We prove new results on common cause closedness of quantum probability spaces, where by a quantum probability space is meant the projection lattice of a non-commutative von Neumann algebra together with a countably additive probability measure on the lattice. Common cause closedness is the feature that for every correlation between a pair of commuting projections there exists in the lattice a third projection commuting with both of the correlated projections and which is a Reichenbachian common cause of the correlation. The (...) main result we prove is that a quantum probability space is common cause closed if and only if it has at most one measure theoretic atom. This result improves earlier ones published in [1]. The result is discussed from the perspective of status of the Common Cause Principle. Open problems on common cause closedness of general probability spaces (L, ϕ) are formulated, where L is an orthomodular bounded lattice and ϕ is a probability measure on L. (shrink)

The idea that causation can be reduced to transmission of an amount of some conserved quantity between events is spelled out and defended against important objections. Transmission is understood as a symmetrical relation of copresence in two distinct events. The actual asymmetry of causality has its origin in the asymmetrical character of certain irreversible physical processes and then spreads through the causal net. This conception is compatible with the possibility of backwards causation and with a causal theory of time. Genidentity, (...) the persistence of concrete objects, can be given an explanation in causal terms. The transmission theory is shown to escape difficulties faced by two important alternative theories of causation: Salmon's (1984) Mark Transmission Theory and Dowe's (1992a) Conserved Quantities Theory. (shrink)

Most philosophers of physics are eliminativists about causation. Following Bertrand Russell’s lead, they think that causation is a folk concept that cannot be rationally reconstructed within a worldview informed by contemporary physics. Against this thesis, I argue that physics contributes to shaping the concept of causation, in two ways. 1. Special Relativity is a physical theory that expresses causal constraints. 2. The physical concept of a conserved quantity can be used in the functional reduction of the notion of causation. The (...) empirical part of this reduction makes the hypothesis that the transference of an amount of a conserved quantity is a necessary and sufficient condition for causation. This hypothesis is defended against several objections from physics: that amounts of energy do not possess the appropriate identity conditions required for being able to be transmitted, that there is no universal principle of the conservation of energy in General Relativity, and that there are at least two types of physical systems in which causation does not involve any transference: entangled systems in quantum mechanics and the Aharanov-Bohm effect. In order to show that physics provides means to elaborate the concept of causation it is important to avoid certain misunderstandings. In particular, the claim that there is causation in a physical world does not mean that causation is an additional ingredient of the "furniture" of the world, over and above the ingredients identified by physics. (shrink)

Most philosophers of physics are eliminativists about causation. Following Bertrand Russell’s lead, they think that causation is a folk concept that cannot be rationally reconstructed within a worldview informed by contemporary physics. Against this thesis, I argue that physics contributes to shaping the concept of causation, in two ways. (1) Special Relativity is a physical theory that expresses causal constraints. (2) The physical concept of a conserved quantity can be used in the functional reduction of the notion of causation. The (...) empirical part of this reduction makes the hypothesis that the transference of an amount of a conserved quantity is a necessary and sufficient condition for causation. This hypothesis is defended against several objections from physics: that amounts of energy do not possess the appropriate identity conditions required for being able to be transmitted, that there is no universal principle of the conservation of energy in General Relativity, and that there are at least two types of physical systems in which causation does not involve any transference: entangled systems in quantum mechanics and the Aharonov–Bohm effect. In order to show that physics provides means to elaborate the concept of causation it is important to avoid certain misunderstandings. In particular, the claim that there is causation in a physical world does not mean that causation is an additional ingredient of the “furniture” of the world, over and above the ingredients identified by physics. (shrink)

There has been a growing trend to include non-causal models in accounts of scientific explanation. A worry addressed in this paper is that without a higher threshold for explanation there are no tools for distinguishing between models that provide genuine explanations and those that provide merely potential explanations. To remedy this, a condition is introduced that extends a veridicality requirement to models that are empirically underdetermined, highly-idealised, or otherwise non-causal. This condition is applied to models of electroweak symmetry breaking beyond (...) the Standard Model. (shrink)

