés de l’expression « succès d’une théorie », la deuxième partie traite de quelques-unes des principales lacunes des (...) approches conséquentialistes traditionnelles du succès des théories. Enfin, dans la dernière section, on esquisse le critère de succès empirique d’une théorie et on donne quelques éléments pour renforcer ce critère. (shrink)

L’objectif de ce texte est double: expliquer certaines limitations des approches traditionnelles du succès des théories, et esquisser un critère pour l’évaluation comparative des succès empiriques d’une théorie. On insiste sur les points suivants: a) la supériorité de la prédiction sur l’adaptation, b) la résolution des anomalies non-réfutantes et c) l’utilisation limitée d’hypothèses ad hoc. Après une première partie consacrée à lever les ambiguïtés de l’expression « succès d’une théorie », la deuxième partie traite de quelques-unes des principales lacunes des (...) approches conséquentialistes traditionnelles du succès des théories. Enfin, dans la dernière section, on esquisse le critère de succès empirique d’une théorie et on donne quelques éléments pour renforcer ce critère. (shrink)

Exploring the early development of an area of medical literature can inform contemporary medical debates. Different methods of inference include deduction, induction, abduction, and inference to the best explanation. I argue that early shaken baby research is best understood as using abduction to tentatively suggest that infants with unexplained intracranial and ocular bleeding have been assaulted. However, this tentative conclusion was quickly interpreted, by some at least, as a general rule that infants with these pathological signs were certainly cases of (...) abuse. Rather than focusing on inductive arguments, researchers today may be better off focusing on making a compelling inference to the best explanation. (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)

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.

In this paper we investigate how inference to the best explanation (IBE) works in engineering science, focussing on the context of malfunction explanation. While IBE has gotten a lot of attention in the philosophy of science literature, few, if any, philosophical work has focussed on IBE in engineering science practice. We first show that IBE in engineering science has a similar structure as IBE in other scientific domains in the sense that in both settings IBE hinges on the weighing of (...) explanatory virtues. We then proceed to show that, due to the intimate connection between explanation and redesign in engineering science, there is a further engineering domain-specific virtue in terms of which engineering malfunction explanations are evaluated, viz. the virtue of redesign utility. This virtue entails that the explanatory information offered by a malfunction explanation should be instrumental in predicting counterfactual dependencies in redesigned systems. We illustrate and elaborate these points in terms of a number of engineering examples, focussing in particular on the 2009 crash of Air France Flight 447. Our extension of analyses of IBE and explanation to engineering science practice offers new insights by identifying a new explanatory virtue in malfunction explanation: redesign utility. (shrink)

Some New Mechanists have proposed that claims of compositional relations are justified by combining the results of top-down and bottom-up interlevel interventions. But what do scientists do when they can perform, say, a cellular intervention, but not a subcellular detection? In such cases, paired interlevel interventions are unavailable. We propose that scientists use abduction and we illustrate its use through a case study of the ionic theory of resting and action potentials.

استنتاج بهترین تبیین، به‌تازگی به‌عنوان استنتاجی جدید در عرض استقراء و قیاس توسط چارلز پیرس در توجیه بسیاری از نظریات علمی ارائه شده است. هدف این نوشتار انجام مقایسه‌ای میان این نوع استنتاج و تجربه از دیدگاه ابن­سیناست. در این مقایسه سعی شده است به تمامی شباهت‌ها و تفاوت­های موجود میان تجربه و استنتاج بهترین تبیین پرداخته شود و در کنار آن به برخی عیوب هر کدام از این دو نیز اشاره شود؛ ازجمله شباهت­های این دو استنتاج می‌توان به مقدمه (...) مضمر موجود در هر دو استنتاج و نیز استقرایی بودن و واقع­گرایی هر دو استنتاج و نیز معیار بودن تبیین علّی در هر دو استنتاج اشاره کرد و از تمایزات میان این دو استنتاج می‌توان به معیارهای انتخاب تبیین بهتر همچون سادگی و جذابیت و تطابق در استنتاج بهترین تبیین اشاره کرد که در تجربه به آنها اعتنایی نشده است. درعین‌حال که کارآمد بودن این معیارها موردتردید است. علاوه بر این، از این تمایزات می­توان به شروط و قواعدی که ابن­سینا بر تجربه افزوده است، اشاره کرد؛ چراکه در استنتاج بهترین تبیین، هیچ اشاره­ای به‌قاعده غیاب­های هم­زمان یا عدم مغالطه اخذ مابالعرض به‌جای مابالذات نشده است. (shrink)

