After delineating the distinguishing features of pragmatism, and noting the resources that pragmatists have available to respond effectively as pragmatists to the two major objections to pragmatism, I examine and critically evaluate the various proposals that pragmatists have offered as a solution to the problem of induction, followed by a discussion of the pragmatic positions on the status of theoretical entities. Thereafter I discuss the pragmatic posture toward the nature of explanation in science. I conclude that pragmatism has (a) a (...) generally compelling solution to Hume's problem of induction; (b) no specific position on the status of theoretical entities, although something like the non-realism of the sort developed by van Fraassen seems a defensible candidate for most pragmatists in general, even though there are non-trivial objections to van Fraassen's position; and (c) central to the pragmatic conception of scientific explanation is the abandonment of our common conception of truth as a necessary condition for sentences to provide adequate explanations, and a drift in the direction of a contextualist account of explanation. (shrink)

Panpsychism claims that the vast majority of conscious subjects in our world are inanimate and physical. Ensemble explanations account for striking phenomena by placing them within an ensemble of outcomes, most of which are not striking. This paper develops an explanatory problem for panpsychism: panpsychism renders two appealing ensemble explanations unsatisfactory. Specifically, we argue that panpsychism renders unsatisfactory the multiverse explanation of why a universe supports life and the many-planets explanation of why a planet supports life.

Seungbae Park argues that Bas van Fraassen’s rejection of inference to the best explanation (IBE) is problematic for his contextual theory of explanation because van Fraassen uses IBE to support the contextual theory. This paper provides a defense of van Fraassen’s views from Park’s objections. I point out three weaknesses of Park’s objection against van Fraassen. First, van Fraassen may be perfectly content to accept the implications that Park claims to follow from his views. Second, even if van Fraassen rejects (...) IBE he may still endorse particular arguments that instantiate IBE. Third, van Fraassen does not, in fact, use IBE to support his contextual theory. (shrink)

As the demand for explainable deep learning grows in the evaluation of language technologies, the value of a principled grounding for those explanations grows as well. Here we study the state-of-the-art in explanation for neural models for natural-language processing (NLP) tasks from the viewpoint of philosophy of science. We focus on recent evaluation work that finds brittleness in explanations obtained through attention mechanisms.We harness philosophical accounts of explanation to suggest broader conclusions from these studies. From this analysis, we assert the (...) impossibility of causal explanations from attention layers over text data. We then introduce NLP researchers to contemporary philosophy of science theories that allow robust yet non-causal reasoning in explanation, giving computer scientists a vocabulary for future research. (shrink)

According to manipulationist accounts of causal explanation, to explain an event is to show how it could be changed by intervening on its cause. The relevant change must be a ‘serious possibility’ claims Woodward 2003, distinct from mere logical or physical possibility—approximating something I call ‘scientific possibility’. This idea creates significant difficulties: background knowledge is necessary for judgments of possibility. Yet the primary vehicles of explanation in manipulationism are ‘invariant’ generalisations, and these are not well adapted to encoding such knowledge, (...) especially in the social sciences, as some of it is non-causal. Ceteris paribus (CP) laws or generalisations labour under no such difficulty. A survey of research methods such as case and comparative studies, randomised control trials, ethnography, and structural equation modeling, suggests that it would be more difficult and in some instances impossible to try to represent the output of each method in invariant generalisations; and that this is because in each method causal and non-causal background knowledge mesh in a way that cannot easily be accounted for in manipulationist terms. Ceteris paribus-generalisations being superior in this regard, a theory of explanation based on the latter is a better fit for social science. (shrink)