I consider recent strategies proposed by econometricians for extrapolating causal effects from experimental to target populations. I argue that these strategies fall prey to the extrapolator’s circle: they require so much knowledge about the target population that the causal effects to be extrapolated can be identified from information about the target alone. I then consider comparative process tracing as a potential remedy. Although specifically designed to evade the extrapolator’s circle, I argue that CPT is unlikely to facilitate extrapolation in typical (...) econometrics and evidence-based policy applications. To argue this, I offer a distinction between two kinds of extrapolation, attributive and predictive, the latter being prevalent in econometrics and evidence-based policy. I argue that CPT is not helpful for predictive extrapolation when using the kinds of evidence that econometricians and evidence-based policy researchers prefer. I suggest that econometricians may need to consider qualitative evidence to overcome this problem. (shrink)

Epistemologists have recently debated whether understanding is a species of knowledge. However, because they have offered little in the way of a detailed analysis of understanding, they lack the resources to resolve this issue. In this paper, I propose that S understands why p if and only if S has the non-Gettierised true belief that p, and for some proposition q, S has the non-Gettierised true belief that q is the best available explanation of p, S can correctly explain p (...) with q, and S can identify the features that make q the best explanation of p. On this analysis, understanding is reducible to knowing that p and that q is the best available explanation of p. (shrink)

Jonathan Kvanvig has argued that “objectual” understanding, i.e. the understanding we have of a large body of information, cannot be reduced to explanatory concepts. In this paper, I show that Kvanvig fails to establish this point, and then propose a framework for reducing objectual understanding to explanatory understanding.

Recent literature on non-causal explanation raises the question as to whether explanatory monism, the thesis that all explanations submit to the same analysis, is true. The leading monist proposal holds that all explanations support change-relating counterfactuals. We provide several objections to this monist position. 1Introduction2Change-Relating Monism's Three Problems3Dependency and Monism: Unhappy Together4Another Challenge: Counterfactual Incidentalism4.1High-grade necessity4.2Unity in diversity5Conclusion.

This paper connects two important debates in epistemology—to wit, on the goal of inquiry and on the nature of understanding—and offers a unified knowledge-based account of both.

What exactly is a genetic disease? For a phrase one hears on a daily basis, there has been surprisingly little analysis of the underlying concept. Medical doctors seem perfectly willing to admit that the etiology of disease is typically complex, with a great many factors interacting to bring about a given condition. On such a view, descriptions of diseases like cancer as geneticseem at best highly simplistic, and at worst philosophically indefensible. On the other hand, there is clearly some practical (...) value to be had by classifying diseases according to theirpredominant cause when this can be accomplished in a theoretically satisfactory manner. The question therefore becomes exactly how one should go about selecting a single causal factor among many to explain the presence of disease. When an attempt to defend such causal selection is made at all, the standard accounts offered (Koch's postulates, Hill's epidemiological criteria, manipulability) are all clearly inadequate. I propose, however, an epidemiological account of disease causation which walks the fine line between practical applicability and theoretical considerations of causal complexity and attempts to compromise between patient-centered and population-centered concepts of disease. The epidemiological account is the most basic framework consistent with our strongly held intuitions about the causal classification of disease, yet it avoids the difficulties encountered by its competitors. (shrink)

