The standard mathematical apparatus of classical electromagnetic theory in Minkowski space-time allows an interpretation in terms of retarded distant action, as well as the standard field interpretation. This interpretation is here presented and defended as a scientifically significant alternative to the field theory, casting doubt upon the common view that classical electromagnetic theory provides scientific support for the physical existence of fields as fundamental entities. The various types of consideration normally thought to provide evidence for the existence of the electromagnetic (...) field are surveyed and analyzed in retarded distant action terms, from both a contemporary viewpoint and with regard to the late 19th century context within which the field theory was first generally accepted. It is concluded that acceptance of the field as real is not evidentially justified in either context, and that the customary historical explanation of the triumph of field theory as due to its empirical superiority is inadequate. An alternative explanation is suggested but not developed, appealing to non-empirical factors associated with the research program based on the conservation of energy. (shrink)

Social research, from economics to demography and epidemiology, makes extensive use of statistical models in order to establish causal relations. The question arises as to what guarantees the causal interpretation of such models. In this paper we focus on econometrics and advance the view that causal models are ‘augmented’ statistical models that incorporate important causal information which contributes to their causal interpretation. The primary objective of this paper is to argue that causal claims are established on the basis of a (...) plurality of evidence. We discuss the consequences of ‘evidential pluralism’ in the context of econometric modelling. (shrink)

In a series of insightful publications, Philip Pettit and Frank Jackson have argued for an explanatory ecumenism that is designed to justify a variety of types of social scientific explanation of different , including structural and rational choice explanations. Their arguments are put in terms of different kinds of explanatory information; the distinction between causal efficacy, causal relevance and explanatory relevance within their program model of explanation; and virtual reality and resilience explanation. The arguments are here assessed from the point (...) of view of the illumination they are able to cast on the issue of economics imperialism, the project of privileging rational choice as a unifying basis for explanations. While the Jackson–Pettit arguments turn out to be helpful in specifying some of the ontological and pragmatic constraints on economics imperialism, they are also shown to conflate distinct dimensions in the purported explanantia (such as small grain and particular grain, and the macro and the existentially quantified) and thereby to miss an important class of individualist causal process explanations of social phenomena. (shrink)

A newly emerged field within economics, known as geographical economics claims to have provided a unified approach to the study of spatial agglomerations at different spatial scales by showing how these can be traced back to the same basic economic mechanisms. We analyze this contemporary episode of explanatory unification in relation to major philosophical accounts of unification. In particular, we examine the role of argument patterns in unifying derivations, the role of ontological convictions and mathematical structures in shaping unification, the (...) distinction between derivational and ontological unification, the issue of how explanation and unification relate and finally the idea that unification comes in degrees. (shrink)

In a well-cited book chapter, ecologist Jared Diamond characterizes three main types of experiment performed in community ecology: laboratory experiment, field experiment, and natural experiment. Diamond argues that each form of experiment has strengths and weaknesses, with respect to, for example, realism or the ability to follow a causal trajectory. But does Diamond’s typology exhaust the available kinds of cause-finding practices? Some social scientists have characterized something they call “causal process tracing.” Is this a fourth type of experiment or something (...) else? I examine Diamond’s typology and causal process tracing in the context of a case study concerning the dynamics of wolf and deer populations on the Kaibab Plateau in the 1920s, a case that has been used as a canonical example of a trophic cascade by ecologists but which has also been subject to controversy. I argue that ecologists have profitably deployed causal process tracing together with other types of experiment to help settle questions of causality in this case. It remains to be seen how widespread the use of causal process tracing outside of the social sciences is (or could be), but there are some potentially promising applications, particularly with respect to questions about specific causal sequences. (shrink)

