The use of unrealistic assumptions in Economics is usually defended not only for pragmatic reasons, but also because of the intrinsic difficulties in determining the degree of realism of assumptions. Additionally, the criterion used for evaluating economic models is associated with their ability to provide accurate predictions. This mode of thought involves –at least implicitly– a commitment to the existence of unvarying invariant factors or regularities. Contrary to this, the present paper presents a critique to the use of invariant knowledge (...) in economics. One reason for this analysis lies in the fact that economic phenomena are not compatible with the logic of invariance, but with the logic of "possibility trees" or "open-ended results". The other reason is that the use of invariant knowledge may entail both external validity problems and negative exposures to a "black swan". Alternatively, an approach where models are understood as possible scenarios is proposed. It is argued that the realism of assumptions is crucial here, since it helps to ascertain the degree of resemblance between the different models and the target system. (shrink)

Stemming from the realization of the importance of the role of explanation in the science classroom, the Next Generation Science Standards call for appropriately supporting students to learn science, argue from evidence, and provide explanations. Despite the ongoing emphasis on explanations in the science classroom, there seems to be no well-articulated framework that supports students in constructing adequate scientific explanations, or that helps teachers assess student explanations. Our motivation for this article is twofold: First, we think that the ways in (...) which researchers in science education have studied scientific explanation are, at best, leaves much to be desired and, at worst, simply incomplete. Second, we believe that research about the teaching and learning of explanation in science classrooms must be guided by explicit models or frameworks that specify elements involved in constructing explanations particularly applicable to science. More importantly, we think that the development of such models or guidelines should be based on theoretical and philosophical foundations. In order to develop these frameworks or guidelines, we first outline and clarify models of scientific explanation developed by philosophers of science over the last few decades. In the second section of this article, we present a more recent philosophical work on scientific explanation, the pragmatic approach to studying scientific explanations. This approach suggests a toolbox for analyzing scientists’ scientific explanations, which provides a useful instrument to science education. In Section 3, we discuss the ways by which the previous two sections are useful in developing a K-12 scientific explanation schema. Implications for future research on students’ explanations are discussed. (shrink)

Epistemic relativists often appeal to an epistemic incommensurability thesis. One notable example is the position advanced by Wittgenstein in On certainty (1969). However, Ian Hacking’s radical denial of the possibility of objective epistemic reasons for belief poses, we suggest, an even more forceful challenge to mainstream meta-epistemology. Our central objective will be to develop a novel strategy for defusing Hacking’s line of argument. Specifically, we show that the epistemic incommensurability thesis can be resisted even if we grant the very insights (...) that lead Hacking to claim that epistemic reasons are always relative to a style of reasoning. Surprisingly, the key to defusing the argument is to be found in recent mainstream work on the epistemic state of objectual understanding. (shrink)

In his later years, Wesley Salmon believed that the two dominant models of scientific explanation (his own causal-mechanical model and the unificationist model) were reconcilable. Salmon envisaged a 'new consensus' about explanation: he suggested that the two models represent two 'complementary' types of explanation, which may 'peacefully coexist' because they illuminate different aspects of scientific understanding. This paper traces the development of Salmon's ideas and presents a critical analysis of his complementarity thesis. Salmon's thesis is rejected on the basis of (...) two objections, and an alternative view of the relation between different types of explanation is proposed. (shrink)

Veel wetenschappers, filosofen en theologen zijn van mening dat God nooit opgevoerd mag worden als verklaring voor een verschijnsel. Eén argument dat ze hiervoor aandragen is dat het op de een of andere manier in de aard van wetenschap zit dat God er geen rol in kan spelen. In dit artikel ga ik in op een specifieke versie van dit argument. Ik vraag me af of de aard van wetenschappelijke verklaringen uitsluit dat God als verklaringsgrond wordt genoemd. Om die vraag (...) te beantwoorden ga ik na of de door wetenschapsfilosofen ontwikkelde standaardmodellen van wetenschappelijk verklaren ruimte bieden aan theïstische verklaringen. Dat blijkt inderdaad zo te zijn, enige kwalificaties daargelaten. De conclusie moet dan ook luiden dat de aard van wetenschappelijke verklaringen niet zodanig is dat theïstische verklaringen uitgesloten zijn. (shrink)