The Kripkean conception of natural kinds (kinds are defined by essences that are intrinsic to their members and that lie at the microphysical level) indirectly finds support in a certain conception of a law of nature, according to which generalizations must have unlimited scope and be exceptionless to count as laws of nature. On my view, the kinds that constitute the subject matter of special sciences such as biology may very well turn out to be natural despite the fact that (...) their essences fail to be microphysical or micro-based. On the causal conception of natural kinds I privilege, the naturalness of a kind is a function of the fact that it figures prominently in at least one causal law. However, there is a strong tendency prevailing among contemporary philosophers to assume that, in order to count as proper laws generalizations must be expectionless. Since most generalizations tracked down by the special sciences turn out not to fulfill these criteria, what this conception of a law implies is that most of the generalizations the special sciences trade in are not proper laws. It follows that, on this view, most if not all of the kinds the special sciences dealing with turn out not to constitute natural kinds, understood as kinds to which bona fide laws apply. In order to establish that the non-microstructurally defined kinds that fall within the domain of enquiry of the special sciences are eligible for the status of natural kind, I must therefore establish that generalizations needn’t have unlimited scope and be exceptionless to count as laws of nature. This is precisely what I seek to do in this paper. I begin by arguing that the question “what is a law of nature?” is most naturally interpreted as the question “what features must generalizations exhibit in order to ground scientific explanations?” and by offering reasons to believe that generalizations needn’t be exceptionless and have unlimited scope to play the crucial role laws have been thought to play in scientific explanation. Drawing on Sandra Mitchell [Mitchell, S. (2000). Philosophy of Science, 67, 242–265] and James Woodward’s [Woodward, J. (1997). Philosophy of science, 64 (proceedings), 524–541; Woodward, J. (2000). British Journal for the philosophy of science, 51(2), 197–254; Woodward, J. (2001). Philosophy of science, 68, 1–20] work, I subsequently develop an alternative account of the criteria generalizations must satisfy in order to count as laws of nature, which at least some of the generalizations of the special sciences turn out to fulfill. I thus give credence to the idea that at least some of the kinds that fall within the domain of the special sciences figure in laws of nature, and I thereby restore the possibility that some special science kinds deserve to be deemed natural. (shrink)

Recently, it has been provocatively claimed that dynamical modeling approaches signal the emergence of a new explanatory framework distinct from that of mechanistic explanation. This paper rejects this proposal and argues that dynamical explanations are fully compatible with, even naturally construed as, instances of mechanistic explanations. Specifically, it is argued that the mathematical framework of dynamics provides a powerful descriptive scheme for revealing temporal features of activities in mechanisms and plays an explanatory role to the extent it is deployed for (...) this purpose. It is also suggested that more attention should be paid to the distinctive methodological contributions of the dynamical framework including its usefulness as a heuristic for mechanism discovery and hypothesis generation in contemporary neuroscience and biology. (shrink)

In this article, I consider some of the first appearances of a hypothesis of quantized energy between the years 1900 and 1913 and provide an analysis of the nature of the unificatory power of this hypothesis in a Bayesian framework. I argue that the best way to understand the unification here is in terms of informational relevance: on the assumption of the quantum hypothesis, phenomena that were previously thought to be unrelated turned out to yield information about one another on (...) the basis of agreeing measurements of the numerical value of Planck’s constant. (shrink)

In Search Of Mechanisms is a book about the methodology of biology. It is a work by Carl Craver and Lindley Darden, both of whom are well-known individually for their advocacy of mechanistic explanation—in the neurosciences and in the fields of genetics, cytology and molecular biology . Here, the two join forces to give a unified model of biological explanation, not limited to a particular area of biological enquiry, as rooted in the search for mechanisms.The objectives of the book are (...) threefold. First, it sets out to describe what biologists do. This first objective can be described as the goal of making biology more comprehensible. If biology involves the search for mechanisms, then one cannot understand the history of biology and its current practice without understanding mechanisms. Secondly, the book seeks to give a proscriptive account of explanation and the process of explaining some phenomena. This second objective relates to an interest in contributing to the .. (shrink)

Kitcher's unification theory of explanation seems to suggest that only the most reductive accounts can legitimately be termed explanatory. This is not what we find in actual scientific practice. In this paper, I attempt to reconcile these ideas. I claim that Kitcher's theory picks out ideal explanations, but that our term explanation is used to cover other accounts that have a certain relationship with the ideal accounts. At times, versions and portions of ideal explanations can also be considered explanatory.

