In this paper I identify a fallacy. The fallacy is worth noting for practical and theoretical reasons. First, the rampant occurrences ofthis fallacy-especially at moments calling for careful thought-indicate that it is more pernicious to clear thinking than many of those found in standard logic texts. Second, the fallacy stands apart from most others in that it contains multiple kinds oflogical error (i.e., fallacious and non-fallacious logical errors) that are themselves committed in abnormal ways, and thus it presents a two-tiered (...) challenge to oversimplified accounts of how an argument can go bad. (shrink)

one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...

Jones & Love (J&L) should have given more attention to Agnostic uses of Bayesian methods for the statistical analysis of models and data. Reliance on the frequentist analysis of Bayesian models has retarded their development and prevented their full evaluation. The Ecumenical integration of Bayesian statistics to analyze Bayesian models offers a better way to test their inferential and predictive capabilities.

Many people in the Western world are distressed about a perceived loss of community and community values, and it has been argued that the key difference between strong and weak community lies in social capital, that is, networks of civic engagement and norms of generalized reciprocity. In the context of social capital, the article introduces a research project that focuses on a community intranet installed in a new housing development in Melbourne, Australia. The prospects for the success of the community (...) intranet in linking residents to one another, increasing participation in local civic organizations, encouraging reciprocity, and thereby fostering social capital are surveyed in both a priori and empirical terms. The article concludes with the questions to be used in the case study to assess whether these prospects are realized in the case at hand. (shrink)

Against Hellman's (1997) recent claims, I argue that Bayesianism is unable to explain the value of generally successful aspects of scientific methodology, viz., deflecting blame from well-confirmed theories onto auxiliaries and preferring more-varied data. Such an explanation would require not just objectification of priors, but a reason to believe priors will generally fall on values that justify the practice. Given the track record on the objectification problem, adding further conditions on priors merely makes the Bayesian's problems even worse.

Contemporary literature in philosophy of science has begun to emphasize the practice of modeling, which differs in important respects from other forms of representation and analysis central to standard philosophical accounts. This literature has stressed the constructed nature of models, their autonomy, and the utility of their high degrees of idealization. What this new literature about modeling lacks, however, is a comprehensive account of the models that figure in to the practice of modeling. This paper offers a new account of (...) both concrete and mathematical models, with special emphasis on the intentions of theorists, which are necessary for evaluating the model-world relationship during the practice of modeling. Although mathematical models form the basis of most of contemporary modeling, my discussion begins with more traditional, concrete models such as the San Francisco Bay model. (shrink)

In everyday life, people typically observe fragments of causal networks. From this knowledge, people infer how novel combinations of causes they may never have observed together might behave. I report on 4 experiments that address the question of how people intuitively integrate multiple causes to predict a continuously varying effect. Most theories of causal induction in psychology and statistics assume a bias toward linearity and additivity. In contrast, these experiments show that people are sensitive to cues biasing various integration rules. (...) Causes that refer to intensive quantities (e.g., taste) or to preferences (e.g., liking) bias people toward averaging the causal influences, whereas extensive quantities (e.g., strength of a drug) lead to a tendency to add. However, the knowledge underlying these processes is fallible and unstable. Therefore, people are easily influenced by additional task‐related context factors. These additional factors include the way data are presented, the difficulty of the inference task, and transfer from previous tasks. The results of the experiments provide evidence for causal model and related theories, which postulate that domain‐general representations of causal knowledge are influenced by abstract domain knowledge, data‐driven task factors, and processing difficulty. (shrink)

The posthumous publication, in 1763, of Thomas Bayes’ “Essay Towards Solving a Problem in the Doctrine of Chances” inaugurated a revolution in the understanding of the confirmation of scientific hypotheses—two hundred years later. Such a long period of neglect, followed by such a sweeping revival, ensured that it was the inhabitants of the latter half of the twentieth century above all who determined what it was to take a “Bayesian approach” to scientific reasoning.

