Consciousness is a natural phenomenon, the object of a flourishing area of research in the natural sciences – research whose primary goal is to identify the neural correlates of consciousness. This raises the question: why is there need for a philosophy of consciousness? As we see things, the need for a philosophy of consciousness arises for two reasons. First, as a young and energetic science operating as yet under no guiding paradigm, the science of consciousness has been subject to considerable (...) confusion regarding its methodological, conceptual, and philosophical foundations, and it is philosophy’s mandate to address such confusion in an attempt to regiment scientific practice. Secondly, the identification of a neural feature that correlated perfectly with consciousness would still leave open a certain metaphysical question: is the relation between consciousness and the relevant neural feature merely correlation, or is that correlation indicative of a deeper, more intimate relation between the two? In this paper, we offer an opinionated overview of the philosophy of consciousness as it addresses these two dimensions of consciousness research. (shrink)

A 1% skeptic is someone who has about a 99% credence in non-skeptical realism and about a 1% credence in the disjunction of all radically skeptical scenarios combined. The first half of this essay defends the epistemic rationality of 1% skepticism, appealing to dream skepticism, simulation skepticism, cosmological skepticism, and wildcard skepticism. The second half of the essay explores the practical behavioral consequences of 1% skepticism, arguing that 1% skepticism need not be behaviorally inert.

The global pessimistic meta-induction argues from the falsity of scientific theories accepted in the past to the likely falsity of currently accepted scientific theories. I contend that this argument commits a statistical error previously unmentioned in the literature and is self-undermining. I then compare the global pessimistic meta-induction to a local pessimistic meta-induction based on recent negative assessments of the reliability of medical research. If there is any future in drawing pessimistic conclusions from the history of science, it lies in (...) local meta-inductions, but these meta-inductions will not result in global distrust of the results of science. (shrink)

The underdetermination thesis poses a threat to rational choice of scientific theories. We discuss two arguments for the thesis. One draws its strength from deductivism together with the existence thesis, and the other is defended on the basis of the failure of a reliable inductive method. We adopt a partially subjective/objective pragmatic Bayesian epistemology of science framework, and reject both arguments for the thesis. Thus, in science we are able to reinstate rational choice called into question by the underdetermination thesis.

This article develops a theory of reasons that has strong similarities to Peter Klein's infinitism. The view it develops, Framework Reasons, upholds Klein's principles of avoiding arbitrariness (PAA) and avoiding circularity (PAC) without requiring an infinite regress of reasons. A view of reasons that holds that the “reason for” relation is constrained by PAA and that PAC can avoid an infinite regress if the “reason for” relation is contextual. Moreover, such a view of reasons can maintain that skepticism is false (...) by the maintaining that there is more to epistemic justification than can be expressed in any reasoning session. One crucial argument for Framework Reasons is that justification depends on a background of plausibility considerations. The final section of the article applies this view of reasons to Michael Bergmann's argument that any nonskeptical epistemology must embrace epistemic circularity. (shrink)

Bayesianism is the predominant philosophy of science in North-America, the most important school of statistics world-wide, and the general version of the rational-choice approach in the social sciences. Although often rejected as a theory of actual behavior, it is still the benchmark case of perfect rationality. The paper reviews the development of Bayesianism in philosophy, statistics and decision making and questions its status as an account of perfect rationality. Bayesians, who otherwise are squarely in the empiricist camp, invoke a priori (...) reasoning when they recommend Bayesian methods - a recommendation that is not justified by their own standards. (shrink)

Science depends on judgments of the bearing of evidence on theory. Scientists must judge whether an observation or the result of an experiment supports, disconfirms, or is simply irrelevant to a given hypothesis. Similarly, scientists may judge that, given all the available evidence, a hypothesis ought to be accepted as correct or nearly so, rejected as false, or neither. Occasionally, these evidential judgments can be made on deductive grounds. If an experimental result strictly contradicts a hypothesis, then the truth of (...) the data deductively entails the falsity of the hypothesis. In the great majority of cases, however, the connection between evidence and hypothesis is non-demonstrative, or inductive. In particular, this is so whenever a general hypothesis is inferred to be correct on the basis of the available data, since the truth of the data will not deductively entail the truth of the hypothesis. It always remains possible that the hypothesis is false even though the data are correct. (shrink)