In 1966 the population biologist Richard Levins gave a forceful and in?uential defence of a method called “robustness analysis” (RA). RA is a way of assessing the result of a model by showing that different but related models give the same result. As Levins put it, “our truth is the intersection of independent lies” (1966, 423). Steven Orzack and Elliott Sober (1993) responded with an equally forceful critique of this method, concluding that the idea of robustness “lacks proper de?nition and (...) that its bearing on the question of whether a proposition is true is highly problematic” (533). Replies to Orzack and Sober, from Levins (1993) and Weisberg (2006b), have rejected the idea that RA, on its own, can con?rm the results of models. I argue that these replies have not properly addressed Orzack and Sober’s real criticisms, which focus not on the role of empirical data in RA but on the problem of ensuring that the models used in RA are independent. By drawing on accounts of RA in experimental science, I argue that there is in fact a fallible but viable form of RA that can both con?rm the results of models and incorporate empirical data. However, for reasons other than those of Orzack and Sober, I conclude that RA may be of limited use in model-based science, as the example of ?shery biology can show. (shrink)

This article demonstrates that non-mechanistic, dynamical explanations are a viable approach to explanation in the special sciences. The claim that dynamical models can be explanatory without reference to mechanisms has previously been met with three lines of criticism from mechanists: the causal relevance concern, the genuine laws concern, and the charge of predictivism. I argue, however, that these mechanist criticisms fail to defeat non-mechanistic, dynamical explanation. Using the examples of Haken et al.’s model of bimanual coordination, and Thelen et al.’s (...) dynamical field model of infant perseverative reaching, I show how each mechanist criticism fails once the standards of Woodward’s interventionist framework are applied to dynamical models. An even-handed application of Woodwardian interventionism reveals that dynamical models are capable of producing genuine explanations without appealing to underlying mechanistic details. 1Introduction2Interventionism and Mechanistic Explanation 2.1Causal relevance and ideal interventions2.2Invariance2.3Explanation3Covering-Laws and Dynamical Explanation 3.1Dynamical models3.2Covering-law explanation3.3Prediction4Causal Relevance 4.1The causal relevance concern4.2Intervening on dynamical models4.3Test case I: The Haken–Kelso–Bunz model4.4Test case II: Dynamical field model5Genuine Laws 5.1The genuine laws concern5.2Using invariance in place of laws5.3Test case I: The Haken–Kelso–Bunz model5.4Test case II: Dynamical field model6Prediction 6.1Predictivism6.2Crude and invariant prediction7Interventionist Criticism of the Haken–Kelso–Bunz Model8Dynamical Explanation8Conclusion. (shrink)

Physicalism ? or roughly the view that the stuff that physics talks about is all the stuff there is ? has had a popular press in philosophical circles during the twentieth century. And yet, at the same time, it has become quite fashionable lately to believe that the mind matters in this world after all and that psychology is an autonomous science irreducible to physics. However, if (true, downward) mental causation implies non-reducibility and Physicalism implies the converse, it is hard (...) to see how these two views could be compatible. This paper reviews some classical arguments purportedly showing how the autonomy of the special sciences can be upheld without violating the laws of physics or the principle that physics constitutes a complete and closed system. These arguments are presented in order of increasing strength, indicating how the more popular arguments in fact fall short of establishing anti-reductionism of the intended kind. New arguments are added which claim to demonstrate quite effectively how downward causation is possible compatibly with the reign of physics. The paper begins with a section which distinguishes various kinds of reductionism. (shrink)

Mechanistic explanations are often said to explain because they reveal the causal structure of the world. Conversely, dynamical models supposedly lack explanatory power because they do not describe causal structure. The only way for dynamical models to produce causal explanations is via the 3M criterion: the model must be mapped onto a mechanism. This framing of the situation has become the received view around the viability of dynamical explanation. In this paper, I argue against this position and show that dynamical (...) models can themselves reveal causal structure and consequently produce nonmechanistic, dynamical explanations. Taking the example of cell fates from systems biology, I show how dynamical models, and specifically the attractor landscapes they describe, identify the causes of cell differentiation and explain why cells select particular fates. These dynamical features of the system better fit Woodward’s (2010, 2018) criteria of specificity and proportionality and make them the best candidate causes of cell fates than mechanisms. I also show how these causes are irreducible and inaccessible to mechanistic models, making 3M unworkable and counterproductive in this case. Dynamical models can reveal dynamical causes and thereby provide causal explanations. (shrink)

