The role that need plays in dealing with problems of distributive justice is examined in a series of vignette studies. Among other things, it becomes clear that impartial observers make gradual assessments of justice that depend on the extent to which the observed individuals are endowed with a good. If it is known how high their need for that good is, the assessments are made relative to this reference point. In addition, impartial decision-makers make hypothetical distribution decisions that take into (...) account need, productivity, and accountability. The need of individuals is partially compensated even if they have contributed less to the available amount than they themselves require. However, the willingness to do so decreases if they are accountable for needing more than others or for having contributed less than others. Lastly, both impartial observers and impartial decision-makers distinguish between different types of needs, the fulfillment of which is given different levels of importance. (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)

I argue that current projects in ‘naturalized metaphysics’ fail to be properly naturalistic, and thereby fail in their stated aim to take one’s metaphysics from science. I argue that naturalism must involve the idea of taking science seriously, and that this can only be spelled out in terms of taking not only the theories of science seriously, but also its practice and its socio-linguistic situatedness seriously as well. This accords with naturalism because not doing so draws an artificial (non-natural) distinction (...) between the epistemic products of science as essence, and its socio-linguistic and practical features as accidents. The picture of naturalism which falls out of this is a form of pragmatism. Once this is spelled out, the question becomes, what is the appropriate attitude for the pragmatist/naturalist to have toward ontology? It is not the same as that of traditional metaphysics, since such an attitude (that metaphysical theorizing can make positive epistemic contributions) requires a priori commitments which themselves are (1) not subject to empirical review, and (2) are anthropocentric and so potentially distorted. But the pragmatist/naturalist will not go the opposite way, and say that metaphysics is meaningless either, since (true to their pragmatic commitments) ontology does things for the scientist and the layperson. It is a mistake to reject it wholesale, since the task of asserting what there is, exposing such an ontology to criticism, both empirical and logical, and revising it, has both small-scale and large-scale consequences. On the small-scale, ontologies are a guide for thinking—scientists, engineers, and lay people can and do use models of existence to navigate occurent problems in their day-to-day lives. Whether this is posing research hypotheses, developing protocols for generating new materials, or cooling off a cup of coffee, ontology plays a role. Large-scale consequences are more weighty, and more difficult to see. These large-scale consequences have to do with the aims and values which individuals and societies possess, and their interrelation with ontology. This certainly was at the forefront of the earliest ontologies—the Epicureans and Stoics built their moral philosophy on the basis of what ontology they thought was correct. This sort of practice goes on, unabated, today, though with virtually no overt acknowledgement of this important interdependency. How, for the pragmatist, do we make sense of ontological talk, if we are to eschew traditional metaphysics? Ontology—the naturalist/pragmatist declares—is a tool. Ontology helps us do things, whether it be predict behavior, understand phenomena, blame or forgive someone, and hope or despair about a life after this one (for example). Building an ontology is about building our own concepts, and this, in turn is a negotiation between our beliefs, experiences, and commitments, and the beliefs, experiences, and commitments of with whom we’re discursively engaged. (shrink)

Cancellability is an essential feature of implicatures. However, its reliability has been challenged by several cases and examples in which conversational implicatures seem to be hard or even impossible to cancel. Should it then be concluded that not all implicatures are cancellable, and therefore Grice's cancellability test should be weakened or abandoned? The present paper addresses this problem by drawing a distinction between theoretical and practical cancellability, where the latter concept captures the (un)reasonableness of explicit or contextual cancellation. By analyzing (...) three legal cases of misleading advertising, I show how the indefensibility of an interpretation can account for the practical uncancellability of an implicature. To explain and account for the reasonableness of an interpretation, the presumptive inferences involved must be reconstructed and evaluated considering different dimensions, such as the conversational context and the associated presumptions. (shrink)