Four important arguments for probabilism—the Dutch Book, representation theorem, calibration, and gradational accuracy arguments—have a strikingly similar structure. Each begins with a mathematical theorem, a conditional with an existentially quantified consequent, of the general form: if your credences are not probabilities, then there is a way in which your rationality is impugned. Each argument concludes that rationality requires your credences to be probabilities. I contend that each argument is invalid as formulated. In each case there is a mirror-image theorem and (...) a corresponding argument of exactly equal strength that concludes that rationality requires your credences not to be probabilities. Some further consideration is needed to break this symmetry in favour of probabilism. (shrink)

In this paper I argue that de Finetti provided compelling reasons for rejecting countable additivity. It is ironical therefore that the main argument advanced by Bayesians against following his recommendation is based on the consistency criterion, coherence, he himself developed. I will show that this argument is mistaken. Nevertheless, there remain some counter-intuitive consequences of rejecting countable additivity, and one in particular has all the appearances of a full-blown paradox. I will end by arguing that in fact it is no (...) paradox, and that what it shows is that conditionalisation, often claimed to be integral to the Bayesian canon, has to be rejected as a general rule in a finitely additive environment. (shrink)

Scientific misconduct is usually assumed to be self-serving. This paper, however, proposes to distinguish between two types of scientific misconduct: ‘type one scientific misconduct’ is self-serving and leads to falsely positive conclusions about one’s own work, while ‘type two scientific misconduct’ is other-harming and leads to falsely negative conclusions about someone else’s work. The focus is then on the latter type, and three known issues are identified as specific forms of such scientific misconduct: biased quality assessment, smear, and officially condoning (...) scientific misconduct. These concern the improper ways how challenges of the prevailing opinion are thwarted in the modern world. The central issue is pseudoskepticism: uttering negative conclusions about someone else’s work that are downright false. It is argued that this may be an emotional response, rather than a calculated strategic action. Recommendations for educative and punitive measures are given to prevent and to deal with these three forms of scientific misconduct. (shrink)

Es werden vier verbreitete Verwendungsweisen des Wortes ‘Argument’ beschrieben, an Beispielen erläutert und dann schrittweise expliziert. Die wichtigsten Explikata sind: ‘eine Satzfolge x ist ein deskriptives Argument in Standardform’, ‘ein deskriptives Argument x in Standardform ist bei der subjektiven Wahrscheinlichkeitsverteilung p stark (bzw. schwach)’, ‘ein Aussagesatz x ist bei der subjektiven Wahrscheinlichkeitsverteilung p ein Argument für (bzw. gegen) einen Aussagesatz y’, ‘ein geordneter Tripel x von deskriptiven Argumenten in Standardform, von Argumentebenen und von Argumentsträngen ist eine deskriptive Argumenthierarchie in Standardform’, (...) ‘eine deskriptive Argumenthierarchie x in Standardform ist gültig (bzw. ungültig; stichhaltig; konsistent; inkonsistent; sichtlich zirkelhaft; stark (bzw. schwach) bei der subjektiven Wahrscheinlichkeitsverteilung p)’. (shrink)

Agreement between "independent" measurements of a theoretically posited quantity is intuitively compelling evidence that a theory is, loosely speaking, on the right track. But exactly what conclusion is warranted by such agreement? I propose a new account of the phenomenon's epistemic significance within the framework of Bayesian epistemology. I contrast my proposal with the standard Bayesian treatment, which lumps the phenomenon under the heading of "evidential diversity".