Suppose that an informant (test, expert, device, perceptual system, etc.) is unlikely to err when pronouncing on a particular subject matter. When this is so, it might be tempting to defer to that informant when forming beliefs about that subject matter. How is such an inferential process expected to fare in terms of truth (leading to true beliefs) and evidential fit (leading to beliefs that fit one’s total evidence)? Using a medical diagnostic test as an example, we set out a (...) formal framework to investigate this question. We establish seven results and make one conjecture. The first four results show that when the test’s error probabilities are low, the process of deferring to the test can score well in terms of (i) both truth and evidential fit, (ii) truth but not evidential fit, (iii) evidential fit but not truth, or (iv) neither truth nor evidential fit. Anything is possible. The remaining results and conjecture generalize these results in certain ways. These results are interesting in themselves—especially given that the diagnostic test is not sensitive to the target disease’s base rate—but also have broader implications for the more general process of deferring to an informant. Additionally, our framework and diagnostic example can be used to create test cases for various reliabilist theories of inferential justification. We show, for example, that they can be used to motivate evidentialist process reliabilism over process reliabilism. (shrink)

This article reviews current methods for evaluating models in the cognitive sciences, including theoretically based approaches, such as Bayes factors and minimum description length measures; simulation approaches, including model mimicry evaluations; and practical approaches, such as validation and generalization measures. This article argues that, although often useful in specific settings, most of these approaches are limited in their ability to give a general assessment of models. This article argues that hierarchical methods, generally, and hierarchical Bayesian methods, specifically, can provide a (...) more thorough evaluation of models in the cognitive sciences. This article presents two worked examples of hierarchical Bayesian analyses to demonstrate how the approach addresses key questions of descriptive adequacy, parameter interference, prediction, and generalization in principled and coherent ways. (shrink)

The essential precondition of implementing interventionist techniques of causal reasoning is that particular variables are identified as so-called intervention variables. While the pertinent literature standardly brackets the question how this can be accomplished in concrete contexts of causal discovery, the first part of this paper shows that the interventionist nature of variables cannot, in principle, be established based only on an interventionist notion of causation. The second part then demonstrates that standard observational methods that draw on Bayesian networks identify intervention (...) variables only if they also answer the questions that can be answered by interventionist techniques—which are thus rendered dispensable. The paper concludes by suggesting a way of identifying intervention variables that allows for exploiting the whole inferential potential of interventionist techniques. (shrink)

Legal scholarship exploring the nature of evidence and the process of juridical proof has had a complex relationship with formal modeling. As evident in so many fields of knowledge, algorithmic approaches to evidence have the theoretical potential to increase the accuracy of fact finding, a tremendously important goal of the legal system. The hope that knowledge could be formalized within the evidentiary realm generated a spate of articles attempting to put probability theory to this purpose. This literature was both insightful (...) and frustrating. Much light was shed on the legal system, but it also quickly became evident that the tools of probability theory were in many ways ill-constructed for the task. Fundamental incompatibilities between the structure of legal decision making and the extant formal tools were identified, and it became evident that many of the purported explanations of legal phenomena were internally inconsistent. As a consequence, interest in this type of formal modeling declined, and attention was directed toward different kinds of explanations of the phenomena. Perhaps under the influence of a recent trend toward various types of formal modeling in legal scholarship, a recent burst of articles, rather than attempting to explain the macro structure of trials, which was the previous object of interest, attempts to quantify the probative value of various items of evidence in ways consistent with the formal features of various probability theories, and then to study decision making from that perspective. For example, the value of evidence is often purported to be its likelihood ratio, that is, the probability of discovering or receiving the evidence given a hypothesis (e.g., the defendant did it) divided by the probability of discovering or receiving the evidence given the negation of the hypothesis (the defendant didn't do it). Alternatively, the value of evidence is purported (more contextually) to be the information gain it provides, defined as the increase in probability it provides for a hypothesis above the probability of the hypothesis based on the other available evidence. Both conceptions then assume that all of the various probability assessments conform or ought to conform to the dictates of Bayes' theorem (that maintains consistency among such assessments); empirical studies are then done testing the extent to which this is so and proposing how the law can increase the probability that it is so. The general criticisms of using Bayes' theorem as a formal model of juridical proof are well known and were integral to the last wave of interest in formal modeling of the evidentiary process. This paper thus for the most part puts aside that more general issue, and focuses specifically on mathematical modeling of the value of particular items of evidence. The paper demonstrates that formal modeling has only limited value in explaining the value of legal evidence, much more limited than those constructing and discussing the models assume, and thus that the conclusions they draw about the value of evidence are unwarranted. This is done through a discussion of four recent examples that attempt to quantify evidence relating to, respectively, carpet fibers, infidelity, DNA random-match evidence, and character evidence used to impeach a witness. This article thus makes two contributions. First, and most importantly, it is another demonstration of the complex relationship between algorithmic tools and legal decision making. Second, at a minimum it points out serious pitfalls for analytical or empirical studies of juridical proof. (shrink)