This chapter presents a typology of the different kinds of inductive inferences we can draw from our evidence, based on the explanatory relationship between evidence and conclusion. Drawing on the literature on graphical models of explanation, I divide inductive inferences into (a) downwards inferences, which proceed from cause to effect, (b) upwards inferences, which proceed from effect to cause, and (c) sideways inferences, which proceed first from effect to cause and then from that cause to an additional effect. I further (...) distinguish between direct and indirect forms of downwards and upwards inferences. I then show how we can subsume canonical forms of inductive inference mentioned in the literature, such as inference to the best explanation, enumerative induction, and analogical inference, under this typology. Along the way, I explore connections with probability and confirmation, epistemic defeat, the relation between abduction and enumerative induction, the compatibility of IBE and Bayesianism, and theories of epistemic justification. (shrink)

Joseph Raz famously argues that given that the law necessarily claims authority and given the account of authority he provides, exclusive legal positivism is the only tenable theory of law. In this article, I contend that even if one accepts that the law necessarily claims authority and that Raz's account of authority is correct, it does not follow that exclusive legal positivism is the only tenable theory of law. This is because even if the law necessarily claims authority, it need (...) not be capable of satisfying the requirements for possessing authority laid down by the correct account of authority. Thus, even if exclusive legal positivism is the only theory of law according to which the law can satisfy those requirements, this does not show that exclusive legal positivism is correct. (shrink)

The use of multiple means of determination to “triangulate” on the existence and character of a common phenomenon, object, or result has had a long tradition in science but has seldom been a matter of primary focus. As with many traditions, it is traceable to Aristotle, who valued having multiple explanations of a phenomenon, and it may also be involved in his distinction between special objects of sense and common sensibles. It is implicit though not emphasized in the distinction between (...) primary and secondary qualities from Galileo onward. It is arguably one of several conceptions involved in Whewell’s method of the “consilience of inductions” (Laudan 1971) and is to be found in several places in Peirce. (From M. Brewer and B. Collins, eds., (1981); Scientific Inquiry in the Social Sciences (a festschrift for Donald T. Campbell), San Francisco: Jossey-Bass, pp. 123–162.). (shrink)

(2013). Is scientific theory change similar to early cognitive development? Gopnik on science and childhood. Philosophical Psychology: Vol. 26, No. 1, pp. 109-128. doi: 10.1080/09515089.2011.625114.