A piece of folklore enjoys some currency among philosophical Bayesians, according to which Bayesian agents that, intuitively speaking, spread their credence over the entire space of available hypotheses are certain to converge to the truth. The goals of the present discussion are to show that kernel of truth in this folklore is in some ways fairly small and to argue that Bayesian convergence-to-the-truth results are a liability for Bayesianism as an account of rationality, since they render a certain sort of (...) arrogance rationally mandatory. (shrink)

In this paper we show that the coherence measures of Olsson (J Philos 94:246–272, 2002), Shogenji (Log Anal 59:338–345, 1999), and Fitelson (Log Anal 63:194–199, 2003) satisfy the two most important adequacy requirements for the purpose of assessing theories. Following Hempel (Synthese 12:439–469, 1960), Levi (Gambling with truth, New York, A. A. Knopf, 1967), and recently Huber (Synthese 161:89–118, 2008) we require, as minimal or necessary conditions, that adequate assessment functions favor true theories over false theories and true and informative (...) theories over true but uninformative theories. We then demonstrate that the coherence measures of Olsson, Shogenji, and Fitelson satisfy these minimal conditions if we confront the hypotheses with a separating sequence of observational statements. In the concluding remarks we set out the philosophical relevance, and limitations, of the formal results. Inter alia, we discuss the problematic implications of our precondition that competing hypotheses must be confronted with a separating sequence of observational statements, which also leads us to discuss theory assessment in the context of scientific antirealism. (shrink)

We pose and resolve several vexing decision theoretic puzzles. Some are variants of existing puzzles, such as 'Trumped' (Arntzenius and McCarthy 1997), 'Rouble trouble' (Arntzenius and Barrett 1999), 'The airtight Dutch book' (McGee 1999), and 'The two envelopes puzzle' (Broome 1995). Others are new. A unified resolution of the puzzles shows that Dutch book arguments have no force in infinite cases. It thereby provides evidence that reasonable utility functions may be unbounded and that reasonable credence functions need not be countably (...) additive. The resolution also shows that when infinitely many decisions are involved, the difference between making the decisions simultaneously and making them sequentially can be the difference between riches and ruin. Finally, the resolution reveals a new way in which the ability to make binding commitments can save perfectly rational agents from sure losses. (shrink)

Logic is the study of the quality of arguments. An argument consists of a set of premises and a conclusion. The quality of an argument depends on at least two factors: the truth of the premises, and the strength with which the premises confirm the conclusion. The truth of the premises is a contingent factor that depends on the state of the world. The strength with which the premises confirm the conclusion is supposed to be independent of the state of (...) the world. Logic is only concerned with this second, logical factor of the quality of arguments. (shrink)

Reverse inference is the most commonly used inferential strategy for bringing images of brain activation to bear on psychological hypotheses, but its inductive validity has recently been questioned. In this article, I show that, when it is analyzed in likelihoodist terms, reverse inference does not suffer from the problems highlighted in the recent literature, and I defend the appropriateness of treating reverse inference in these terms. 1 Introduction2 Reverse Inference3 Reverse Inference Defended3.1 Typical reverse inferences are fallacious3.2 No quick and (...) easy fix3.3 A likelihoodist defense of reverse inference3.4 An example4 Appropriateness of the Likelihoodist Approach4.1 Likelihoodist reverse inference is not applicable4.2 Cognitive neuroscientists are not interested in comparative conclusions4.3 Reverse inference and negative hypotheses4.4 Likelihoodist reverse inference may confuse cognitive neuroscientists4.5 Bayesian reverse inferences should be preferred to likelihoodist reverse inferences5 Conclusion. (shrink)