Currently, two frameworks of causal reasoning compete: Whereas dependency theories focus on dependencies between causes and effects, dispositional theories model causation as an interaction between agents and patients endowed with intrinsic dispositions. One important finding providing a bridge between these two frameworks is that failures of causes to generate their effects tend to be differentially attributed to agents and patients regardless of their location on either the cause or the effect side. To model different types of error attribution, we augmented (...) a causal Bayes net model with separate error sources for causes and effects. In several experiments, we tested this new model using the size of Markov violations as the empirical indicator of differential assumptions about the sources of error. As predicted by the model, the size of Markov violations was influenced by the location of the agents and was moderated by the causal structure and the type of causal variables. (shrink)

This article explores some open questions related to the problem of verification of theories in the context of empirical sciences by contrasting three epistemological frameworks. Each of these epistemological frameworks is based on a corresponding central metaphor, namely: (a) Neo-empiricism and the gambling metaphor; (b) Popperian falsificationism and the scientific tribunal metaphor; (c) Cognitive constructivism and the object as eigen-solution metaphor. Each of one of these epistemological frameworks has also historically co-evolved with a certain statistical theory and method for testing (...) scientific hypotheses, respectively: (a) Decision theoretic Bayesian statistics and Bayes factors; (b) Frequentist statistics and p-values; (c) Constructive Bayesian statistics and e-values. This article examines with special care the Zero Probability Paradox (ZPP), related to the verification of sharp or precise hypotheses. Finally, this article makes some remarks on Lakatos’ view of mathematics as a quasi-empirical science. (shrink)

: Our paper discusses the epistemic attitudes of particle physicists on the discovery of the Higgs boson at the Large Hadron Collider. It is based on questionnaires and interviews made shortly before and shortly after the discovery in 2012. We show, to begin with, that the discovery of a Standard Model Higgs boson was less expected than is sometimes assumed. Once the new particle was shown to have properties consistent with SM expectations – albeit with significant experimental uncertainties –, there (...) was a broad agreement that ‘a’ Higgs boson had been found. Physicists adopted a two-pronged strategy. On the one hand, they treated the particle as a SM Higgs boson and tried to establish its properties with higher precision; on the other hand, they searched for any hints of physics beyond the SM. This motivates our first philosophical thesis: the Higgs discovery, being of fundamental importance and establishing a new kind of particle, represented a crucial experiment if one interprets this notion in an appropriate sense. By embedding the LHC into the tradition of previous precision experiments and the experimental strategies thus established, underdetermination and confirmational holism are kept at bay. Second, our case study suggests that criteria of theory preference should be understood as epistemic and pragmatic values that have to be weighed in factual research practice. The Higgs discovery led to a shift from pragmatic to epistemic values as regards the mechanisms of electroweak symmetry breaking. Complex criteria, such as naturalness, combine epistemic and pragmatic different values, but are coherently applied by the community. (shrink)

The Full Bayesian Significance Test, FBST, is extensively reviewed. Its test statistic, a genuine Bayesian measure of evidence, is discussed in detail. Its behavior in some problems of statistical inference like testing for independence in contingency tables is discussed.

A Bayesian measure of evidence for precise hypotheses is presented. The intention is to give a Bayesian alternative to significance tests or, equivalently, to p-values. In fact, a set is defined in the parameter space and the posterior probability, its credibility, is evaluated. This set is the “Highest Posterior Density Region” that is “tangent” to the set that defines the null hypothesis. Our measure of evidence is the complement of the credibility of the “tangent” region.