I offer a new argument for the elimination of ‘beliefs’ from cognitive science based on Wimsatt’s concept of robustness and a related concept of fragility. Theoretical entities are robust if multiple independent means of measurement produce invariant results in detecting them. Theoretical entities are fragile when multiple independent means of detecting them produce highly variant results. I argue that sufficiently fragile theoretical entities do not exist. Recent studies in psychology show radical variance between what self-report and non-verbal behaviour indicate about (...) participants’ beliefs. This is evidence that ‘belief’ is fragile, and is thus a strong candidate for elimination. 1 Introduction2 Robustness and Fragility2.1 A historical example of robustness2.2 Fragility and elimination3 The Received View4 Evidence for the Fragility of Belief4.1 Contamination and fragility4.2 Implicit association tests and fragility5 Attempts to Preserve the Belief Category for Cognitive Science5.1 Beliefs and aliefs5.2 Contradictory beliefs5.3 In-between beliefs and the unity assumption5.4 Belief sub-classes5.5 Self-deception6 Alternative Mental States7 Conclusion. (shrink)

We discuss explanation of an earlier event by a later event, and argue that prima facie cases of backwards event explanation are ubiquitous. Some examples: (1) I am tidying my flat because my brother is coming to visit tomorrow. (2) The scarlet pimpernels are closing because it is about to rain. (3) The volcano is smoking because it is going to erupt soon. We then look at various ways people might attempt to explain away these prima facie cases by arguing (...) that in each case the 'real' explanation is something else. We argue that none of the explaining-away strategies are successful, and so any plausible account of explanation should either make room for backwards explanation, or have a good story to tell about why it doesn't have to. (shrink)

Fundamental assumptions behind qualitative modelling are critically considered and some inherent problems in that modelling approach are outlined. The problems outlined are due to the assumption that a sufficient set of symbols representing the fundamental features of the physical world exists. That assumption causes serious problems when modelling continuous systems. An alternative for intelligent system building for cases not suitable for qualitative modelling is proposed. The proposed alternative combines neural networks and quantitative modelling.

Un partisan du monisme matérialiste qui souscrit au réalisme intentionnel s’engage à octroyer aux contenus des représentations mentales une efficacité causale dans la production d’effets physiques. Deux difficultés se présentent : d’une part, le caractère extrinsèque des propriétés sémantiques paraît inconciliable avec leur efficacité causale ; d’autre part, comme un matérialiste suppose que toute entité qui exemplifie une propriété sémantique exemplifie simultanément des propriétés physiques, celles-ci risquent de priver celle-là d’efficacité causale . La première section est consacrée au premier problème, (...) et la seconde section au second problème.A philosopher who subscribes jointly to physicalism and to intentional realism is bound to grant content causal efficacy in the causation of physical effects. He must then overcome two problems. First, the extrinsicness of semantic properties seems to deprive them of causal power . Secondly, on minimalist physicalist assumptions, no entity can instantiate a semantic property unless it simultaneously instantiates some physical properties. A representation's semantic property risks therefore to be deprived of causal efficacy by its physical properties . I deal with the first problem in the first section of this paper and with the second problem in the second section. (shrink)

In this paper a critique to philosophical approaches that presuppose invariant knowledge for policy purposes is carried out. It is shown that socioeconomic processes do not fit to the logic of stable causal factors, but they are more suited to the logic of "open-ended results". On the basis of this ontological variation it is argued that ex-ante interventions are not appropriate in the socioeconomic realm. On the contrary, they must be understood in a “dynamic” sense. Finally, derivational robustness analysis is (...) proposed as a useful tool for overcoming the problem of “overconstraint”, a typical problem of economic models. (shrink)

This paper argues against Papineau's claim that causal relations can be reduced to correlations and defends Cartwright's thesis that they can be nevertheless boot-strapped from them, given sufficiently rich causal background knowledge.