Michael Zimmerman has recently argued against the twofold Strawsonian claim that there can be no moral responsibility without a moral community and that, as a result, moral responsibility is essentially interpersonal. I offered a number of objections to Zimmerman’s view, to which Zimmerman responded. In this article, I respond to Zimmerman’s responses to my criticisms.

This contribution sheds light on the role of infinite idealization in structural analysis, by exploring how infinite elements and finite element methods are combined in civil engineering models. This combination, I claim, should be read in terms of a ‘complementarity function’ through which the representational ideal of completeness is reached in engineering model-building. Taking a cue from Weisberg’s definition of multiple-model idealization, I highlight how infinite idealizations are primarily meant to contribute to the prediction of structural behavior in Multiphysics approaches.

Newsome ((2003). The debate between current versions of covariation and mechanism approaches to causal inference. Philosophical Psychology, 16, 87-107.) recently published a critical review of psychological theories of human causal inference. In that review, he characterized covariation and mechanism theories, the two dominant theory types, as competing, and offered possible ways to integrate them. I argue that Newsome has misunderstood the theoretical landscape, and that covariation and mechanism theories do not directly conflict. Rather, they rely on distinct sets of reliable (...) indicators of causation, and focus on different types of causation (type vs. token). There are certainly debates in the research field, but the theoretical landscape is not as fractured as Newsome suggests, and a potential unifying framework has already emerged using causal Bayes nets. Philosophical work on causal epistemology matters for psychologists, but not in the way Newsome suggests. (shrink)

A pervasive feature of the sciences, particularly the applied sciences, is an experimental focus on a few (often only one) possible causal connections. At the same time, scientists often advance and apply relatively broad models that incorporate many different causal mechanisms. We are naturally led to ask whether there are normative rules for integrating multiple local experimental conclusions into models covering many additional variables. In this paper, we provide a positive answer to this question by developing several inference rules that (...) use local causal models to place constraints on the integrated model, given quite general assumptions. We also demonstrate the practical value of these rules by applying them to a case study from ecology. Experimental scope in applied sciences Fusing the results of experiments A concrete example of the inference rules Application to a case study. (shrink)

Many approaches to evidence amalgamation focus on relatively static information or evidence: the data to be amalgamated involve different variables, contexts, or experiments, but not measurements over extended periods of time. However, much of scientific inquiry focuses on dynamical systems; the system’s behavior over time is critical. Moreover, novel problems of evidence amalgamation arise in these contexts. First, data can be collected at different measurement timescales, where potentially none of them correspond to the underlying system’s causal timescale. Second, missing variables (...) have a significantly different impact on time series measurements than they do in the traditional static setting; in particular, they make causal and structural inference much more difficult. In this paper, we argue that amalgamation should proceed by integrating causal knowledge, rather than at the level of “raw” evidence. We defend this claim by first outlining both of these problems, and then showing that they can be solved only if we operate on causal structures. We therefore must use causal discovery methods that are reliable given these problems. Such methods do exist, but their successful application requires careful consideration of the problems that we highlight. (shrink)

Mathematicians distinguish between proofs that explain their results and those that merely prove. This paper explores the nature of explanatory proofs, their role in mathematical practice, and some of the reasons why philosophers should care about them. Among the questions addressed are the following: what kinds of proofs are generally explanatory (or not)? What makes a proof explanatory? Do all mathematical explanations involve proof in an essential way? Are there really such things as explanatory proofs, and if so, how do (...) they relate to the sorts of explanation encountered in philosophy of science and metaphysics? (shrink)