Przedmowa Problematyka związana z zależnościami przyczynowymi, ich modelowaniem i odkrywa¬niem, po długiej nieobecności w filozofii i metodologii nauk, budzi współcześnie duże zainteresowanie. Wiąże się to przede wszystkim z dynamicznym rozwojem, zwłaszcza od lat 1990., technik obli¬czeniowych. Wypracowane w tym czasie sieci bayesowskie uznaje się za matematyczny język przyczynowości. Pozwalają one na daleko idącą auto¬matyzację wnioskowań, co jest także zachętą do podjęcia prób algorytmiza¬cji odkrywania przyczyn. Na potrzeby badań naukowych, które pozwalają na przeprowadzenie eksperymentu z randomizacją, standardowe metody ustalania zależności przyczynowych (...) opracowano na początku XX wieku. Zupełnie inaczej sprawa przedstawia się w przypadku badań nieeksperymentalnych, gdzie podobne rozwiązania pozostają kwestią przyszłości. Zadaniem tej książki jest podanie warunków, które powinny być spełnione przez te rozwiązania, oraz sformułowanie proceduralnego kryterium zależności przy¬czynowych jako szczegółowej realizacji tych warunków. Pociąga ono waż¬kie konsekwencje dla filozofii i metodologii nauk, które ujawnia – podany w Części II – zarys me-todolo¬gii proceduralnej. W literaturze przedmiotu brakuje w miarę wszechstronnego i systema¬tycznego omówie¬nia najnowszych filozoficznych i metodologicznych dys¬kusji na temat przy¬czynowości, co niech będzie wytłumaczeniem, dlaczego w niektórych punktach obecnej książki szczegółowo referuję trudno dos¬tępne teksty źró¬dłowe. Przymiotnik „proceduralny” używam tu w znaczeniu węższym niż Huw Price (w którego pracach właściwszy byłby termin „kryterialny”) dla podkre¬ślenia – zgodnie z łacińskim źródłosłowem procedo – że dla ustalenia przy¬czyny niezbędne jest podjęcie przez uczonych określonych interakcji z ba¬daną rzeczywistością. Zalążki zamysłu prezentowanego w tej książce przedstawiłem podczas warsztatów filozoficznych „Philosophy and Probability” w roku 2002, zor¬ganizowanych przez Instytut Filozofii Uniwersytetu w Konstancji. Wdzięczny jestem uczestnikom tych warsztatów za uwagi, a przede wszyst¬kim następującym osobom: Luc Bovens, Brandon Fitelson, Alan Hájek, Stephan Hartmann oraz Jon Williamson. Podczas międzynarodowej konferencji „Analytical Pragmatism”, zorgani¬zowanej w Lublinie w roku 2003 przez Wydział Filo¬zofii Katolickiego Uniwersytetu Lubelskiego, odniosłem swoją koncepcję do prac Nancy Cartwright. Szczególnie inspirujący okazał się komentarz Huw Price’a do mojego referatu i przeprowadzona z nim dysku¬sja. Ujęcie koncepcji metodologii proceduralnej na szerszym tle współ-czes¬nego nurtu empirystycznego w filozofii nauki przedstawiłem w roku 2004 podczas konferencji „5th Quadrennial Fellows Conference”, zorgani¬zowanej przez Instytut Filozofii Uniwersytetu Jagiellońskiego oraz Centrum Filozofii Nauki w Pittsburghu. Szczególnie pomocne w dalszych moich pra¬cach były uwagi Jamesa Bogena, Janet Kourany, Jamesa Lennoxa, Johna Nortona, Thomasa Bonka, Jana Woleńskiego i Johna Worralla, za które wyra¬żam swoją wdzięczność. Korpus książki powstał podczas mojego stażu w Centrum Filozofii Nauki w Pittsburghu, który odbyłem jako stypendysta Fundacji na Rzecz Nauki Polskiej w roku akademickim 2004-2005. Uczestniczyłem w tym czasie w życiu naukowym Centrum i w pracach badawczych zespołu z Instytutu Filozofii Uniwersytetu Carnegie-Mellon w Pittsburghu kierowanego przez Clarka Glymoura. Na jego ręce składam podziękowanie za wiele po¬mocnych uwag do moich wy¬stąpień oraz tekstów i za dyskusje przede wszystkim z nim samym i z jego najbliższymi współpracownikami: Peterem Spirtesem oraz Richardem Scheinesem, a także pozostałymi członkami tego zes¬połu, doktorantami i uczestnikami seminarium badawczego „Causality in the Social Sciences”. Za wieloletnie wsparcie, wielopłaszczyznowe inspiracje towarzyszące pi¬saniu tej książki, a także liczne pomocne uwagi do jej wcześniejszych wersji dziękuję przede wszystkim Księdzu Profesorowi Andrzejowi Bronkowi oraz Księdzu Profesorowi Józefowi Herbutowi, współprowadzącemu seminarium doktorskie w Katedrze Metodologii Nauk Katolickiego Uniwersytetu Lubel¬skiego im. Jana Pawła II, jak również pozostałym uczestnikom tego semina¬rium. Dziękuję mojej Żonie, dr Annie Kawalec za wiele wysiłku włożonego w ulepszenie redakcji – językowej i merytorycznej – obecnej książki. Książkę tę można czytać na kilka sposobów. Czytelnikom zainteresowa¬nym przede wszystkim prowadzeniem badań empirycznych polecałbym rozpoczęcie od Rozdziału 2. i kontynuację pozostałych rozdziałów Części I, a następnie Dodatków. Czytelnikom zainteresowanym problemami filozo¬fii i metodologii nauk polecałbym rozpoczęcie lektury książki od Części II i uzupełniającą lekturę Rozdziału 2., a następnie Wprowadzenia i Zakończenia. Czytelnikom mniej zainteresowanym zagadnieniami teoretycznymi pole¬całbym zapoznanie się z fascynującymi dziejami odkrycia przyczyn cholery przez Johna Snowa, które rekonstruuję w Rozdziale 1. W dalszej części nato¬miast polecałbym przejście do Wprowadzenia i Zakończenia, które w mniej specjalistyczny sposób przybliżają proponowane tu rozstrzygnięcia. Tekst książki nie był dotąd publikowany. Wyjątkiem są pewne fragmenty Rozdziału 8. oraz 9., które w zmienionej postaci ukazały się w Rocznikach Filozoficznych (Kawalec 2004). -/- Lublin, luty 2006 r. (shrink)