This paper advances the thesis of methodological mechanism, the claim that to be committed to mechanism is to adopt a certain methodological postulate, i.e. to look for causal pathways for the phenomena of interest. We argue that methodological mechanism incorporates a minimal account of understanding mechanisms, according to which a mechanism just is a causal pathway described in the language of theory. In order to argue for this position we discuss a central example of a biological mechanism, the mechanism of (...) cell death, known as apoptosis. We argue that this example shows that our philosophically deflationary account is sufficient in order to have an illuminating account of mechanisms as the concept is used in biology. (shrink)

Mathematical explanations are poorly understood. Although mathematicians seem to regularly suggest that some proofs are explanatory whereas others are not, none of the philosophical accounts of what such claims mean has become widely accepted. In this paper we explore Wilkenfeld’s suggestion that explanations are those sorts of things that generate understanding. By considering a basic model of human cognitive architecture, we suggest that existing accounts of mathematical explanation are all derivable consequences of Wilkenfeld’s ‘functional explanation’ proposal. We therefore argue that (...) the explanatory criteria offered by earlier accounts can all be thought of as features that make it more likely that a mathematical proof will generate understanding. On the functional account, features such as characterising properties, unification, and salience correlate with explanatoriness, but they do not define explanatoriness. (shrink)

ABSTRACT: Whereas relevance in scientific explanations is usually discussed as if it was a single problem, several criteria of relevance will be distinguished in this paper. Emphasis is laid upon the notion of intra-scientific relevance, which is illustrated using explanation of the law of areas as an example. Traditional accounts of explanation, such as the causal and unificationist accounts, are analyzed against these criteria of relevance. Particularly, it will be shown that these accounts fail to indicate which explanations fulfill the (...) condition of intra-scientific relevance. Finally, the significance of this latter criterion is emphasized, and the epistemic benefits of explanations that fulfill it are highlighted. (shrink)

In this paper, I examine the comparatively neglected intuition of production regarding causality. I begin by examining the weaknesses of current production accounts of causality. I then distinguish between giving a good production account of causality and a good account of production. I argue that an account of production is needed to make sense of vital practices in causal inference. Finally, I offer an information transmission account of production based on John Collier’s work that solves the primary weaknesses of current (...) production accounts: applicability and absences. (shrink)

Current research in molecular epidemiology uses biomarkers to model the different disease phases from environmental exposure, to early clinical changes, to development of disease. The hope is to get a better understanding of the causal impact of a number of pollutants and chemicals on several diseases, including cancer and allergies. In a recent paper Russo and Williamson address the question of what evidential elements enter the conceptualisation and modelling stages of this type of biomarkers research. Recent research in causality has (...) examined Ned Hall’s distinction between two concepts of causality: production and dependence. In another recent paper, Illari examined the relatively under-explored production approach to causality, arguing that at least one job of an account of causal production is to illuminate our inferential practices concerning causal linking. Illari argued that an informational account solves existing problems with traditional accounts. This paper follows up this previous work by investigating the nature of the causal links established in biomarkers research. We argue that traditional accounts of productive causality are unable to provide a sensible account of the nature of the causal link in biomarkers research, while an informational account is very promising. (shrink)

This paper argues that besides mechanistic explanations, there is a kind of explanation that relies upon “topological” properties of systems in order to derive the explanandum as a consequence, and which does not consider mechanisms or causal processes. I first investigate topological explanations in the case of ecological research on the stability of ecosystems. Then I contrast them with mechanistic explanations, thereby distinguishing the kind of realization they involve from the realization relations entailed by mechanistic explanations, and explain how both (...) kinds of explanations may be articulated in practice. The second section, expanding on the case of ecological stability, considers the phenomenon of robustness at all levels of the biological hierarchy in order to show that topological explanations are indeed pervasive there. Reasons are suggested for this, in which “neutral network” explanations are singled out as a form of topological explanation that spans across many levels. Finally, I appeal to the distinction of explanatory regimes to cast light on a controversy in philosophy of biology, the issue of contingence in evolution, which is shown to essentially involve issues about realization. (shrink)