Phenomenology has been described as a “non-argumentocentric” way of doing philosophy, reflecting that the philosophical focus is on generating adequate descriptions of experience. But it should not be described as an argument-free zone, regardless of whether this is intended as a descriptive claim about the work of the “usual suspects” or a normative claim about how phenomenology ought to be properly practiced. If phenomenology is always at least partly in the business of arguments, then it is worth giving further attention (...) to the role and form of phenomenological argumentation, how it interacts with its more strictly descriptive component, and the status of phenomenological claims regarding conditions for various kinds of experience. I contend that different versions of phenomenological reasoning encroach upon argument forms that are commonly thought to be antithetical to phenomenology, notably abductive reasoning, understood in terms of its role in both hypothesis generation and in terms of justification. This paper identifies two main steps to making this case. The first step takes seriously the consequences of the intrinsically dialectical aspect of phenomenology in intersection with other modes of philosophy, the natural attitude, and non-philosophy. The second step focuses on transcendental reflection and arguments about the conditions/structures they contain. Together, these two steps aim to rescue phenomenology from the objection that it has an “ostrich epistemology” with regard to the ostensible purity of description, the intuition of essences, or the “conditions” ascertained through transcendental reflection. (shrink)

The motivating question of this paper is: ‘How are our beliefs in the theorems of mathematics justified?’ This is distinguished from the question ‘How are our mathematical beliefs reliably true?’ We examine an influential answer, outlined by Russell, championed by Gödel, and developed by those searching for new axioms to settle undecidables, that our mathematical beliefs are justified by ‘intuitions’, as our scientific beliefs are justified by observations. On this view, axioms are analogous to laws of nature. They are postulated (...) to best systematize the data to be explained. We argue that there is a decisive difference between the cases. There is agreement on the data to be systematized in the scientific case that has no analog in the mathematical one. There is virtual consensus over observations, but conspicuous dispute over intuitions. In this respect, mathematics more closely resembles stereotypical philosophy. We conclude by distinguishing two ideas that have long been associated -- realism (the idea that there is an independent reality) and objectivity (the idea that in a disagreement, only one of us can be right). We argue that, while realism is true of mathematics and philosophy, these domains fail to be objective. One upshot of the discussion is that even questions of fundamental physics may fail to be objective in roughly the sense that the question, ‘Is the Parallel Postulate is true?’, understood as one of pure mathematics, fails to be. Another is a kind of pragmatism. Factual questions in mathematics, modality, logic, and evaluative areas go proxy for non-factual practical ones. -/- . (shrink)

We face reality presented with the data of conscious experience and nothing else. The project of early modern philosophy was to build a complete theory of the world from this starting point, with no cheating. Crucial to this starting point is the data of conscious sensory experience – sense data. Attempts to avoid this project often argue that the very idea of sense data is confused. But the sense-data way of talking, the sense-data language, can be freed from every blemish (...) using ideas from contemporary metaontology. We can adopt a sense-data framework that vindicates the traditional claims of sense-data theories and leads to plausible theories of perception and color. We can, we should, and in a sense, we must. Yet when we do, we face the traditional problem of external world skepticism, head-on. The real challenge of skepticism is forced upon us; it cannot honestly be avoided using externalist tricks, burden of proof shifting, or other razzle dazzle. But the challenge can be met: we are rational to posit the external world as the best explanation of the many synchronic and diachronic patterns over our sense-data. This paper argues for all of these points and ends with a plea for analytic empiricism – a traditional sense-data version of empiricism that uses all of the tools of analytic philosophy while avoiding the more questionable doctrines of the Vienna Circle (phenomenalism, verificationism). Analytic empiricism is our last best hope for completing the great philosophical project of early modern philosophy. (shrink)

Metaethical debunking arguments often conclude that no moral belief is epistemically justified. Early versions of such arguments largely relied on metaphors and analogies and left the epistemology of debunking underspecified. Debunkers have since come to take on substantial and broad-ranging epistemological commitments. The plausibility of metaethical debunking has thereby become entangled in thorny epistemological issues. In this thesis, I provide a critical yet sympathetic evaluation of the prospects and challenges facing such arguments in light of this development. In doing so, (...) I address the following central question: how could genealogical information undermine the epistemic justification of moral beliefs? In Part I, I begin answering the central question by extracting explicit and implicit epistemic principles from three popular debunking arguments. These arguments, due to Gilbert Harman, Richard Joyce, and Sharon Street, generate principles concerning ontological parsimony, explanatory dispensability, epistemic insensitivity, lack of epistemic safety, unexplained reliability, epistemic coincidences, and explanatory constraints on rational belief. Having set out the principles tasked with explaining how genealogical information undermines, Part II of the thesis seeks to evaluate whether debunking arguments built on them succeed. To this end, I consider two types of challenges faced by such arguments. First, there are strategies that attempt to block global moral debunking arguments. I argue that one popular such strategy, the so-called ‘third-factor strategy’, has been misunderstood. When understood correctly, it is of no help in answering debunking arguments. I then flesh out an alternative and more promising strategy for blocking such arguments. I then turn to internal challenges facing debunkers, particularly those who rely on ‘explanationist’ principles. I argue that explanationist debunking arguments, as well as most others, fall prey to one or more of four internal challenges: the implausibility of first-order epistemic principles, the threat of overgeneralization, the threat of self-defeat, and the need for costly metaepistemic commitments. I conclude that current debunking arguments fail to establish that no moral belief is justified. By analyzing why existing arguments fail, I develop two conditions of adequacy that debunkers must satisfy in order to navigate the internal challenges successfully. I end by suggesting future directions that debunkers should pursue to rehabilitate the prospects for global moral debunking arguments. (shrink)