Bayesian model selection has frequently been the focus of philosophical inquiry (e.g., Forster, Br J Philos Sci 46:399–424, 1995; Bandyopadhyay and Boik, Philos Sci 66:S390–S402, 1999; Dowe et al., Br J Philos Sci 58:709–754, 2007). This paper argues that Bayesian model selection procedures are very diverse in their inferential target and their justification, and substantiates this claim by means of case studies on three selected procedures: MML, BIC and DIC. Hence, there is no tight link between Bayesian model selection and (...) Bayesian philosophy. Consequently, arguments for or against Bayesian reasoning based on properties of Bayesian model selection procedures should be treated with great caution. (shrink)

The last forty years have produced a dramatic reversal in leading accounts of science. Once thought necessary to (explain) scientific progress, a rigid method of science is now widely considered impossible. Study of products yields to study of processes and practices, .unity gives way to diversity, generality to particularity, logic to luck, and final justification to heuristic scaffolding. I sketch the story, from Bacon and Descartes to the present, of the decline and fall of traditional scientific method, conceived as The (...) Central Planning Bureau for Science or as Rationality Czar. I defend a deflationary account of method and of rational judgment,. with emphasis on heuristic appraisal and cognitive economy. (shrink)

This paper argues for two theses: that degrees of belief are context sensitive; that outright belief is belief to degree 1. The latter thesis is rejected quickly in most discussions of the relationship between credence and belief, but the former thesis undermines the usual reasons for doing so. Furthermore, identifying belief with credence 1 allows nice solutions to a number of problems for the most widely-held view of the relationship between credence and belief, the threshold view. I provide a sketch (...) of a formal framework on which both theses are true. This is a modified Bayesian framework; I argue that despite making credences context-sensitive, the framework lets Bayesians hold on to their signature explanatory successes. The sort of context-sensitivity claimed for credences here mirrors the sort of context-sensitivity I have elsewhere claimed for outright belief: one's credences depend, in part, on the space of alternative possibilities one takes seriously in a context. (shrink)

The interpretation of tests of a point null hypothesis against an unspecified alternative is a classical and yet unresolved issue in statistical methodology. This paper approaches the problem from the perspective of Lindley's Paradox: the divergence of Bayesian and frequentist inference in hypothesis tests with large sample size. I contend that the standard approaches in both frameworks fail to resolve the paradox. As an alternative, I suggest the Bayesian Reference Criterion: it targets the predictive performance of the null hypothesis in (...) future experiments; it provides a proper decision-theoretic model for testing a point null hypothesis and it convincingly accounts for Lindley's Paradox. (shrink)