Research on human causal induction has shown that people have general prior assumptions about causal strength and about how causes interact with the background. We propose that these prior assumptions about the parameters of causal systems do not only manifest themselves in estimations of causal strength or the selection of causes but also when deciding between alternative causal structures. In three experiments, we requested subjects to choose which of two observable variables was the cause and which the effect. We found (...) strong evidence that learners have interindividually variable but intraindividually stable priors about causal parameters that express a preference for causal determinism. These priors predict which structure subjects preferentially select. The priors can be manipulated experimentally and appear to be domain-general. Heuristic strategies of structure induction are suggested that can be viewed as simplified implementations of the priors. (shrink)

Recent studies indicate that indicative conditionals like "If people wear masks, the spread of Covid-19 will be diminished" require a probabilistic dependency between their antecedents and consequents to be acceptable (Skovgaard-Olsen et al., 2016). But it is easy to make the slip from this claim to the thesis that indicative conditionals are acceptable only if this probabilistic dependency results from a causal relation between antecedent and consequent. According to Pearl (2009), understanding a causal relation involves multiple, hierarchically organized conceptual dimensions: (...) prediction, intervention, and counterfactual dependence. In a series of experiments, we test the hypothesis that these conceptual dimensions are differentially encoded in indicative and counterfactual conditionals. If this hypothesis holds, then there are limits as to how much of a causal relation is captured by indicative conditionals alone. Our results show that the acceptance of indicative and counterfactual conditionals can become dissociated. Furthermore, it is found that the acceptance of both is needed for accepting a causal relation between two co-occurring events. The implications that these findings have for the hypothesis above, and for recent debates at the intersection of the psychology of reasoning and causal judgment, are critically discussed. Our findings are consistent with viewing indicative conditionals as answering predictive queries requiring evidential relevance (even in the absence of direct causal relations). Counterfactual conditionals in contrast target causal relevance, specifically. Finally, we discuss the implications our results have for the yet unsolved question of how reasoners succeed in constructing causal models from verbal descriptions. (shrink)

Simulation and Similarity is a novel and comprehensive account of, in first place, models and modeling. The author’s writing is exceptionally clear and intelligible. Simulation is referred to in the book only once, where it is defined as a kind of numerical analysis involving “computing the behavior of the model using a particular set of initial conditions” (82). Modeling, which is defined as “the indirect study of real-world systems via the construction and analysis of models” (4), appears to be the (...) primary focus of this book. This emphasis seems legitimate because the modeling practice precedes any simulation and is the key to its understanding as well.Chapter 2 “Three kinds of models” presents an account of the following kinds of models: concrete models (San Francisco Bay model being an example), mathematical models (Lottka–Volterra model of predation as an example), and computational models (illustrated by Schelling’s segregation model). First model example is a hydraulic one; the .. (shrink)

Drawing on an array of sources, from Deleuze and Guattari’s philosophy through to non-philosophy, this paper concerns itself with the manifestation of the concepts of hope and despair in utopian thought and continental philosophy and the experience of hopelessness, despair and exhaustion in the contemporary moment. I aim to demonstrate such pressing concerns through a comparison of Japanese philosopher Kojin Karatani and Japanese fiction writer Ryū Murakami with the American science fiction-thriller film directed by Michael Bay, The Island. What (...) is explored in these works is the dialectic of exhaustion and possibility. The focus of the paper is on the fecund moment inhering in the incapacity of thought to think the possibility of utopia. In terms of the philosophy of education, this hones in on the perceived lack of vision of such a possibility among youth and the failure of the university qua institution to proffer an alternative world to its cohort. To demon... (shrink)