Mechanistic explanations, according to one prominent account, are derived from objective explanations (Craver 2007, 2014 ). Mechanistic standards of explanation are in turn pulled from nature, and are thereby insulated from the values of investigators, since explanation is an objectively defined achievement grounded in the causal structure of the world (Craver 2014 ). This results in the closure of mechanism’s explanatory standards—it is insulated from the values, norms and goals of investigators. I raise two problems with this position. First, it (...) relies on several ontological claims which, while plausible, fail to guarantee the objectivity of mechanistic explanatory standards to the degree of certainty required. Second, Craver’s position itself introduces a value–laden explanatory standard—the 3M requirement (Kaplan & Craver 2011 )—which undermines the closure of explanatory standards. I show how in practice mechanistic explanation is in part guided by explanatory taste, shorthand for background contextual values that influence our standards of explanation. Mechanism often has a particular pragmatically-oriented taste for control, and gerrymanders explanatory standards in order to obtain it. I conclude by arguing that objectivity, rather than being obtained through the right set of explanatory standards, is better thought of as the result of processes of intersubjective criticism, which renders visible the contextual values of communities of investigators and allows them to be controlled for (Longino 1990 ). (shrink)

Der Artikel führt den Begriff der epistemischen Konkurrenz ein. Im Gegensatz zu „wissenschaftliche Kontroverse“ beschreibt er eine Situation, in der sich zwei Forschungsfelder gegenseitig als mit demselben Bereich von Phänomen befasst wahrnehmen, wobei ihre methodischen Ansätze und theoretischen Erklärungen jedoch so unterschiedlich sind, dass ein offener Konflikt über die Wahrheit oder Falschheit bestimmter Aussagen oder die Genauigkeit in der Anwendung einer Methode nicht stattfindet. Nichtsdestotrotz streben beide Parteien danach, die maßgebliche Erklärung der entsprechenden Phänomene anzubieten. Indem die erweiterte Gemeinschaft der (...) Forschenden oder die Öffentlichkeit einen Ansatz als maßgeblich anerkennt, handeln sie als eine dritte, gewissermaßen neutrale Partei, die einen Preis vergibt, um den die anderen Parteien konkurrieren. Der Artikel beschreibt das Verhältnis von Genetik und Entwicklungsbiologie um 1900 als epistemische Konkurrenz. Diese Forschungsfelder geben unterschiedliche Erklärungen für die Phänomene der organischen Reproduktion. Die Erklärungen unterscheiden sich bezüglich der Formbegriffe und entsprechend hinsichtlich der Begriffe der Vererbung von Aspekten der Form eines Organismus. Zudem basieren die Erklärungen der beiden Felder auf unterschiedlichen Arten kausalen Schließens, die in unterschiedliche experimentelle Ansätze eingebettet sind. Diese Unterschiede können als Instanzen eines allgemeineren Unterschieds zwischen der Tradition der Naturgeschichte, die sich mit Unterschieden zwischen Organismen auseinandersetzt, und der Tradition der Anatomie, die sich mit den Teilen der Organismen beschäftigt, angesehen werden. Dieses Bild der Genetik und Entwicklungsbiologie als Zweige unterschiedlicher fest verankerter Traditionen widerspricht dem Narrativ der Trennung des Begriffs der Vererbung von dem der Entwicklung im Zuge einer Trennung der Disziplinen der Genetik und der Embryologie, das in der Historiographie der Biologie nach wie vor weit verbreitet ist. (shrink)