In this paper I argue that it is finally time to move beyond the Nagelian framework and to break new ground in thinking about epistemic reduction in biology. I will do so, not by simply repeating all the old objections that have been raised against Ernest Nagel’s classical model of theory reduction. Rather, I grant that a proponent of Nagel’s approach can handle several of these problems but that, nevertheless, Nagel’s general way of thinking about epistemic reduction in terms of (...) theories and their logical relations is entirely inadequate with respect to what is going on in actual biological research practice. (shrink)

In this paper we discuss the new Tweety puzzle. The original Tweety puzzle was addressed by approaches in non-monotonic logic, which aim to adequately represent the Tweety case, namely that Tweety is a penguin and, thus, an exceptional bird, which cannot fly, although in general birds can fly. The new Tweety puzzle is intended as a challenge for probabilistic theories of epistemic states. In the first part of the paper we argue against monistic Bayesians, who assume that epistemic states can (...) at any given time be adequately described by a single subjective probability function. We show that monistic Bayesians cannot provide an adequate solution to the new Tweety puzzle, because this requires one to refer to a frequency-based probability function. We conclude that monistic Bayesianism cannot be a fully adequate theory of epistemic states. In the second part we describe an empirical study, which provides support for the thesis that monistic Bayesianism is also inadequate as a descriptive theory of cognitive states. In the final part of the paper we criticize Bayesian approaches in cognitive science, insofar as their monistic tendency cannot adequately address the new Tweety puzzle. We, further, argue against monistic Bayesianism in cognitive science by means of a case study. In this case study we show that Oaksford and Chater’s (2007, 2008) model of conditional inference—contrary to the authors’ theoretical position—has to refer also to a frequency-based probability function. (shrink)

The Linda paradox is a key topic in current debates on the rationality of human reasoning and its limitations. We present a novel analysis of this paradox, based on the notion of verisimilitude as studied in the philosophy of science. The comparison with an alternative analysis based on probabilistic confirmation suggests how to overcome some problems of our account by introducing an adequately defined notion of verisimilitudinarian confirmation.

In this paper, I explore a question about deductive reasoning: why am I in a position to immediately infer some deductive consequences of what I know, but not others? I show why the question cannot be answered in the most natural ways of answering it, in particular in Descartes’s way of answering it. I then go on to introduce a new approach to answering the question, an approach inspired by Hume’s view of inductive reasoning.

A defense of imprecise credences (and other imprecise doxastic attitudes).

Among Bayesian confirmation theorists, several quantitative measures of the degree to which an evidential proposition E confirms a hypothesis H have been proposed. According to one popular recent measure, s, the degree to which E confirms H is a function of the equation P(H|E) − P(H|~E). A consequence of s is that when we have two evidential propositions, E1 and E2, such that P(H|E1) = P(H|E2), and P(H|~E1) ≠ P(H|~E2), the confirmation afforded to H by E1 does not equal the (...) confirmation afforded to H by E2. I present several examples that demonstrate the unacceptability of this result, and conclude that we should reject s (and other measures that share this feature) as a measure of confirmation. (shrink)

P. Kyle Stanford defends the problem of unconceived alternatives, which maintains that scientists are unlikely to conceive of all the scientifically plausible alternatives to the theories they accept. Stanford’s argument has been criticized on the grounds that the failure of individual scientists to conceive of relevant alternatives does not entail the failure of science as a corporate body to do so. I consider two replies to this criticism and find both lacking. In the process, I argue that Stanford does not (...) provide evidence that there are likely scientifically plausible unconceived alternatives to scientific theories accepted now and in the future. (shrink)