One of the most unsettling problems in the history of philosophy examines how mathematics can be used to adequately represent the world. An influential thesis, stated by Eugene Wigner in his paper entitled "The Unreasonable Effectiveness of Mathematics in the Natural Sciences," claims that "the miracle of the appropriateness of the language of mathematics for the formulation of the laws of physics is a wonderful gift which we neither understand nor deserve." Contrary to this view, this thesis delineates and implements (...) a strategy to show that the applicability of mathematics is very reasonable indeed. I distinguish three forms of the problem of the applicability of mathematics, and focus on one I call the problem of uncanny accuracy: Given that the construction and manipulation of mathematical representations is pervaded by uncertainty, error, approximation, and idealization, how can their apparently uncanny accuracy be explained? I argue that this question has found no satisfactory answer because our rational reconstruction of scientific practice has not involved tools rich enough to capture the logic of mathematical modelling. Thus, I characterize a general schema of mathematical analysis of real systems, focusing on the selection of modelling assumptions, on the construction of model equations, and on the extraction of information, in order to address contextually determinate questions on some behaviour of interest. A concept of selective accuracy is developed to explain the way in which qualitative and quantitative solutions should be utilized to understand systems. The qualitative methods rely on asymptotic methods and on sensitivity analysis, whereas the quantitative methods are best understood using backward error analysis. The basic underpinning of this perspective is readily understandable across scientific fields, and it thereby provides a view of mathematical tractability readily interpretable in the broader context of mathematical modelling. In addition, this perspective is used to discuss the nature of theories, the role of scaling, and the epistemological and semantic aspects of experimentation. In conclusion, we argue for a method of local and global conceptual analysis that goes beyond the reach of the tools standardly used to capture the logic of science; on their basis, the applicability of mathematics finds itself demystified. (shrink)

An increasing number of philosophers have promoted the idea that mechanism provides a fruitful framework for thinking about the explanatory contributions of computational approaches in cognitive neuroscience. For instance, Piccinini and Bahar :453–488, 2013) have recently argued that neural computation constitutes a sui generis category of physical computation which can play a genuine explanatory role in the context of investigating neural and cognitive processes. The core of their proposal is to conceive of computational explanations in cognitive neuroscience as a subspecies (...) of mechanistic explanations. This paper identifies several challenges facing their mechanistic account and sketches an alternative way of thinking about the epistemic roles of computational approaches used in the study of brain and cognition. Drawing on examples from both low-level and systems-level computational neuroscience, I argue that at least some computational explanations of neural and cognitive processes are partially independent from mechanistic constraints. (shrink)

Languages involving modalities and languages involving vagueness have each been thoroughly studied. On the other hand, virtually nothing has been said about the interaction of modality and vagueness. This paper aims to start filling that gap. Section 1 is a discussion of various possible sources of vague modality. Section 2 puts forward a model theory for a quantified language with operators for modality and vagueness. The model theory is followed by a discussion of the resulting logic. In Section 3, the (...) framework will permit us to address a puzzle raised by Elizabeth Barnes and Robert Williams. (shrink)

La discusión acerca de funciones es de larga data en filosofía. Normalmente se describe a la revolución científica del siglo XVII como eliminando las causas finales y la teleología de la física. Sin embargo, el lenguaje funcional cumple un papel central en ciertas áreas de la práctica biológica. Esto ha llevado a muchos filósofos a intentar elucidar el concepto de función, en algunos casos para defender la relevancia de estos usos, en otros para mostrar que se trata de meras formas (...) de hablar que podrían ser eliminadas sin pérdida de ningún tipo de información relevante. El objetivo principal de este trabajo es mostrar la necesidad de apelar a conceptos funcionales para una reconstrucción adecuada de la teoría de la selección natural darwiniana. Pues, se utiliza lenguaje funcional en la conceptualización del campo de aplicación de esta teoría, y tal campo debe ser determinable con independencia la teoría de la selección natural. (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)

Counterpossibles are counterfactuals with necessarily false antecedents. The problem of counterpossibles is easiest to state within the "nearest possible world" framework for counterfactuals: on this approach, a counterfactual is true (roughly) when the consequent is true in the "nearest" possible world where the antecedent is true. Since counterpossibles have necessarily false antecedents, there is no possible world where the antecedent is true. On the approach favored by Lewis, Stalnaker, Williamson, and others, counterpossibles are all trivially true. I introduce several arguments (...) against the trivial approach. First, it is counter-intuitive to think that all counterpossibles are true. Second, if all counterpossibles were true, then we could not make sense of their use in logical, philosophical, or mathematical arguments. Making sense of the role of sentences like these requires that they not have vacuous truth conditions. The account of counterpossibles I ultimately favor is an extension of the "nearest possible world" semantics discussed above. The Lewis/Stalnaker account is supplemented with the addition of impossible worlds, and the nearness metric is extended to range over these impossible worlds as well as possible worlds. Thus, a counterfactual is true when its consequent is true in the nearest world where the antecedent is true; if the counterfactual's antecedent is impossible, then the nearest world in question will be an impossible world. Once the framework of impossible worlds and similarity is in place, we can put it to use in the analysis of other philosophical phenomena. I examine one proposal that makes use of a theory of counterpossibles to develop an analysis of the notion of metaphysical dependence. (shrink)