Because we humans speak a public language, there has always been a special reason to suppose that we have a language of thought. For nonhuman animals, this special reason is missing, and the issue is less straightforward. On the one hand, there is evidence of various types of nonlinguistic representations, such as analog magnitude representations, which can explain many types of intelligent behavior. But on the other hand, the mere fact that some aspects of animal cognition can be explained by (...) nonlinguistic representations hardly suffices to show that animal minds are bereft of any sentence-like representations. This paper explores these complexities and argues that empirical research into the logical abilities of nonhuman animals provides a more direct way of evaluating whether they have a language of thought. Along the way, I offer a novel suggestion of how the hypothesis that animals draw disjunctive syllogisms can be empirically distinguished from the hypothesis, defended by Michael Rescorla, that animals reason probabilistically in accordance with Bayes’ Law. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:?;5. HUME AND SPINOZA It is strange that there has been so little interest in comparing two great philosophers, Hume and -Spinoza, who were both so important and influential in bringing about the decline of traditional religion. Jessop's bibliography indicates no interest in Hume and Spinoza up to the 1930 's. The Hume conferences of 1976, as far as I have been able to 2 determine, avoided the topic. (...) In one of the better new Hume volumes, Livingston and King, Hume, A Re-evaluation, 3 Spinoza is cited twice, and once incorrectly at that. On the other hand, in the massive new Spinoza volume edited by Siegfried Hessing, Speculum Spinozanun 1677-1977, Hume is mentioned four times, but only one of these has any real relevance to Hume's views vis-a-vis Spinoza's. Some discussion of Hume's comments, usually brief, occurs in the commentators. B. M. Laing, in David Hume, (London 1932), has just three short references to Spinoza. John Laird, in Hume's Philosophy of Human Nature, (London 1932) has a couple of cursory references to Spinoza, plus a bit more extended statement of Pierre Bay le" s critique of him. In H. H. Price, Hume's Theory of the External World, (Oxford 1940), there is one paragraph on Hume and Spinoza. In Norman Kemp Smith, The Philosophy of David Hume (London 1941), there are three references to Spinoza. Rachel Kydd, Reason and Conduct in Hume's Treatise (Oxford 194 6), has the greatest number of references to Spinoza. She was concerned to compare him with Hume on other matters than are dealt with in this paper, namely Spinoza's theory of reason and 9 the passions. In contrast, André Leroy, David Hume, (Paris 1953), has just one paragraph on Spinoza dealing with the immateriality of the soul; and Ernest C. Mossner, in his monumental Life of David Hume, (Austin 1954), has only one reference to Spinoza - James Beattie's denunciation of Hume, Hobbes, Malebranche, Leibniz and Spinoza. Lastly, in a fairly recent commentary by James Noxon, Spinoza is mentioned 66. three times, but not for anything in Hume's text. Noxon does point out (p. 75) that Spinoza is not mentioned in ] 2 Hume's correspondence. John H. Randall has offered an explanation for this neglect of Spinoza by Hume scholars, namely that "Hume stands for all time as the antithesis of Spinoza in his thought". In the England of Hume's day, Spinoza was little known, but still better known at the time than he was in France or England. Spinoza's Tractatus Theologico-Politicus 14 had been twice translated into English anonymously. He had been attacked by Bishop Stillingfleet, by John Evelyn, by Berkeley and several others. But Spinoza was not a major figure, except to the English Deists, and to Hume's early patron, the Chevalier Andrew Michael Ramsay. Most of the information known about Spinoza came from Pierre Bayle' s Historical and Critical Dictionary, where the article "Spinoza" is the longest in the Dictionary, about three hundred pages in length. My suspicion, or hypothesis, is that Hume first became interested in Spinoza through Ramsay, and then learned what he knew about Spinoza from Bayle' s article. When the young David Hume went to France to write his A Treatise of Human Nature in 1734, he went first to see the Chevalier Ramsay, who entertained Hume for about two weeks. Ramsay was a leading Scottish Catholic, was the teacher of Bonnie Prince Charlie, a leading Scottish revolutionary, 18 as well as the Grand Master of the Free Masons. With Ramsay's eclectic views it is not odd that he had a serious interest in Spinoza's theory, and that he was composing answers to it. Ramsay advised Hume about his own book, and Hume felt he had to show Ramsay the Treatise before he 19 brought it back to England. In the Treatise there is a not too well studied section on Spinoza, Of the immateriality of the soul 20 (T240-45). In introducing Spinoza into the discussion of 67. the immateriality of the soul, Hume follows what was common practice in his day, namely to insult Spinoza and his theory... (shrink)

This is a series of lectures on formal decision theory held at the University of Bayreuth during the summer terms 2008 and 2009. It largely follows the book from Michael D. Resnik: Choices. An Introduction to Decision Theory, 5th ed. Minneapolis London 2000 and covers the topics: -/- Decisions under ignorance and risk Probability calculus (Kolmogoroff Axioms, Bayes' Theorem) Philosophical interpretations of probability (R. v. Mises, Ramsey-De Finetti) Neuman-Morgenstern Utility Theory Introductory Game Theory Social Choice Theory (Sen's Paradox of (...) Liberalism, Arrow's Theorem) . (shrink)