I develop an account of homology and homoplasy drawing on their use in biological inference and explanation. Biologists call on homology and homoplasy to infer character states, support adaptationist explanations, identify evolutionary novelties and hypothesize phylogenetic relationships. In these contexts, the concepts must be understood phylogenetically and kept separate: as they play divergent roles, overlap between the two ought to be avoided. I use these considerations to criticize an otherwise attractive view defended by Gould, Hall, and Ramsey & Peterson. By (...) this view, homology and homoplasy can only be delineated qua some level of description, and some homoplasies (parallelisms) are counted as homologous. I develop an account which retains the first, but rejects the second, aspect of that view. I then characterize parallelisms and convergences in terms of their causal role. By the Strict Continuity account, homology and homoplasy are defined phylogenetically and without overlaps, meeting my restriction. Convergence and parallelisms are defined as two types of homoplasy: convergent homoplasies are largely constrained by external factors, while parallelisms are due to internal constraints. (shrink)

. Philosophers and scientists often cite ontic factors when explaining the methods and success of scientific inquiry. That is, the adoption of a method or approach is explained in reference to the kind of system in which the scientist is interested: these are explanations of why scientists do what they do, that appeal to properties of their target systems. We present a framework for understanding such “Opticks to his Principia. Newton’s optical work is largely experiment-driven, while the Principia is primarily (...) mathematical, so usually, each work is taken to exemplify a different kind of science. However, Newton himself often presented them in terms of a largely consistent method. We use our framework to articulate an original and plausible position: that the differences between the Opticks and the Principia are due to the kinds of systems targeted. That is, we provide an ontic-driven explanation of methodological differences. We suspect that ontic factors should have a more prominent role in historical explanations of scientific method and development. (shrink)

Our epistemic access to the past is infamously patchy: historical information degrades and disappears and bygone eras are often beyond the reach of repeatable experiments. However, historical scientists have been remarkably successful at uncovering and explaining the past. I argue that part of this success is explained by the exploitation of dependencies between historical events, entities, and processes. For instance, if sauropod dinosaurs were hot blooded, they must have been gluttons; the high-energy demands of endothermy restrict sauropod grazing strategies. Understanding (...) such dependencies extends our reach into the past in spite of incomplete data. In addition, this serves as a counterexample to two accounts of method in the historical sciences. By one, historical science proceeds by identifying ‘smoking guns’: traces that discriminate between live hypotheses. By the other, historical hypotheses are supported by consilience: the convergence of independent lines of evidence. However, testing for ‘coherency’ between past hypotheses also plays a critical role in historical confirmation. Just as historical scientists exploit dependencies between past entities and present entities to infer what the past was like, they also exploit dependencies between past entities themselves. I do not suggest that archetypical historical science proceeds in this manner. Rather, the lesson I draw is that historical methodology cannot be characterized as archetypically relying on one method or another. Historical science is at base opportunistic, and is resistant to unitary analyses. 1 Introduction2 Snowballs and Explosions: The Basic Idea3 Were Sauropods Endothermic?4 Dependent Entities and Interdependent Explanations5 Smoking Guns and Consilience. (shrink)

We argue that neuroeconomics should be a mechanistic science. We defend this view as preferable both to a revolutionary perspective, according to which classical economics is eliminated in favour of neuroeconomics, and to a classical economic perspective, according to which economics is insulated from facts about psychology and neuroscience. We argue that, like other mechanistic sciences, neuroeconomics will earn its keep to the extent that it either reconfigures how economists think about decision-making or how neuroscientists think about brain mechanisms underlying (...) behaviour. We discuss some ways that the search for mechanisms can bring about such top-down and bottom-up revision, and we consider some examples from the recent neuroeconomics literature of how varieties of progress of this sort might be achieved. (shrink)