Reasoning from inconclusive evidence, or ‘induction’, is central to science and any applications we make of it. For that reason alone it demands the attention of philosophers of science. This Element explores the prospects of using probability theory to provide an inductive logic, a framework for representing evidential support. Constraints on the ideal evaluation of hypotheses suggest that overall support for a hypothesis is represented by its probability in light of the total evidence, and incremental support, or confirmation, indicated by (...) an increased probability given the evidence than otherwise. This proposal is shown to have the capacity to reconstruct many canons of the scientific method and inductive inference. Along the way, significant objections are discussed, such as the challenge from inductive scepticism and the objection that the probabilistic approach makes evidential support arbitrary. (shrink)

Many cognitive and evolutionary theories of religion argue that supernatural explanations are byproducts of our cognitive adaptations. An influential argument states that our supernatural explanations result from a tendency to generate anthropomorphic explanations, and that this tendency is a byproduct of an error management strategy because agents tend to be associated with especially high fitness costs. We propose instead that anthropomorphic and other supernatural explanations result as features of a broader toolkit of well-designed cognitive adaptations, which are designed for explaining (...) the abstract and causal structure of complex, unobservable, and uncertain phenomena that have substantial impacts on fitness. Specifically, we argue that (1) mental representations about the abstract vs. the supernatural are largely overlapping, if not identical, and (2) when the data-generating processes for scarce and ambiguous observations are complex and opaque, a naive observer can improve a bias-variance trade-off by starting with a simple, underspecified explanation that Western observers readily interpret as “supernatural.” We then argue that (3) in many cases, knowledge specialists across cultures offer pragmatic services that involve apparently supernatural explanations, and their clients are frequently willing to pay them in a market for useful and effective services. We propose that at least some ethnographic descriptions of religion might actually reflect ordinary and adaptive responses to novel problems such as illnesses and natural disasters, where knowledge specialists possess and apply the best available explanations about phenomena that would otherwise be completely mysterious and unpredictable. (shrink)

Marušić & Schwenkler (Analytic Philosophy, 59, 309) offer a simple and elegant defense of strong cognitivism about intention: the view that an intention to φ is a form of belief that one will φ. I show that their defense fails: however simple and elegant, it fails to account for various aspects about intention and its expression, and faces distinctive challenges of its own, including a dilemma and counterexample. These also undermine Marušić & Schwenkler's claim to a best-explanation type of account (...) and recommend alternatives to strong cognitivism altogether. (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)

Science and religion have been described as the “two dominant forces in our culture”. As such, the relation between them has been a matter of intense debate, having profound implications for deeper understanding of our place in the universe. One position naturally associated with scientists of a materialistic outlook is that science and religion are contradictory, incompatible worldviews; however, a great deal of recent literature criticises this “conflict thesis” as simple-minded, essentially ignorant of the nature of religion and its philosophical (...) and theological underpinnings. In this first part of a two-part article, I set out the wide-ranging background required for a proper understanding of the debate as a preliminary for the second part, in which Ian Barbour ’s influential four-fold typology of science-religion relations is critically assessed, leading to the conclusion that the conflict model is not to be so easily dismissed. (shrink)

According to van Fraassen, inference to the best explanation (IBE) is incompatible with Bayesianism. To argue to the contrary, many philosophers have suggested hybrid models of scientific reasoning with both explanationist and probabilistic elements. This paper offers another such model with two novel features. First, its Bayesian component is imprecise. Second, the domain of credence functions can be extended.