ZusammenfassungDer Artikel führt den Begriff der epistemischen Konkurrenz ein. Im Gegensatz zu „wissenschaftliche Kontroverse“ beschreibt er eine Situation, in der sich zwei Forschungsfelder gegenseitig als mit demselben Bereich von Phänomen befasst wahrnehmen, wobei ihre methodischen Ansätze und theoretischen Erklärungen jedoch so unterschiedlich sind, dass ein offener Konflikt über die Wahrheit oder Falschheit bestimmter Aussagen oder die Genauigkeit in der Anwendung einer Methode nicht stattfindet. Nichtsdestotrotz streben beide Parteien danach, die maßgebliche Erklärung der entsprechenden Phänomene anzubieten. Indem die erweiterte Gemeinschaft der (...) Forschenden oder die Öffentlichkeit einen Ansatz als maßgeblich anerkennt, handeln sie als eine dritte, gewissermaßen neutrale Partei, die einen Preis vergibt, um den die anderen Parteien konkurrieren. Der Artikel beschreibt das Verhältnis von Genetik und Entwicklungsbiologie um 1900 als epistemische Konkurrenz. Diese Forschungsfelder geben unterschiedliche Erklärungen für die Phänomene der organischen Reproduktion. Die Erklärungen unterscheiden sich bezüglich der Formbegriffe und entsprechend hinsichtlich der Begriffe der Vererbung von Aspekten der Form eines Organismus. Zudem basieren die Erklärungen der beiden Felder auf unterschiedlichen Arten kausalen Schließens, die in unterschiedliche experimentelle Ansätze eingebettet sind. Diese Unterschiede können als Instanzen eines allgemeineren Unterschieds zwischen der Tradition der Naturgeschichte, die sich mit Unterschieden zwischen Organismen auseinandersetzt, und der Tradition der Anatomie, die sich mit den Teilen der Organismen beschäftigt, angesehen werden. Dieses Bild der Genetik und Entwicklungsbiologie als Zweige unterschiedlicher fest verankerter Traditionen widerspricht dem Narrativ der Trennung des Begriffs der Vererbung von dem der Entwicklung im Zuge einer Trennung der Disziplinen der Genetik und der Embryologie, das in der Historiographie der Biologie nach wie vor weit verbreitet ist. (shrink)

Causal analysis in the social sciences takes advantage of a variety of methods and of a multi-fold source of information and evidence. This pluralistic methodology and source of information raises the question of whether we should accordingly have a pluralistic metaphysics and epistemology. This paper focuses on epistemology and argues that a pluralistic methodology and evidence don’t entail a pluralistic epistemology. It will be shown that causal models employ a single rationale of testing, based on the notion of variation. Further, (...) I shall argue that this monistic epistemology is also involved in alternative philosophical theories of causation. (shrink)

I discuss the relevance of the current predicament in cosmology to the debate over scientific realism. I argue that the existence of two, empirically successful but ontologically inconsistent cosmological theories presents difficulties for the realist position.

According to Antoine Augustine Cournot, chance events are the result of the intersection between independent causal chains. This coincidental notion of chance is not a new one, but—as Cournot remarks—it comes from Saint Thomas Aquinas, Boethius, and more probably from Jean de La Placette. Such a conception of chance phenomena seems to be very important, not only because it is closely related to the Principle of Causality, but also since it grounds Cournot’s theory of objective probability. Starting from Martin’s work, (...) the main attempt of this survey is to endorse the idea that Cournot’s coincidental notion of hasard is objective, that is it is ontic and it does not depend—in some sense—on our degree of knowledge. In order to do that, a central role in the discussion will be given to the meaning of the independence between the intersecting causal chains and to Cournot’s conception of causation. (shrink)

Causal exclusion arguments are taken to threaten the autonomy of the special sciences, and the causal efficacy of mental properties. A recent line of response to these arguments has appealed to “independently plausible” and “well grounded” theories of causation to rebut key premises. In this paper I consider two papers which proceed in this vein and show that they share a common feature: they both require causes to be proportional to their effects. I argue that this feature is a bug, (...) and one that generalises: any attempt to rescue the autonomy of the special sciences, or the efficacy of the mental, from exclusion worries had better not look to proportionality for help. (shrink)