Tight correlations between mental states and brain states have been observed time and again within the ethology of biologically ingrained animal behaviors, the comparative psychology of animal minds, the evolutionary psychology of mental adaptations, the behavioral genetics of inherited mental traits, the developmental psychology of the maturing mind, the psychopharmacology of mind-altering substances, and cognitive neuroscience more generally. They imply that our mental lives are only made possible because of brain activity—that having a functioning brain is a necessary condition for (...) having conscious experiences. This mind-brain dependence thesis yields predictions that have been spectacularly confirmed by the evidence, whereas its antithesis has been massively disconfirmed—at least so long as it is not formulated so vaguely as to yield no specific empirical consequences at all. Dualists are thus forced to make a difficult choice: either retain a belief in personal survival at the expense of ignoring or dismissing the implications of our best evidence, or accept those implications at the expense of acknowledging that the prospects for personal survival are extremely dim. -/- 1. Introduction: A Probabilistic Argument -- 2. Scientific Reasoning I: Mill’s Methods and Modern Epidemiological Principles - 2.1 When Correlation Indicates Causation -- 3. Scientific Reasoning II: Inference to the Best Explanation, Testability, and Predictive Success - 3.1 Parsimony: Tempering Explanations to Minimize False Beliefs - 3.2 Plausibility: Harmonizing Explanations with Background Knowledge - 3.3 Testability and Confirmation: Checking Hypotheses Against the Data - 3.3.1 Confirmation of the Dependence Thesis from Failed Attempts to Falsify It - 3.3.2 Confirmation of the Dependence Thesis from the Falsification of its Rival - 3.4 Scope: Bringing Disparate Facts Together - 3.5 Fertility: Generating New Lines of Research - 3.6 Overview -- 4. Scientific Reasoning III: Bayesian and Information-Theoretic Approaches - 4.1 Bayesian Probability - 4.2 Bayesian Confirmation Theory - 4.3 A Bayesian Approach to the Dependence and Independence Theses - 4.4 The Probabilistic Price of Ad Hoc Accommodation: Simplicity vs. Goodness of Fit - 4.4.1 Simplicity Reflected in the Likelihood - 4.4.2 Simplicity Reflected in the Prior Probability - 4.5 Prediction vs. Accommodation - 4.6 Bayesian Analysis of the Dependence and Independence Theses -- 5. The Dualist’s Dilemma: Reject Science, or Reject Personal Survival? - 5.1 What’s Left for a Soul to Do? -- 6. Conclusion. (shrink)

In this chapter, Logan Paul Gage examines the only real attempt to disprove God’s existence by a New Atheist: Richard Dawkins’s “Ultimate 747 Gambit.” Central to Dawkins’s argument is the claim that God is more complex than what he is invoked to explain. Gage evaluates this claim using the main extant notions of simplicity in the literature. Gage concludes that on no reading does this claim survive scrutiny. Along the way, Dawkins claims that there are no good positive arguments for (...) God’s existence. Gage attempts to show that Dawkins’s argument depends upon distinctively philosophical assumptions that do not appear to withstand scrutiny. (shrink)

This book examines the philosophical conception of abductive reasoning as developed by Charles S. Peirce, the founder of American pragmatism. It explores the historical and systematic connections of Peirce's original ideas and debates about their interpretations. Abduction is understood in a broad sense which covers the discovery and pursuit of hypotheses and inference to the best explanation. The analysis presents fresh insights into this notion of reasoning, which derives from effects to causes or from surprising observations to explanatory theories. The (...) author outlines some logical and AI approaches to abduction as well as studies various kinds of inverse problems in astronomy, physics, medicine, biology, and human sciences to provide examples of retroductions and abductions. The discussion covers also everyday examples with the implication of this notion in detective stories, one of Peirce’s own favorite themes. The author uses Bayesian probabilities to argue that explanatory abduction is a method of confirmation. He uses his own account of truth approximation to reformulate abduction as inference which leads to the truthlikeness of its conclusion. This allows a powerful abductive defense of scientific realism. This up-to-date survey and defense of the Peircean view of abduction may very well help researchers, students, and philosophers better understand the logic of truth-seeking. (shrink)

The inaugural title in the new, Open Access series BSPS Open, The Material Theory of Induction will initiate a new tradition in the analysis of inductive inference. The fundamental burden of a theory of inductive inference is to determine which are the good inductive inferences or relations of inductive support and why it is that they are so. The traditional approach is modeled on that taken in accounts of deductive inference. It seeks universally applicable schemas or rules or a single (...) formal device, such as the probability calculus. After millennia of halting efforts, none of these approaches has been unequivocally successful and debates between approaches persist. The Material Theory of Induction identifies the source of these enduring problems in the assumption taken at the outset: that inductive inference can be accommodated by a single formal account with universal applicability. Instead, it argues that that there is no single, universally applicable formal account. Rather, each domain has an inductive logic native to it. Which that is, and its extent, is determined by the facts prevailing in that domain. Paying close attention to how inductive inference is conducted in science and copiously illustrated with real-world examples, The Material Theory of Induction will initiate a new tradition in the analysis of inductive inference. (shrink)