In scientific explanations, the explanans theory is sometimes incommensurable with the explanandum empirical data. How is this possible, especially when the explanation is deductive in nature? This paper attempts to solve the puzzle without relying on any particular theory of reference. For us, it is rather obvious that the geometric idea of projection plays a key role in Keplers explanation of Tycho Brahes empirical data. We discover that a similar mechanism operates in theoretic explanations in general. In short, all theoretic (...) explanations are projective explanations. If so, there should be no logical reason why explanans theories cannot be incommensurable with explanandum data. For illustration, we analyse Einsteins explanation of the results of the Michelson–Morley experiment in some detail. (shrink)

This paper argues that in some explanations mathematics are playing an explanatory rather than a representational role, and that this feature unifies many types of non-causal or non-mechanistic explanations that some philosophers of science have been recently exploring under various names. After showing how mathematics can play either a representational or an explanatory role by considering two alternative explanations of a same biological pattern—“Bergmann’s rule”—I offer an example of an explanation where the bulk of the explanatory job is done by (...) a mathematical theorem, and where mechanisms involved in the target systems are not explanatorily relevant. Then I account for the way mathematical properties may function in an explanatory way within an explanation by arguing that some mathematical propositions involving variables non directly referring to the target system features constitute constraints to which a whole class of systems should comply, provided they are describable by a mathematical object concerned by those propositions. According to such “constraint account”, those mathematical facts are directly entailing the explanandum, as a consequence of such constraints. I call those explanations “structural”, because here properties of mathematical structures are accounting for the explanandum; various kinds of mathematical structures thereby define various types of structural explanations. (shrink)

Following a previous elaboration of the concept of weak individuality and some examples of its instances in ecology and biology, the article focuses on general features of the concept, arguing that in any ontological field individuals are understood on the basis of our knowledge of interactions, through the application of these general formulas for extracting individuals from interactions. Then, the specificities of the individuality in the sense of this weak concept are examined in ecology; I conclude by addressing the differences (...) between ecosystems and organisms as they appear in the viewpoint of such concept. (shrink)

This paper uses formal Darwinism as elaborated by Alan Grafen to articulate an explanatory pluralism that casts light upon two strands of controversies running across evolutionary biology, viz., the place of organisms versus genes, and the role of adaptation. Formal Darwinism shows that natural selection can be viewed either physics-style, as a dynamics of alleles, or in the style of economics as an optimizing process. After presenting such pluralism, I argue first that whereas population genetics does not support optimization, optimality (...) can still be taken as a default hypothesis when modeling evolutionary processes; and second, that organisms have an explanatory role in evolutionary theory, since they are involved in the economic perspective of optimization. Finally, in order to ask whether the Modern Synthesis can indeed provide a theory of organisms, I apply a Kantian-inspired theoretical view of organisms (underlying much developmental modeling), according to which they are both designed entities and subjects of intrinsic circular processes involving the whole organism and its parts. I first show that the design aspect is accountable for in terms of the Modern Synthesis understood in the formal Darwinism framework. I then question whether the latter aspect of organisms can also be ultimately captured in the same framework, and to this purpose devise an empirical test relying on an assessment of the relative weight of genetic elements in developmental and functional gene regulatory networks. (shrink)

ABSTRACT: According to a traditional account, understanding why X occurred is equivalent to knowing that X was caused by Y. This paper defends the account against a major objection, viz., knowing-that is not sufficient for understanding-why, for understanding-why requires a kind of grasp while knowledge-that does not. I discuss two accounts of grasp in recent literature and argue that if either is true, then knowing that X was caused by Y entails at least a rudimentary understanding of why X occurred. (...) If my defense is successful, it would cast doubt on an influential account of the epistemic value of understanding. (shrink)