It is argued in this paper that although much attention has been paid to causal chains and common causes within the literature on probabilistic causality, a primary virtue of that approach is its ability to deal with cases of multiple causation. In doing so some ways are indicated in which contemporary sine qua non analyses of causation are too narrow (and ways in which probabilistic causality is not) and an argument by Reichenbach designed to provide a basis for the asymmetry (...) of causation is refined. The importance of referring causal claims to an abstract model is also emphasized. (shrink)

Philosophical discussion of molecular and developmental biology began in the late 1960s with the use of genetics as a test case for models of theory reduction. With this exception, the theory of natural selection remained the main focus of philosophy of biology until the late 1970s. It was controversies in evolutionary theory over punctuated equilibrium and adaptationism that first led philosophers to examine the concept of developmental constraint. Developmental biology also gained in prominence in the 1980s as part of a (...) broader interest in the new sciences of self-organization and complexity. The current literature in the philosophy of molecular and developmental biology has grown out of these earlier discussions under the influence of twenty years of rapid and exciting growth of empirical knowledge. Philosophers have examined the concepts of genetic information and genetic program, competing definitions of the gene itself and competing accounts of the role of the gene as a developmental cause. The debate over the relationship between development and evolution has been enriched by theories and results from the new field of 'evolutionary developmental biology'. Future developments seem likely to include an exchange of ideas with the philosophy of psychology, where debates over the concept of innateness have created an interest in genetics and development. (shrink)

We introduce two notions–the shadows and the shallows of explanation–in opening up explanation to broader, interdisciplinary investigation. The shadows of explanation refer to past philosophical efforts to provide either a conceptual analysis of explanation or in some other way to pinpoint the essence of explanation. The shallows of explanation refer to the phenomenon of having surprisingly limited everyday, individual cognitive abilities when it comes to explanation. Explanations are ubiquitous, but they typically are not accompanied by the depth that we might, (...) prima facie, expect. We explain the existence of the shadows and shallows of explanation in terms of there being a theoretical abyss between explanation and richer, theoretical structures that are often attributed to people. We offer an account of the shallows, in particular, both in terms of shorn-down, internal, mental machinery, and in terms of an enriched, public symbolic environment, relative to the currently dominant ways of thinking about cognition and the world. (shrink)

Convincing disputes about explanatory reductionism in the philosophy of biology require a clear and precise understanding of what a reductive explanation in biology is. The central aim of this book is to provide such an account by revealing the features that determine the reductive character of a biological explanation. Chapters I-IV provide the ground, on which I can then, in Chapter V, develop my own account of explanatory reduction in biology: Chapter I reveals the meta-philosophical assumptions that underlie my analysis (...) of reduction, Chapter II introduces the previous debate about reduction in the philosophy of biology by pointing out the most crucial lessons one should learn from this debate, Chapter III critically discusses the two perspectives on explanatory reduction that have been proposed in the philosophy of biology so far, and Chapter IV clarifies in what ways the issue of reduction is entangled with the issue of explanation. In Chapter V I present my own account of explanatory reduction. My main claim is that reductive explanations in the biological sciences possess three main characteristics: they explain the behavior of a biological system S, first, exclusively in terms of factors that are located on a lower level of organization than S, second, by focusing on factors that are internal to S , and third, by describing the genuine parts of S only as “parts in isolation”. This account is ontic because it traces the reductivity of an explanation back to certain relations that exist in the world. (shrink)