Completeness is an important but misunderstood norm of explanation. It has recently been argued that mechanistic accounts of scientific explanation are committed to the thesis that models are complete only if they describe everything about a mechanism and, as a corollary, that incomplete models are always improved by adding more details. If so, mechanistic accounts are at odds with the obvious and important role of abstraction in scientific modelling. We respond to this characterization of the mechanist’s views about abstraction and (...) articulate norms of completeness for mechanistic explanations that have no such unwanted implications. _1_ Introduction _2_ A Balancing Act: When Do Details Matter? _3_ The Norms of Causal Explanation _4_ The Norms of Constitutive Explanation _5_ Salmon-Completeness _6_ From More Details to More Relevant Details _7_ Non-explanatory Virtues of Abstraction _8_ From Explanatory Models to Explanatory Knowledge _9_ Mechanistic Completeness Reconsidered _10_ Conclusion. (shrink)

The main focus of this paper is the question as to what it is for an individual to think of her environment in terms of a concept of causation, or causal concepts, in contrast to some more primitive ways in which an individual might pick out or register what are in fact causal phenomena. I show how versions of this question arise in the context of two strands of work on causation, represented by Elizabeth Anscombe and Christopher Hitchcock, respectively. I (...) then describe a central type of reasoning that, I suggest, a subject has to be able to engage in, if we are to credit her with causal concepts. I also point out that this type of reasoning turns on the idea of a physical connection between cause and effect, as articulated in recent singularist approaches of causation. (shrink)

How do why-interrogatives work? How do they express the questions they express, in the contexts in which they express them? In this essay, I argue that, at a fundamental level, why-interrogatives work just like other wh-interrogatives, particularly other adjunct wh-interrogatives, and they express the questions they express, in the contexts in which they express them, by the same means that other wh-interrogatives do. These conclusions go against a trend in recent work on why-interrogatives, which holds that they are syntactically and (...) semantically unlike other wh-interrogatives. Since the claim that why-interrogatives are unlike other wh-interrogatives has been taken to support various philosophical theses about the nature of why-questions and explanation, showing that why-interrogatives are just like other wh-interrogatives undermines this line of support for these theses. (shrink)

The most expressive account of explanations in neuroscience is currently the causal-mechanistic model formulated by Carl Craver. According to him, explanations in neuroscience describe mechanisms, in other words, it points out how parts organize themselves and interact to engender the phenomenon. Furthermore, neuroscience is unified as scientists from different areas that compose it work together to develop mechanisms. This model was extensively discussed in the last years and several criticisms were raised towards it. Still, it remains as the soundest model (...) for explanations in neuroscience nowadays. This paper is presented as a review of this model, as well as the critiques worked out against it and finishes with a brief consideration of the problem of explanation in neuroscience. (shrink)

Life-science phenomena are often explained by specifying the mechanisms that bring them about. The new mechanistic philosophers have done much to substantiate this claim and to provide us with a better understanding of what mechanisms are and how they explain. Although there is disagreement among current mechanists on various issues, they share a common core position and a seeming commitment to some form of scientific realism. But is such a commitment necessary? Is it the best way to go about mechanistic (...) explanation? In this article, we propose an alternative antirealist account that also fits explanatory practice in the life sciences. We pay special attention to mechanistic models, i.e. scientific models that involve a mechanism, and to the role of coherence considerations in building such models. To illustrate our points, we consider the mechanism for the action potential. 1 Introduction2 Some Core Features of Mechanistic Explanation3 Scientific Realism and Mechanistic Explanation4 Antirealist Mechanistic Explanation: The Case of the Action Potential5 Some Outstanding Issues for the Antirealist Mechanist6 Two Problems for the Realist Mechanist7 Conclusions. (shrink)

This paper brings together results from the philosophy and the psychology of explanation to argue that there are multiple concepts of explanation in human psychology. Specifically, it is shown that pluralism about explanation coheres with the multiplicity of models of explanation available in the philosophy of science, and it is supported by evidence from the psychology of explanatory judgment. Focusing on the case of a norm of explanatory power, the paper concludes by responding to the worry that if there is (...) a plurality of concepts of explanation, one will not be able to normatively evaluate what counts as good explanation. (shrink)