In The Levels of Selection (Brandon, 1984), Robert Brandon provides a suggestive but ultimately unsuccessful attempt to use the probabilistic notion ofscreening off in providing a schema for dealing with an aspect of the units of selection question in the philosophy of biology. I characterize that failure, and suggest a revision and expansion of Brandon's account which addresses its key shortcoming.

The aim of this paper is to distinguish between, and examine, three issues surrounding Humphreys's paradox and interpretation of conditional propensities. The first issue involves the controversy over the interpretation of inverse conditional propensities — conditional propensities in which the conditioned event occurs before the conditioning event. The second issue is the consistency of the dispositional nature of the propensity interpretation and the inversion theorems of the probability calculus, where an inversion theorem is any theorem of probability that makes explicit (...) (or implicit) appeal to a conditional probability and its corresponding inverse conditional probability. The third issue concerns the relationship between the notion of stochastic independence which is supported by the propensity interpretation, and various notions of causal independence. In examining each of these issues, it is argued that the dispositional character of the propensity interpretation provides a consistent and useful interpretation of the probability calculus. (shrink)

(1988). The explanative recourse to realism. International Studies in the Philosophy of Science: Vol. 3, No. 1, pp. 2-18. doi: 10.1080/02698598808573321.

The principle of the common cause demands that every pair of causally independent but statistically correlated events should be the effect of a common cause. This demand is often supplemented with the requirement that said cause should screen-off the two events from each other. This paper introduces a new probabilistic model for common causes, which generalises this requirement to include sets of distinct but non-disjoint causes. It is demonstrated that the model hereby proposed satisfies the explanatory function generally attributed to (...) common causes and an existential proof is offered. Finally, the model is compared to other known structures intended to perform a similar function, such as Reichenbachian Common Cause Systems and Bayesian Networks. (shrink)

The principle of the common cause claims that if an improbable coincidence has occurred, there must exist a common cause. This is generally taken to mean that positive correlations between non-causally related events should disappear when conditioning on the action of some underlying common cause. The extended interpretation of the principle, by contrast, urges that common causes should be called for in order to explain positive deviations between the estimated correlation of two events and the expected value of their correlation. (...) The aim of this paper is to provide the extended reading of the principle with a general probabilistic model, capturing the simultaneous action of a system of multiple common causes. To this end, two distinct models are elaborated, and the necessary and sufficient conditions for their existence are determined. (shrink)

The principle of common cause asserts that positive correlations between causally unrelated events ought to be explained through the action of some shared causal factors. Reichenbachian common cause systems are probabilistic structures aimed at accounting for cases where correlations of the aforesaid sort cannot be explained through the action of a single common cause. The existence of Reichenbachian common cause systems of arbitrary finite size for each pair of non-causally correlated events was allegedly demonstrated by Hofer-Szabó and Rédei in 2006. (...) This paper shows that their proof is logically deficient, and we propose an improved proof. (shrink)

The Principle of the Common Cause is usually understood to provide causal explanations for probabilistic correlations obtaining between causally unrelated events. In this study, an extended interpretation of the principle is proposed, according to which common causes should be invoked to explain positive correlations whose values depart from the ones that one would expect to obtain in accordance to her probabilistic expectations. In addition, a probabilistic model for common causes is tailored which satisfies the generalized version of the principle, at (...) the same time including the standard conjunctive-fork model as a special case. (shrink)