Hempel seems to hold the following three views: (H1) Understanding is pragmatic/relativistic: Whether one understands why X happened in terms of Explanation E depends on one's beliefs and cognitive abilities; (H2) Whether a scientific explanation is good, just like whether a mathematical proof is good, is a nonpragmatic and objective issue independent of the beliefs or cognitive abilities of individuals; (H3) The goal of scientific explanation is understanding: A good scientific explanation is the one that provides understanding. Apparently, H1, H2, (...) and H3 cannot be all true. Some philosophers think that Hempel is inconsistent, while some others claim that Hempel does not actually hold H3. I argue that Hempel does hold H3 and that he can consistently hold all of H1, H2, and H3 if he endorses what I call the “understanding argument.” I also show how attributing the understanding argument to Hempel can make more sense of his D-N model and his philosophical analysis of the pragmatic aspects of scientific explanation. (shrink)

In this paper, I discuss Michael Moore’s and Jonathan Schaffer’s views on the ontology of omissions in context of their stances on the problem of omissive causation. First, I consider, from a general point of view, the question of the ontology of omissions, and how it relates to the problem of omissive causation. Then I describe Moore’s and Schaffer’s particular views on omissions and how they combine with their stances on the problem of omissive causation. I charge Moore and Schaffer (...) with inconsistencies and insufficiencies within their overall theories, and consider their replies. Finally, I propose my own view on the ontology of omissions and solution to the problem of omissive causation. (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)

Traditionally, a scientific model is thought to provide a good scientific explanation to the extent that it satisfies certain scientific goals that are thought to be constitutive of explanation. Problems arise when we realize that individual scientific models cannot simultaneously satisfy all the scientific goals typically associated with explanation. A given model’s ability to satisfy some goals must always come at the expense of satisfying others. This has resulted in philosophical disputes regarding which of these goals are in fact necessary (...) for explanation, and as such which types of models can and cannot provide explanations. Explanatory monists argue that one goal will be explanatory in all contexts, while explanatory pluralists argue that the goal will vary based on pragmatic considerations. In this paper, I argue that such debates are misguided, and that both monists and pluralists are incorrect. Instead of any goal being given explanatory priority over others in a given context, the different goals are all deeply dependent on one another for their explanatory power. Any model that sacrifices some explanatory goals to attain others will always necessarily undermine its own explanatory power in the process. And so when forced to choose between individual scientific models, there can be no explanatory victors. Given that no model can satisfy all the goals typically associated with explanation, no one model in isolation can provide a good scientific explanation. Instead we must appeal to collections of models. Collections of models provide an explanation when they satisfy the web of interconnected goals that justify the explanatory power of one another. (shrink)

City College of New York The hereditarian theory of race differences in IQ was briefly revived with the appearance of The Bell Curve but then quickly dismissed. The authors attempt a defense of it here, with an eye to conceptual and logical issues of special interests to philosophers, such as alleged infirmities in the heritability concept. At the same time, some relevant post-Bell Curve empirical data are introduced.

The inductive argument from the falsity of most past scientific theories (more than 100 years old) to the falsity of most present ones is defensible, I argue, if it is modified to account for the degrees of theoreticity or observationality in such theories, and the extent to which they are hedged. The case of descriptive astronomy is examined to show that most of the true theories of the 1890s were high in observationality and/or significantly hedged. The false theories of that (...) period, however, were not even approximately true. Apparently, scientists are more interested in supplanting theories with improved observations than in producing true theories. (shrink)

Any theory of explanation must account for the explanatory successes of statistical scientific theories. This should not be done by endorsing determinism. These considerations have been taken as sufficient ground for rejecting the demand on explanations to be deductive. The arguments for doing so, in Coffa (1974) and Salmon (1977, 1984, 1988), are, however, not persuasive. Deductivism is a viable position. Considering that doubts can be raised against the explanatory validity of probabilistic causal relations and the intuitive plausibility of deductivism, (...) it is also a recommendable position, though elaboration is needed in accounting for some of the uses of statistical theories in explanations. (shrink)