Explanation is a central concept in human psychology. Drawing upon philosophical theories of explanation, psychologists have recently begun to examine the relationship between explanation, probability and causality. Our study advances this growing literature in the intersection of psychology and philosophy of science by systematically investigating how judgments of explanatory power are affected by the prior credibility of a potential explanation, the causal framing used to describe the explanation, the generalizability of the explanation, and its statistical relevance for the evidence. Collectively, (...) the results of our five experiments support the hypothesis that the prior credibility of a causal explanation plays a central role in explanatory reasoning: first, because of the presence of strong main effects on judgments of explanatory power, and second, because of the gate-keeping role it has for other factors. Highly credible explanations were not susceptible to causal framing effects. Instead, highly credible hypotheses were sensitive to the effects of factors which are usually considered relevant from a normative point of view: the generalizability of an explanation, and its statistical relevance for the evidence. These results advance current literature in the philosophy and psychology of explanation in three ways. First, they yield a more nuanced understanding of the determinants of judgments of explanatory power, and the interaction between these factors. Second, they illuminate the close relationship between prior beliefs and explanatory power. Third, they clarify the relationship between abductive and probabilistic reasoning. (shrink)

Clinicians and cognitive scientists typically conceive of delusions as doxastic—they view delusions as beliefs. But some philosophers have countered with anti-doxastic objections: delusions cannot be beliefs because they fail the necessary conditions of belief. A common response involves meeting these objections on their own terms by accepting necessary conditions on belief but trying to blunt their force. I take a different approach by invoking a cognitive-phenomenal view of belief and jettisoning the rational/behavioural conditions. On this view, the anti-doxastic claims can (...) be rejected outright, and doxasticism can be defended. I call this the cognitive phenomenological defence of doxasticism. (shrink)

Current philosophical accounts of causation suggest that the same causal assertion can have different meanings. Yet, in actual social-scientific practice, the possible meanings of some causal generalisations intended to support policy prescriptions are not always spelled out. In line with a standard referentialist approach to semantics, we propose and elaborate on four questions to systematically elucidate the meaning of causal generalisations. The analysis can be useful to a host of agents, including social scientists, policy-makers, and philosophers aiming at being socially (...) relevant. To illustrate our proposal, we analyse the complexities related to the meaning of causal generalisations in the context of a concrete case of economic research which is explicitly intended to guide public policy, namely, the OECD research on the causes of unemployment. (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)

Some explanations in social science, psychology and biology belong to a higher level than other explanations. And higher explanations possess the virtue of abstracting away from the details of lower explanations, many philosophers argue. As a result, these higher explanations are irreplaceable. And this suggests that there are genuine higher laws or patterns involving social, psychological and biological states. I show that this ‘abstractness argument’ is really an argument schema, not a single argument. This is because the argument uses the (...) ‘is lower than’ relation, and this relation admits of different readings. I then suggest four rigorous definitions of the ‘is lower than’ relation, and show that the abstractness argument’s prospects are much brighter for some of these definitions than for others. To show this, I evaluate the so-called ‘disjunctive threat’ to the abstractness argument. (shrink)

The most common way of analysing the meaning of causal generalisations relies on referentialist semantics. In this article, we instead develop an analysis based on inferentialist semantics. According to this approach, the meaning of a causal generalisation is constituted by the web of inferential connections in which the generalisation participates. We distinguish and discuss five classes of inferential connections that constitute the meaning of causal generalisations produced in policy-oriented economic research. The usefulness of our account is illustrated with the analysis (...) of generalisations about unemployment put forward by the Organisation for Economic Co-operation and Development in its highly influential 1994 OECD Jobs Study. The article ends with a discussion of some crucial philosophical questions about the use of inferentialism in the analysis of causal generalisations. (shrink)