An engaging and illuminating exploration of grief—and why, despite its intense pain, it can also help us grow Experiencing grief at the death of a person we love or who matters to us—as universal as it is painful—is central to the human condition. Surprisingly, however, philosophers have rarely examined grief in any depth. In Grief, Michael Cholbi presents a groundbreaking philosophical exploration of this complex emotional event, offering valuable new insights about what grief is, whom we grieve, and how (...) grief can ultimately lead us to a richer self-understanding and a fuller realization of our humanity. Drawing on psychology, social science, and literature as well as philosophy, Cholbi explains that we grieve for the loss of those in whom our identities are invested, including people we don't know personally but cherish anyway, such as public figures. Their deaths not only deprive us of worthwhile experiences; they also disrupt our commitments and values. Yet grief is something we should embrace rather than avoid, an important part of a good and meaningful life. The key to understanding this paradox, Cholbi says, is that grief offers us a unique and powerful opportunity to grow in self-knowledge by fashioning a new identity. Although grief can be tumultuous and disorienting, it also reflects our distinctly human capacity to rationally adapt as the relationships we depend on evolve. An original account of how grieving works and why it is so important, Grief shows how the pain of this experience gives us a chance to deepen our relationships with others and ourselves. (shrink)

Michael Tooley presents a major new philosophical theory of the nature of time, offering a powerful alternative to the traditional "tensed" and recent "tenseless" accounts of time. He argues for a dynamic conception of the universe, in which past, present, and future are not merely subjective features of experience. He claims that the past and the present are real, while the future is not. Tooley's approach accounts for time in terms of causation. He therefore claims that the key to (...) understanding the dynamic nature of the universe is to understand the nature of causation. Time, Tense, and Causation is a landmark treatment of one of the oldest and most perplexing intellectual problems, and will be fascinating reading for anyone interested in the character of time. (shrink)

Michael Ridge presents an original expressivist theory of normative judgments--Ecumenical Expressivism--which offers distinctive treatments of key problems in metaethics, semantics, and practical reasoning. He argues that normative judgments are hybrid states partly constituted by ordinary beliefs and partly constituted by desire-like states.

Every choice we make is set against a background of massive ignorance about our past, our future, our circumstances, and ourselves. Philosophers are divided on the moral significance of such ignorance. Some say that it has a direct impact on how we ought to behave - the question of what our moral obligations are; others deny this, claiming that it only affects how we ought to be judged in light of the behaviour in which we choose to engage - the (...) question of what responsibility we bear for our choices. Michael Zimmerman claims that our ignorance has an important bearing on both questions, and offers an account of moral obligation and moral responsibility that is sharply at odds with the prevailing wisdom. His book will be of interest to a wide range of readers in ethics. (shrink)

Prior research has demonstrated that accountants differ from the general population on many personality traits. Understanding accountants’ personality traits is important when these characteristics may impact professional behavior or ability to work with members of the business community. Our study investigates the relationship between Machiavellianism, ethical orientation, anti-intellectualism, and social desirability response bias in Canadian accountants. We find that Canadian accountants score much higher on the Machiavellianism scale than U.S. accountants. Additionally, our results show a significant relationship between Machiavellianism and (...) relativism, idealism, anti-intellectualism, and social desirability response bias. Our results indicate that professional Canadian accountants may not share the same personality characteristics as U.S. accountants. We extend previous research investigating Canadian accountants, by explicitly recognizing the impact of social desirability response bias, and by including anti-intellectualism. (shrink)

Inspired by the work of Wilfrid Sellars, Michael Williams launches an all-out attack on what he calls "phenomenalism," the idea that our knowledge of the world rests on a perceptual or experiential foundation.

In Unnatural Doubts, Michael Williams constructs a masterly polemic against the very idea of epistemology, as traditionally conceived.

Michael G. Titelbaum presents a new Bayesian framework for modeling rational degrees of belief—the first of its kind to represent rational requirements on agents who undergo certainty loss.

In this book, Michael Strevens aims to explain how simplicity can coexist with, indeed be caused by, the tangled interconnections between a complex system's ...

This essay is a response to Michael Martin’s “Why the Resurrection Is Initially Improbable,” Philo, Vol. 1, No.1. I argue that Martin has not succeeded in achieving his aim of showing that the Resurrection is initially improbable and thus, by Bayes’s Theorem, implausible. I respond to five of Martin’s arguments: the “particular time and place argument”; the claim that there is no plausible Christian theory of why Jesus should have been incarnated and resurrected; the claim that the Resurrection accounts (...) in the New Testament are unreliable; Martin’s assumptions about how one establishes the initial probability of Resurrection; and the use Martin makes of Bayes’s Theorem to discredit belief in the Resurrection. (shrink)

Michael Tye untangles the complex web of empirical and conceptual issues of the newly revived imagery debate in psychology between those that liken mental...