There are two important philosophical research programmes on explanation in the twentieth century—the search for an account or model of scientific explanation, and the defence of inference to the best explanation as a rational form of inference. These two research programmes have largely developed independently from one another. This paper argues that bringing the two research programmes in contact promises to yield fruitful discussion. I consider and reject two arguments for keeping the two research programmes separate. I outline several issues (...) related to both research programmes that would benefit from inter(sub)disciplinary dialogue. (shrink)

In this article, I will provide a critical overview of the form of non-deductive reasoning commonly known as “Inference to the Best Explanation” (IBE). Roughly speaking, according to IBE, we ought to infer the hypothesis that provides the best explanation of our evidence. In section 2, I survey some contemporary formulations of IBE and highlight some of its putative applications. In section 3, I distinguish IBE from C.S. Peirce’s notion of abduction. After underlining some of the essential elements of IBE, (...) the rest of the entry is organized around an examination of various problems that IBE confronts, along with some extant attempts to address these problems. In section 4, I consider the question of when a fact requires an explanation, since presumably IBE applies only in cases where some explanation is called for. In section 5, I consider the difficult question of how we ought to understand IBE in light of the fact that among philosophers, there is significant disagreement about what constitutes an explanation. In section 6, I consider different strategies for justifying the truth-conduciveness of the explanatory virtues, e.g., simplicity, unification, scope, etc., criteria which play an indispensable role in any given application of IBE. In section 7, I survey some of the most recent literature on IBE, much of which consists of investigations of the status of IBE from the standpoint of the Bayesian philosophy of science. (shrink)

The book provides an overview of the contemporary discussion of the mind-body problem. This discussion takes its modern form during the 17th century in the works of René Descartes. The book covers the most important points of view in modern philosophy of mind. An important thesis of the book is that contemporary debates are still heavily influenced by Descartes’ arguments, especially those related to the nature of consciousness. (Google translate).

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

The modern abundance and prominence of data has led to the development of “data science” as a new field of enquiry, along with a body of epistemological reflections upon its foundations, methods, and consequences. This article provides a systematic analysis and critical review of significant open problems and debates in the epistemology of data science. We propose a partition of the epistemology of data science into the following five domains: (i) the constitution of data science; (ii) the kind of enquiry (...) that it identifies; (iii) the kinds of knowledge that data science generates; (iv) the nature and epistemological significance of “black box” problems; and (v) the relationship between data science and the philosophy of science more generally. (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)

This volume examines the limitations of mathematical logic and proposes a new approach to logic intended to overcome them. To this end, the book compares mathematical logic with earlier views of logic, both in the ancient and in the modern age, including those of Plato, Aristotle, Bacon, Descartes, Leibniz, and Kant. From the comparison it is apparent that a basic limitation of mathematical logic is that it narrows down the scope of logic confining it to the study of deduction, without (...) providing tools for discovering anything new. As a result, mathematical logic has had little impact on scientific practice. Therefore, this volume proposes a view of logic according to which logic is intended, first of all, to provide rules of discovery, that is, non-deductive rules for finding hypotheses to solve problems. This is essential if logic is to play any relevant role in mathematics, science and even philosophy. To comply with this view of logic, this volume formulates several rules of discovery, such as induction, analogy, generalization, specialization, metaphor, metonymy, definition, and diagrams. A logic based on such rules is basically a logic of discovery, and involves a new view of the relation of logic to evolution, language, reason, method and knowledge, particularly mathematical knowledge. It also involves a new view of the relation of philosophy to knowledge. This book puts forward such new views, trying to open again many doors that the founding fathers of mathematical logic had closed historically. (shrink)

Abductive Reasoning: Logical Investigations into Discovery and Explanation is a much awaited original contribution to the study of abductive reasoning, providing logical foundations and a rich sample of pertinent applications. Divided into three parts on the conceptual framework, the logical foundations, and the applications, this monograph takes the reader for a comprehensive and erudite tour through the taxonomy of abductive reasoning, via the logical workings of abductive inference ending with applications pertinent to scientific explanation, empirical progress, pragmatism and belief revision.