Do multi-level selection explanations of the evolution of social traits deepen the understanding provided by single-level explanations? Central to the former is a mathematical theorem, the multi-level Price decomposition. I build a framework through which to understand the explanatory role of such non-empirical decompositions in scientific practice. Applying this general framework to the present case places two tasks on the agenda. The first task is to distinguish the various ways of suppressing within-collective variation in fitness, and moreover to evaluate their (...) biological interest. I distinguish four such ways: increasing retaliatory capacity, homogenising assortment, and collapsing either fitness structure or character distribution to a mean value. The second task is to discover whether the third term of the Price decomposition measures the effect of any of these hypothetical interventions. On this basis I argue that the multi-level Price decomposition has explanatory value primarily when the sharing-out of collective resources is `subtractable'. Thus its value is more circumscribed than its champions Sober and Wilson (1998) suppose. (shrink)

This chapter contains sections titled: Highlights of Past Literature Current Work Future Work.

The notion of common cause closedness of a classical, Kolmogorovian probability space with respect to a causal independence relation between the random events is defined, and propositions are presented that characterize common cause closedness for specific probability spaces. It is proved in particular that no probability space with a finite number of random events can contain common causes of all the correlations it predicts; however, it is demonstrated that probability spaces even with a finite number of random events can be (...) common cause closed with respect to a causal independence relation that is stronger than logical independence. Furthermore it is shown that infinite, atomless probability spaces are always common cause closed in the strongest possible sense. Open problems concerning common cause closedness are formulated and the results are interpreted from the perspective of Reichenbach's Common Cause Principle. (shrink)

The usefulness of machine learning algorithms has led to their widespread adoption prior to the development of a conceptual framework for making sense of them. One common response to this situation is to say that machine learning suffers from a “black box problem.” That is, machine learning algorithms are “opaque” to human users, failing to be “interpretable” or “explicable” in terms that would render categorization procedures “understandable.” The purpose of this paper is to challenge the widespread agreement about the existence (...) and importance of a black box problem. The first section argues that “interpretability” and cognates lack precise meanings when applied to algorithms. This makes the concepts difficult to use when trying to solve the problems that have motivated the call for interpretability. Furthermore, since there is no adequate account of the concepts themselves, it is not possible to assess whether particular technical features supply formal definitions of those concepts. The second section argues that there are ways of being a responsible user of these algorithms that do not require interpretability. In many cases in which a black box problem is cited, interpretability is a means to a further end such as justification or non-discrimination. Since addressing these problems need not involve something that looks like an “interpretation” of an algorithm, the focus on interpretability artificially constrains the solution space by characterizing one possible solution as the problem itself. Where possible, discussion should be reformulated in terms of the ends of interpretability. (shrink)

Scientific explanation is an important goal of scientific practise. Philosophers have proposed a striking diversity of seemingly incompatible accounts of explanation, from deductive-nomological to statistical relevance, unification, pragmatic, causal-mechanical, mechanistic, causal intervention, asymptotic, and model-based accounts. In this dissertation I apply two novel methods to reexamine our evidence about scientific explanation in practise and thereby address the fragmentation of philosophical accounts. I start by collecting a data set of 781 articles from one year of the journal Science. Using automated text (...) mining techniques I measure the frequency and distribution of several groups of philosophically interesting words, such as "explain", "cause", "evidence", "theory", "law", "mechanism", and "model". I show that "explain" words are much more common in scientific writing than in other genres, occurring in roughly half of all articles, and that their use is very often qualified or negated. These results about the use of words complement traditional conceptual analysis. Next I use random samples from the data set to develop a large number of small case studies across a wide range of scientific disciplines. I use a sample of "explain" sentences to develop and defend a new general philosophical account of scientific explanation, and then test my account against a larger set of randomly sampled sentences and abstracts. Five coarse categories can classify the explanans and explananda of my cases: data, entities, kinds, models, and theories. The pair of the categories of the explanans and explanandum indicates the "form" of an explanation. The explain-relation supports counterfactual reasoning about the dependence of qualities of the explanandum on qualities of the explanans. But for each form there is a different "core relation" between explanans and explanandum that supports the explain-relation. Causation, modelling, and argument are the core relations for different forms of scientific explanation between different categories of explanans and explananda. This flexibility allows me to resolve some of the fragmentation in the philosophical literature. I provide empirical evidence to show that my general philosophical account successfully describes a wide range of scientific practise across a large number of scientific disciplines. (shrink)