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

Diagnoses in medicine are often taken to serve as explanations of patients’ symptoms and signs. This article examines how they do so. I begin by arguing that although some instances of diagnostic explanation can be formulated as covering law arguments, they are explanatory neither in virtue of their argumentative structures nor in virtue of general regularities between diagnoses and clinical presentations. I then consider the theory that medical diagnoses explain symptoms and signs by identifying their actual causes in particular cases. (...) While I take this to be largely correct, I argue that for a diagnosis to function as a satisfactory causal explanation of a patient’s symptoms and signs, it also needs to be supplemented by understanding the mechanisms by which the identified cause produces the symptoms and signs. This mechanistic understanding comes not from the diagnosis itself, but rather from the theoretical framework within which the physician operates. (shrink)

Grounding theorists insist that grounding and explanation are intimately related. This claim could be understood as saying either that grounding ‘inherits’ its properties from explanation or it could be interpreted as saying that grounding plays an important—possibly an indispensable—role in metaphysical explanation. Or both. I argue that saying that grounding ‘inherits’ its properties from explanation can only be justified if grounding is explanatory by nature, but that this view is untenable. We ought therefore to be ‘separatists’ and view grounding and (...) explanation as distinct. As it turns out, though, once grounding has been in this sense distinguished from the explanation it backs, the view that the role grounding plays in explanation justifies its introduction ends up in serious trouble. I conclude that the role grounding plays in explanation does not justify attributing to grounding whatever nature we think it has, and it most likely does not give us any special reason to think grounding exists. (shrink)

In this paper I critically investigate an unorthodox attempt to metaphysically explain in virtue of what there are states of affairs. This is a suggestion according to which states of affairs exist thanks to, rather than, as is the common view, in spite of, the infinite regress their metaphysical explanation seems to engender. I argue that, no matter in which form it is defended, or in which theoretical framework it is set, this suggestion cannot provide us with the explanation we (...) crave. (shrink)

It has been claimed that certain forms of individual essentialism render the Theory of Natural Selection unable to explain why any given individual has the traits it does. Here, three reasons are offered why the Theory ought to ignore these forms of essentialism. First, the trait-distributions explained by population genetics supervene on individual-level causal links, and thus selection must have individual-level effects. Second, even if there are individuals that possess thick essences, they lie outside the domain of the Theory. Finally, (...) the contingency of sexual reproduction suggests that essentialism is misguided in this arena. 1 The problem 2 A reprise of the controversy 3 Enter individual essences 4 How can selection not have individual-level effects? 5 Why can't we get rid of essences we don't like? 6 Is sex necessary? (shrink)

What distinguishes a whole from an arbitrary sum of elements? I suggest a temporal and causal oriented approach. I defend two connected claims. The former is that existence is, by every means, coextensive with being the cause of a causal process. The latter is that a whole is the cause of a causal process with a joint effect. Thus, a whole is something that takes place in time. The approach endorses an unambiguous version of Restricted Composition that suits most commonsensical (...) intuitions about wholes. (shrink)

Some psychologists aim to secure a role for psychological explanations in understanding contemporary social disparities, a concern that plays out in debates over the relevance of the Implicit Association Test. Meta-analysts disagree about the predictive validity of the IAT and about the importance of implicit attitudes in explaining racial disparities. Here, I use the IAT to articulate and explore one route to establishing the relevance of psychological attitudes with small effects: an appeal to a process of “accumulation” that aggregates small (...) effects into large harms. After characterizing mechanisms of accumulation and considering some candidate examples, I argue that such mechanisms suggest how a contemporary attitude with small effects could figure in the explanation of large disparities, but they do not vindicate the importance of such an attitude since such mechanisms are typically also determined by competing causes. I close by sketching several strategies for advancing a defense of the relevance of attitudes with small effects. (shrink)

The leitmotif of Mario Bunge’s work was that the philosophy of science should be informed by a comprehensive scientific philosophy, and vice versa; with both firmly rooted in realism and materialism. Now Bunge left such a big oeuvre, comprising more than 70 books and hundreds of articles, that it is impossible to review it in its entirety. In addition to biographical remarks, this obituary will therefore restrict itself to some select issues of his philosophy: his scientific metaphysics, his philosophy of (...) physics, his concept of mechanismic explanation, his philosophy of social science and technology, and his approach to the demarcation problem. The final section will explore why Bunge, despite the extent and depth of his work, has not achieved a more prominent status in the philosophical community. (shrink)

Recently, Luk mentioned that scientific knowledge both explains and predicts. Do these two functions of scientific knowledge have equal significance, or is one of the two functions more important than the other? This commentary explains why prediction may be mandatory but explanation may be only desirable and optional.