According to a widely shared generic conception of inferential justification—‘the standard conception’—an agent is inferentially justified in believing that p only if she has antecedently justified beliefs in all the non-redundant premises of a good argument for p. This conception tends to serve as the starting-point in contemporary debates about the nature and scope of inferential justification: as neutral common ground between various competing, more specific, conceptions. But it’s a deeply problematic starting-point. This paper explores three questions that haven’t been (...) given the attention they deserve, that complicate the application of the standard conception to cases, and that reveal it to be underspecified at the core—in ways that aren’t resolved but inherited by more specific (extant) versions of it. The goal isn’t to answer the questions, but to articulate them, explain what turns on them, and invite a critical re-examination of the standard conception. (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)

This paper presents arguments and evidence from psychology and neuroscience supporting Lipton’s 2004 claim that scientists create knowledge through an abductive process that he calls “Inference to the Best Explanation”. The paper develops two conclusions. Conclusion 1 is that without conscious effort on our part, our brains use a process very similar to abduction as a powerful way of interpreting sensory information. To support Conclusion 1, evidence from psychology and neuroscience is presented that suggests that what we humans perceive through (...) our senses is not reality, but rather, our ‘brain’s “best guess” of the causes of its sensory input. The implication of this best guessing is that our brains use a process very similar to abduction throughout our lives to inform us of what is happening in the world around us. In addition, an argument based on Darwinian evolution is presented claiming that our brains do an excellent job of interpreting sensory information from the outside world. (If they did not, we, as a species, could hardly have survived.) Combining these two claims leads to Conclusion 1. Building on Conclusion 1, Conclusion 2 is that Lipton and others are correct in claiming that scientists use abduction when creating scientific theories. Abduction must be strong, because Nature chose abduction for its own sensemaking purposes. This paper’s contribution to knowledge is in pointing out that recent psychological and neuroscientific research has major implications for the philosophical world’s confidence in the probable validity of abductive inference. The punchline is simple: Nature chose abduction! (shrink)

According to Karl Popper, science cannot verify its theories empirically, but it can falsify them, and that suffices to account for scientific progress. For Popper, a law or theory remains a pure conjecture, probability equal to zero, however massively corroborated empirically it may be. But it does just seem to be the case that science does verify empirically laws and theories. We trust our lives to such verifications when we fly in aeroplanes, cross bridges and take modern medicines. We can (...) do some justice to this apparent capacity of science to verify if we make a number of improvements to Popper’s philosophy of science. The key step is to recognize that physics, in accepting unified theories only, thereby makes a big metaphysical assumption about the nature of the universe. The outcome is a conception of scientific method which facilitates the criticism and improvement of metaphysical assumptions of physics. This view provides, not verification, but a perfect simulacrum of verification indistinguishable from the real thing. (shrink)

Theory of illness causation is an important issue in all biomedical sciences, and solid etiological explanations are needed in order to develop therapeutic approaches in medicine and preventive interventions in public health. Until now, the literature about the theoretical underpinnings of illness causation research has been scarce and fragmented, and lacking a convenient summary. This interdisciplinary book provides a convenient and accessible distillation of the current status of research into this developing field, and adds a personal flavor to the discussion (...) by proposing the etiological stance as a comprehensive approach to identify modifiable causes of illness. (shrink)

Philosophical Perspectives, Volume 35, Issue 1, Page 170-188, December 2021.

There are long-standing doubts about whether data from subjective scales—for instance, self-reports of happiness—are cardinally comparable. It is unclear how to assess whether these doubts are justified without first addressing two unresolved theoretical questions: how do people interpret subjective scales? Which assumptions are required for cardinal comparability? This paper offers answers to both. It proposes an explanation for scale interpretation derived from philosophy of language and game theory. In short: conversation is a cooperative endeavour governed by various maxims (Grice 1989); (...) because subjective scales are vague and individuals want to make themselves understood, scale interpretation is a search for a focal point (Schelling 1960). A specific focal point it hypothesised; if this hypothesis is correct, subjective data will be cardinally comparable. Four individually necessary and jointly sufficient conditions for cardinal comparability are specified. The paper then argues this hypothesis can be empirically be tested, makes an initial attempt to do so using subjective well-being data, and concludes it is supported. Numerous areas for further research are identified including, at the end of the paper, how certain tests could be used to ‘correct’ subjective data if they are not cardinal. (shrink)

The idea that there are some facts that call for explanation serves as an unexamined premise in influential arguments for the inexistence of moral or mathematical facts and for the existence of a god and of other universes. This book is the first to offer a comprehensive and critical treatment of this idea. It argues that calling for explanation is a sometimes-misleading figure of speech rather than a fundamental property of facts.