Within the modeling literature, there is often an implicit assumption about the relationship between a given model and a scientific explanation. The goal of this article is to provide a unified framework with which to analyze the myriad relationships between a model and an explanation. Our framework distinguishes two fundamental kinds of relationships. The first is metaphysical, where the model is identified as an explanation or as a partial explanation. The second is epistemological, where the model produces understanding that is (...) related to the explanation of interest. Our analysis reveals that the epistemological relationships are not always dependent on the metaphysical relationships, contrary to what has been assumed by many philosophers of science. Moreover, we identify several importantly different ways that scientific models instantiate these relationships. We argue that our framework provides novel insights concerning the nature of models, explanation, idealization, and understanding. (shrink)

Externalist theories in natural language semantics have become the orthodoxy since Kripke is widely thought to have refuted descriptive theories involving internal cognitive representation of meaning. This shift may be seen in developments in philosophy of language of the 1970s – the direct reference “revolution against Frege”. I consider Fodor’s heretical thought that something has gone “awfully wrong” in this philosophical consensus, perhaps confirming Chomsky’s view that the whole field of philosophical semantics is “utterly wrongheaded” and “crazy” by virtue of (...) its non-naturalist assumptions and “methodological dualism.” Kripke acknowledges that he was led to his views by his “natural intuition”. Accordingly, I take up the aetiological question Chomsky poses, suggesting that we may go beyond the usual analysis of those doctrines that have been assumed too uncritically “to ask why they seem so compelling”. I suggest that the externalist orthodoxy is a kind of cognitive illusion seen elsewhere in philosophy and cognitive science. (shrink)

An account of scientific explanation is presented according to which (1) scientific explanation consists in solving “insight” problems (Metcalfe and Wiebe 1984) and (2) understanding is the result of solving such problems. The theory is pragmatic; it draws upon van Fraassen’s (1977, 1980) insights, avoids the objections to pragmatic accounts offered by Kitcher and Salmon (1987), and relates scientific explanation directly to understanding. The theory also accommodates cases of explanatory asymmetry and intuitively legitimate rejections of explanation requests.

: The common practice of giving (comparing, rejecting and inferring) explanations of phenomena is at the root of articulate learning, including the enterprises we collect under the noun ‘science’. The way that practice privileges a single item from the myriad relevant to any phenomenon tells us something about articulateness itself.

Throughout the last century there has been much discussion over what it is that makes an activity or a theory 'scientific'. In the philosophy of science, conversation has focused on differentiating legitimate science from so-called 'pseudoscience'. In the broader cultural sphere this topic has received attention in multiple legal debates regarding the status of creationism, where it has been generally agreed that the 'supernatural' nature of the claims involved renders them unscientific. In this thesis I focus upon the latter of (...) these issues, arguing that although there may be merit in the larger demarcation project of separating science from pseudoscience, the notion of 'supernaturality' does not belong in this adjudication. Due to the complex cultural issues that have played a role in the history of this topic, this will involve a degree of historical and normative analysis alongside more philosophically abstract considerations. Complicating the discussion is thefact that neither the term 'science' nor 'supernatural' enjoys a widely agreed upon definition. In order to assess the question then, I will survey a wide variety of definitions of each term in order to identify areas of potential conflict. I argue that in none of the prevalent understandings can we find impediment to scientific investigation inherent in the supernaturality of a claim, but rather posit that where difficulty arises it does so for more mundane reasons. I conclude that not only is there no inherent issue with scientific investigation of the supernatural, but that the term 'supernatural' itself is too poorly defined to provide a useful role in philosophical discussion. While I argue that notions of supernaturality should be abandoned entirely when assessing demarcation criteria, I concede that numerous extraneous factors, including the significant degree of overlap between the supernatural and the 'religious', warrant consideration of a compromise position. (shrink)