Mechanistic information is used in the field of risk assessment in order to clarify two controversial methodological issues, the selection of inference guides and the definition of standards of evidence. In this paper we present an analysis of the concept of mechanistic information in risk assessment by recurring to previous philosophical analyses of mechanistic explanation. Our conclusion is that the conceptual analysis of mechanistic explanation facilitates a better characterization of the concept of mechanistic information. However, it also shows that the (...) use of this kind of information in risk assessment is heavily influenced by pragmatic factors, which have not been sufficiently taken into account in philosophical analysis. Mechanistic models are like hypothesis that have to be validated empirically. Due to their dependence on the standards of evidence, they are subject to the same pragmatic factors. Therefore, recurring to mechanistic information does not lead to closure of the methodological controversies in risk assessment. (shrink)

The ArgumentIn this paper it will be shown that Newton'sPrincipiagives an explication of and an argument for the first Law of Motion, that seems to be outside the scope of today's philosophy of science but was familiar to seventeenth-century commentators: The foundation of classical mechanics is possible only by recurrence to results of a successful technical practice. Laws of classical mechanics gain their meaning as well as their claims to validity only when considered as statements about artifacts whose production belongs (...) to the shared know-how of a scientific community. (shrink)

Scientific and ‘intuitive’ or ‘folk’ theories are typically characterized as serving three critical functions: prediction, explanation, and control. While prediction and control have clear instrumental value, the value of explanation is less transparent. This paper reviews an emerging body of research from the cognitive sciences suggesting that the process of seeking, generating, and evaluating explanations in fact contributes to future prediction and control, albeit indirectly by facilitating the discovery and confirmation of instrumentally valuable theories. Theoretical and empirical considerations also suggest (...) why explanations may nonetheless feel intrinsically valuable. The paper concludes by considering some implications of the psychology of explanation for a naturalized philosophy of explanation. (shrink)

In pedagogical contexts and in everyday life, we often come to believe something because it would best explain the data. What is it about the explanatory endeavor that makes it essential to everyday learning and to scientific progress? There are at least two plausible answers. On one view, there is something special about having true explanations. This view is highly intuitive: it’s clear why true explanations might improve one’s epistemic position. However, there is another possibility—it could be that the process (...) of seeking, generating, or evaluating explanations itself puts one in a better epistemic position, even when the outcome of the process is not a true explanation. In other words, it could be that accurate explanations are beneficial, or it could be that high-quality explaining is beneficial, where there is something about the activity of looking for an explanation that improves our epistemic standing. The main goal of this paper is to tease apart these two possibilities, both theoretically and empirically, which we align with “Inference to the Best Explanation” and “Explaining for the Best Inference”, respectively. We also provide some initial support for EBI and identify promising directions for future research. (shrink)

I propose a distinct type of robustness, which I suggest can support a confirmatory role in scientific reasoning, contrary to the usual philosophical claims. In model robustness, repeated production of the empirically successful model prediction or retrodiction against a background of independentlysupported and varying model constructions, within a group of models containing a shared causal factor, may suggest how confident we can be in the causal factor and predictions/retrodictions, especially once supported by a variety of evidence framework. I present climate (...) models of greenhouse gas global warming of the 20th Century as an example, and emphasize climate scientists’ discussions of robust models and causal aspects. The account is intended as applicable to a broad array of sciences that use complex modeling techniques. (shrink)