This essay addresses the question of when evidence for a stronger claim H1 also constitutes evidence for a weaker claim H2. Although the answer “Always” is tempting, it is false on a natural Bayesian conception of evidence. This essay first describes some prima facie counterexamples to this answer and surveys some weaker answers and rejects them. Next, it proposes an answer, which appeals to the “Dragging Condition.” After explaining and arguing for its use of the Dragging Condition, the essay argues (...) that the Dragging Condition provides a general account of, and solution to, the counterexamples with which the essay began. The essay briefly discusses the relevance of the Dragging Condition to the recently much-discussed topic of “transmission failure” in epistemology, applies the Dragging Condition to the problem of “bootstrapping” in epistemology, and discusses three important objections to the view defended in the essay. (shrink)

In the first paper, I discussed the basic claims of Bayesianism (that degrees of belief are important, that they obey the axioms of probability theory, and that they are rationally updated by either standard or Jeffrey conditionalization) and the arguments that are often used to support them. In this paper, I will discuss some applications these ideas have had in confirmation theory, epistemol- ogy, and statistics, and criticisms of these applications.

Bayesianism is a collection of positions in several related fields, centered on the interpretation of probability as something like degree of belief, as contrasted with relative frequency, or objective chance. However, Bayesianism is far from a unified movement. Bayesians are divided about the nature of the probability functions they discuss; about the normative force of this probability function for ordinary and scientific reasoning and decision making; and about what relation (if any) holds between Bayesian and non-Bayesian concepts.

Additionally, the text shows how to develop computationally feasible methods to mesh with this framework.

Amalgamating evidence of different kinds for the same hypothesis into an overall confirmation is analogous, I argue, to amalgamating individuals’ preferences into a group preference. The latter faces well-known impossibility theorems, most famously “Arrow’s Theorem”. Once the analogy between amalgamating evidence and amalgamating preferences is tight, it is obvious that amalgamating evidence might face a theorem similar to Arrow’s. I prove that this is so, and end by discussing the plausibility of the axioms required for the theorem.

This paper defends the claim that there is a deep tension between the principle of countable additivity and the one-third solution to the Sleeping Beauty problem. The claim that such a tension exists has recently been challenged by Brian Weatherson, who has attempted to provide a countable additivity-friendly argument for the one-third solution. This attempt is shown to be unsuccessful. And it is argued that the failure of this attempt sheds light on the status of the principle of indifference that (...) underlies the tension between countable additivity and the one-third solution. (shrink)

Recent philosophical attention to climate models has highlighted their weaknesses and uncertainties. Here I address the ways that models gain support through observational data. I review examples of model fit, variety of evidence, and independent support for aspects of the models, contrasting my analysis with that of other philosophers. I also investigate model robustness, which often emerges when comparing climate models simulating the same time period or set of conditions. Starting from Michael Weisberg’s analysis of robustness, I conclude that his (...) approach involves a version of reasoning from variety of evidence, enabling this robustness to be a confirmatory virtue.. (shrink)

Kuhn’s famous thesis that there is ‘no unique algorithm’ for choosing between rival scientific theories is analysed using the machinery of social choice theory. It is shown that the problem of theory choice as posed by Kuhn is formally identical to a standard social choice problem. This suggests that analogues of well-known results from the social choice literature, such as Arrow’s impossibility theorem, may apply to theory choice. If an analogue of Arrow’s theorem does hold for theory choice this would (...) refute Kuhn’s thesis, but it would also pose a threat to the rationality of science, a threat that is if anything more worrying than that posed by Kuhn. Various possible ‘escape routes’ from Arrow’s impossibility result are examined, in particular Amartya Sen’s idea of ‘enriching the informational basis’. It is shown that Sen’s idea can be applied to the problem of theory choice in science. This in turn sheds light on two well-known approaches to inductive inference in philosophy of science: Bayesianism and statistical model selection. (shrink)

One’s life can be meaningful, but not worth living, or worth living, but not meaningful, which demonstrates that an evaluation of whether life is worth living differs from an evaluation of whether one’s life is meaningful. But how do these evaluations differ? As I will argue, an evaluation of whether life is worth living is a more comprehensive evaluation than the evaluation of whether one’s individual life is meaningful. In judging whether one finds life worth living, one takes into account, (...) not only whether one’s life is meaningful, but undesirable aspects of life such as chronic pain and suffering. For example, a person who is suffering greatly, but who has lived a meaningful life, might still conclude that his or her life is not worth living. Although the famed question about the meaning of life has received most of the attention, I argue that the better and more fruitful question is “Is life worth living?” One should want, not just for one’s life to be meaningful, but for it to be worth living. (shrink)