In this book, Michael Arbib, a researcher in artificial intelligence and brain theory, joins forces with Mary Hesse, a philosopher of science, to present an integrated account of how humans 'construct' reality through interaction with the social and physical world around them. The book is a major expansion of the Gifford Lectures delivered by the authors at the University of Edinburgh in the autumn of 1983. The authors reconcile a theory of the individual's construction of reality as a network (...) of schemas 'in the head' with an account of the social construction of language, science, ideology and religion to provide an integrated schema-theoretic view of human knowledge. The authors still find scope for lively debate, particularly in their discussion of free will and of the reality of God. The book integrates an accessible exposition of background information with a cumulative marshalling of evidence to address fundamental questions concerning human action in the world and the nature of ultimate reality. (shrink)

What is going on under the hood in philosophical analysis, that familiar process that attempts to uncover the nature of such philosophically interesting kinds as knowledge, causation, and justice by the method of posit and counterexample? How, in particular, do intuitions tell us about philosophical reality? The standard, if unappealing, answer is that philosophical analysis is conceptual analysis—that what we learn about when we do philosophy is in the first instance facts about our own minds. Drawing on recent work on (...) the psychology of concepts, this book proposes a new understanding of philosophical analysis, which I call inductive analysis. The thesis that philosophical analysis is inductive analysis explains how novel, substantive philosophical knowledge can be generated in the armchair. It also explains why attempts at philosophical analysis tend to fall short of providing a complete and uncontroversial definition, and supplies reasons not to lament this apparent shortcoming. (shrink)

Sometimes we learn through the use of imagination. The epistemology of imagination asks how this is possible. One barrier to progress on this question has been a lack of agreement on how to characterize imagination; for example, is imagination a mental state, ability, character trait, or cognitive process? This paper argues that we should characterize imagination as a cognitive ability, exercises of which are cognitive processes. Following dual process theories of cognition developed in cognitive science, the set of imaginative processes (...) is then divided into two kinds: one that is unconscious, uncontrolled, and effortless, and another that is conscious, controlled, and effortful. This paper outlines the different epistemological strengths and weaknesses of the two kinds of imaginative process, and argues that a dual process model of imagination helpfully resolves or clarifies issues in the epistemology of imagination and the closely related epistemology of thought experiments. (shrink)

Sceptical theists--e.g., William Alston and Michael Bergmann--have claimed that considerations concerning human cognitive limitations are alone sufficient to undermine evidential arguments from evil. We argue that, if the considerations deployed by sceptical theists are sufficient to undermine evidential arguments from evil, then those considerations are also sufficient to undermine inferences that play a crucial role in ordinary moral reasoning. If cogent, our argument suffices to discredit sceptical theist responses to evidential arguments from evil.

Michael Wedin argues against the prevailing notion that Aristotle's views on the nature of reality are fundamentally inconsistent. According to Wedin's new interpretation, the difference between the early theory of the Categories and the later theory of the Metaphysics reflects the fact that Aristotle is engaged in quite different projects in the two works--the earlier focusing on ontology, and the later on explanation.

This paper proposes a holistic approach to the model-world relationship, suggesting that the model-world relationship be viewed as an overall structural fit where one organized whole fits another organized whole. This approach is largely motivated by the implausibility of Michael Weisberg’s weighted feature-matching account of the model-world relationship, where a set-theoretic conception of the structures of models is assumed. To show the failure of Weisberg’s account and the plausibility of my approach, a concrete model, i.e. the San Francisco Bay (...) model, is discussed. (shrink)

In _The Immorality of Punishment_ Michael Zimmerman argues forcefully that not only our current practice but indeed any practice of legal punishment is deeply morally repugnant, no matter how vile the behaviour that is its target. Despite the fact that it may be difficult to imagine a state functioning at all, let alone well, without having recourse to punishing those who break its laws, Zimmerman makes a timely and compelling case for the view that we must seek and put (...) into practice alternative means of preventing crime and promoting social stability. (shrink)