What is the source of logical and mathematical truth? This book revitalizes conventionalism as an answer to this question. Conventionalism takes logical and mathematical truth to have their source in linguistic conventions. This was an extremely popular view in the early 20th century, but it was never worked out in detail and is now almost universally rejected in mainstream philosophical circles. Shadows of Syntax is the first book-length treatment and defense of a combined conventionalist theory of logic and mathematics. It (...) argues that our conventions, in the form of syntactic rules of language use, are perfectly suited to explain the truth, necessity, and a priority of logical and mathematical claims, as well as our logical and mathematical knowledge. (shrink)

Memory skepticism denies our memory beliefs could have any notable epistemic good. One route to memory skepticism is to challenge memory’s epistemic trustworthiness, that is, its functioning in a way necessary for it to provide epistemic justification. In this paper we develop and respond to this challenge. It could threaten memory in such a way that we altogether lack doxastic attitudes. If it threatens memory in this way, then the challenge is importantly self-defeating. If it does not threaten memory in (...) this way, then the challenge leaves a foundation for an inference to the best explanation response, one we articulate and support. (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)

It is generally supposed by psychical researchers that evidence suggestive of consciousness surviving bodily death would always be compatible with the so-called 'super-psi hypothesis', according to which living-agent psi is wholly responsible for the evidence. In this paper, I argue that, granted how super-psi is supposed to work, a case can be made for certain near-death experience cases to be incompatible with the super-psi hypothesis. From such a base, the explanatory impasse between the super-psi hypothesis and the survival hypothesis can (...) be broken. Keywords: near-death experiences, NDEs, super-psi, mind-body dualism, survival, consciousness. (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)

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)

Philosophers of physics have long debated whether the Past State of low entropy of our universe calls for explanation. What is meant by “calls for explanation”? In this article we analyze this notion, distinguishing between several possible meanings that may be attached to it. Taking the debate around the Past State as a case study, we show how our analysis of what “calling for explanation” might mean can contribute to clarifying the debate and perhaps to settling it, thus demonstrating the (...) fruitfulness of this analysis. Applying our analysis, we show that two main opponents in this debate, Huw Price and Craig Callender, are, for the most part, talking past each other rather than disagreeing, as they employ different notions of “calling for explanation”. We then proceed to show how answering the different questions that arise out of the different meanings of “calling for explanation” can result in clarifying the problems at hand and thus, hopefully, to solving them. (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)

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)

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)

In this paper I offer a coherentist justification of induction along the lines of a Sellarsian coherence theory. On this coherence theory, a proposition is justified if we can answer all objections raised against it in our social practice of demanding justification and responding to such demands. On the basis of this theory of justification, I argue that we are justified in accepting the uniformity of nature partly because we have no alternative but to accept it for rationally pursuing our (...) epistemic goal. In addition, my coherentist view explains which inductive inferences it is rational to accept. Furthermore, my coherentist view also explains why we can hardly determine a particular numerical value x such that we can draw the conclusion ‘it is rational to accept that p’ from the premise ‘the numerical probability of p is greater than or equal to x’. (shrink)

This is book l of three philosophy books in international language; formal academic philosophy source in Kurdish language Given overall view on classic epistemology for university student in non English language philosophy departments and philosophy schools .

How should we reason in science? Jan Sprenger and Stephan Hartmann offer a refreshing take on classical topics in philosophy of science, using a single key concept to explain and to elucidate manifold aspects of scientific reasoning. They present good arguments and good inferences as being characterized by their effect on our rational degrees of belief. Refuting the view that there is no place for subjective attitudes in 'objective science', Sprenger and Hartmann explain the value of convincing evidence in terms (...) of a cycle of variations on the theme of representing rational degrees of belief by means of subjective probabilities (and changing them by Bayesian conditionalization). In doing so, they integrate Bayesian inference—the leading theory of rationality in social science—with the practice of 21st century science. Bayesian Philosophy of Science thereby shows how modeling such attitudes improves our understanding of causes, explanations, confirming evidence, and scientific models in general. It combines a scientifically minded and mathematically sophisticated approach with conceptual analysis and attention to methodological problems of modern science, especially in statistical inference, and is therefore a valuable resource for philosophers and scientific practitioners. (shrink)