The paper addresses the question of whether heritability can be useful in establishing genetics as an explanation for an individual’s display of some trait or behavior. After reviewing the fundamental philosophical challenge to heritability—that heritability is a population level measure—an argument is presented for rethinking the role heritability occupies in both causal and explanatory claims. It is argued that heritability can be useful for genetically based explanations of individual traits, if the conditions for proper genetic explanation are modestly reconceived, and (...) the measure is seen as an evidential tool which conforms to standard methods for determining causal factors. (shrink)

Are there arguments in mathematics? Are there explanations in mathematics? Are there any connections between argument, proof and explanation? Highly controversial answers and arguments are reviewed. The main point is that in the case of a mathematical proof, the pragmatic criterion used to make a distinction between argument and explanation is likely to be insufficient for you may grant the conclusion of a proof but keep on thinking that the proof is not explanatory.

The goal of this paper is to present and defend an empiricist, neo-Hempelian account of scientific explanation as ampliative, specialized embedding. The proposal aims to preserve what I take to be the core of Hempel’s empiricist account, by weakening it in some respects and strengthening it in others, introducing two new conditions that solve most of Hempel’s problems without abandoning his empiricist strictures. According to this proposal, to explain a phenomenon is to make it expectable by introducing new conceptual/ontological machinery (...) and using special, and non-ad hoc, non-accidental regularities. The new conditions are elaborated making essential use of two central structuralist ideas, namely T-theoreticity and specialization. I first introduce and qualify the project, then present the new account in detail and assess it vis-à-vis its rivals, and finally discuss some possible objections, concluding that the account fares better than its monistic rivals and well enough to qualify as a promising neo-Hempelian account. Even for those unpersuaded by its monistic goals, it has the merit of calling attention to two new necessary conditions not explicitly emphasized thus far and showing how they serve to answer many of the criticisms addressed against Hempel’s account. (shrink)

The analyses of explanation and causal beliefs are heavily dependent on using probability functions as models of epistemic states. There are, however, several aspects of beliefs that are not captured by such a representation and which affect the outcome of the analyses. One dimension that has been neglected in this article is the temporal aspect of the beliefs. The description of a single event naturally involves the time it occurred. Some analyses of causation postulate that the cause must not occur (...) later than the effect. If we want this kind of causality it is easy to add the appropriate clause to ( CAUS ). An alternative is not to rule out backwards causation or causal loops a priori , but expect that ( CAUS ), via the properties of the contraction P C - , will result in the desired temporal relation between C and E . One way of ensuring this is to postulate that when the probability function P is contracted to P C - , the probabilities of all events that occurred before C remain the same in P C - as in P . This means that all beliefs about the history of events up to C are left unaltered in the construction of the hypothetical state of belief P C - . In conclusion, I hope to have shown that, in spite of these limitations, ( EXP ) and ( CAUS ) provide viable analyses of explanation and causality between single events for the case when epistemic states can be described by probability functions. I have also shown that the two analyses can be used to explicate the close connections between the two notions. These analyses reduce the problems of explanation and causality, hopefully in a non-circular way, to the problem of identifying contractions of states of belief. (shrink)

It is shown that, given any finite set of pairs of random events in a Boolean algebra which are correlated with respect to a fixed probability measure on the algebra, the algebra can be extended in such a way that the extension contains events that can be regarded as common causes of the correlations in the sense of Reichenbach's definition of common cause. It is shown, further, that, given any quantum probability space and any set of commuting events in it (...) which are correlated with respect to a fixed quantum state, the quantum probability space can be extended in such a way that the extension contains common causes of all the selected correlations, where common cause is again taken in the sense of Reichenbach's definition. It is argued that these results very strongly restrict the possible ways of disproving Reichenbach's Common Cause Principle. (shrink)

The aim of this paper is to elaborate a notion of explanation which is applicable to stochastic processes such as quantum processes. The model-theoretic approach was adopted in order to delimit appropriate classes, by defining set-theoretical predicates, of different kinds of physical transformations that quantum systems suffer, either of transitions or of transmutations, by interaction or in a spontaneous manner. To explain a singular quantum process consists in showing that it is feasible to model it as an indeterministic process of (...) certain specified kind. (shrink)