It is customary to distinguish experimental from purely observational sciences. The former include physics and molecular biology, the latter astronomy and palaeontology. Experiments involve actively intervening in the course of nature, as opposed to observing events that would have happened anyway. When a molecular biologist inserts viral DNA into a bacterium in his laboratory, this is an experiment; but when an astronomer points his telescope at the heavens, this is an observation. Without the biologist’s handiwork the bacterium would never have (...) contained foreign DNA; but the planets would have continued orbiting the sun whether or not the astronomer had directed his telescope skyward. The observational/experimental distinction would probably be difficult to make precise 1, as the notion of an ‘intervention’ is not easily defined, but it is intuitively fairly clear, and is frequently invoked by scientists and historians of science. Experimentation, or ‘putting questions to nature’, is often cited as a hallmark of the modern scientific method, something that permitted the enormous advances of the last 350 years. And it is sometimes said that the social sciences lag behind the natural because controlled experiments cannot be done so readily in the former. Moreover in certain sciences, e.g. epidemiology, students are explicitly taught that experimental data is preferable to observational data, particularly for doing causal inference. So the distinction between observational and experimental science has quite wide currency, and is often regarded as methodologically significant. Surprisingly, mainstream philosophy of science has had rather little to say about the observational/experimental distinction. 2 For example, discussions of confirmation usually invoke a notion of ‘evidence’, to be contrasted with ‘theory’ or ‘hypothesis’; the aim is to understand how the evidence bears on the hypothesis. But whether this ‘evidence’ comes from observation or experiment generally plays no role in the discussion; this is true …. (shrink)

Robert Stalnaker has argued that mathematical information is information about the sentences and expressions of mathematics. I argue that this metalinguistic account is open to a variant of Alonzo Church's translation objection and that Stalnaker's attempt to get around this objection is not successful. If correct, this tells not only against Stalnaker's account of mathematical truths, but against any metalinguistic account of truths that are both necessary and informative.

Debates about evolution and creation inevitably raise philosophical issues about the nature of scientific knowledge. What is a theory? What is an explanation? How is science different from non- science? How should theories be evaluated? Does science achieve truth? The aim of this chapter is to give a concise and accessible introduction to the philosophy of science, focusing on questions relevant to understanding evolution by natural selection, creation, and intelligent design. For the questions just listed, I state what I think (...) is the best available answer and show how it applies to debates about evolution and creationism. I also indicate alternative answers that are preferred by other philosophers. I hope that the result will be useful for science educators and anyone else involved in controversies about evolution and creation. (shrink)

My dissertation asks how we affect conversational context and how it affects us when we participate in any conversation—including philosophical conversations. Chapter 1 argues that speakers make pragmatic presuppositions when they use proper names. I appeal to these presuppositions in giving a treatment of Frege’s puzzle that is consistent with the claim that coreferential proper names have the same semantic value. I outline an explanation of the way presupposition carrying expressions in general behave in belief ascriptions, and suggest that substitutivity (...) failure is a special case of this behavior. Chapter 2 develops a compositional probabilistic semantics for the language of subjective uncertainty, including epistemic adjectives scoped under quantifiers. I argue that we should distinguish sharply between the effects that epistemically hedged statements have on conversational context, and the effects that they have on belief states. I also suggest that epistemically hedged statements are a kind of doxastic advice, and explain how this hypothesis illuminates some otherwise puzzling phenomena. Chapter 3 argues that ordinary causal talk is deeply sensitive to conversational context. The principle that I formulate to characterize that context sensitivity explains at least some of the oddness of ‘systematic causal overdetermination,’ and explains why some putative overgenerated causes are never felicitously counted, in conversation, as causes. But the principle also makes metaphysical theorizing about causation rather indirectly constrained by ordinary language judgments. (shrink)