The Gettier Problem is the problem of revising the view that knowledge is justified true belief in a way that is immune to Gettier counter-examples. The “Gettier Problem problem”, according to Lycan, is the problem of saying what is misguided about trying to solve the Gettier Problem. In this paper I take up the Gettier Problem problem. I distinguish giving conditions that are necessary and sufficient for knowledge from giving conditions that explain why one knows when one does know. I (...) argue that the problem with the Gettier Problem is that it requires us to articulate conditions that suffice for knowledge even if those conditions are non-explanatory. After defending this view, I take up two related methodological issues, one about the evidence that can be given in favor of an account of knowledge, and one about the role that investigating justification might play in investigating knowledge. (shrink)

ABSTRACT The exclusion problem is meant to show that non-reductive physicalism leads to epiphenomenalism: if mental properties are not identical with physical properties, then they are not causally efficacious. Defenders of a difference-making account of causation suggest that the exclusion problem can be solved because mental properties can be difference-making causes of physical effects. Here, we focus on what we dub an incompatibilist implementation of this general strategy and argue against it from a non-reductive physicalist perspective. Specifically, we argue that (...) incompatibilism undermines either the non-reductionist or the physicalist aspirations of non-reductive physicalism. (shrink)

I seek to provide a systematic and comprehensive framework for the description and analysis of scientific practice—a philosophical grammar of scientific practice, ‘grammar’ as meant by the later Wittgenstein. I begin with the recognition that all scientific work, including pure theorizing, consists of actions, of the physical, mental, and ‘paper-and-pencil’ varieties. When we set out to see what it is that one actually does in scientific work, the following set of questions naturally emerge: who is doing what, why, and how? (...) More specifically, we must arrive at some coherent philosophical accounts of the following elements of scientific practice: the agent—free, embodied, and constantly in second-person interactions with other agents; the purposes and proximate aims of the agent; types of activities that the agent engages in; ontological principles necessarily presumed for the performance of particular activities; instruments and other resources that the agent pulls together for the performance of each activity. After sketching the general framework, I also give some illustrative contrasts between the more traditional descriptions of scientific practice and the kind of descriptions enabled by the proposed framework. (shrink)

It is commonly assumed that the concept of mechanism is a keytool for the scientific understanding of observable phenomena. However, there is no single definition of mechanism in the current philosophy of science. In fact, philosophers have developed several characterizations of what seemed to be a clear intuitive concept for scientists. In this paper, I will analyze these philosophical conceptions of mechanism, highlighting their problematic aspects and proposing a new mechanistic approach based on the idea that the pertinent levels of (...) organization for a mechanistic explanation can be identified with intervals of quasi-decompositionality. I argue that this approach allows us to consider that activities are directly derived from the entities’ structure. Consequently, a mechanistic explanation implies an arbitrary but not capricious choice of an organizational level. According to this approach, inter-level causation is merely apparent and there is no place for emergent properties. (shrink)

Glennan appeals to interventions to solve the ontological and explanatory regresses that threaten his mechanistic account of causality . I argue that Glennan’s manoeuvre fails. The appeal to interventions is not able to address the ontological regress, and it blocks the explanatory regress only at the cost of making the account inapplicable to non-modular mechanisms. I offer a solution to the explanatory regress that makes use of dynamic Bayesian networks. My argument is illustrated by a case study from systems biology, (...) namely, the mechanism for the irreversibility of apoptosis. I conclude by pointing out the implications of my argument for Glennan’s mechanistic account of causality and, more generally, for accounts of mechanistic explanation based on interventions. 1 Introduction2 Glennan’s Account of Causality3 Objections to Glennan’s Account4 Glennan’s Replies5 Ontological Symmetry?6 Explanatory Symmetry?7 A Solution to the Explanatory Regress8 The Prospects of Glennan’s Account. (shrink)

Knobe's laudable conclusion that we make sense of our social world based on moral considerations requires a development account of human thought and a theoretical framework. We outline a view that such a moral framework must be rooted in social interaction.

The arguments for and against a truth-relativist semantics for propositional knowledge attributions (KTR) have been debated almost exclusively in the philosophy of language. But what implications would this semantic thesis have in epistemology? This question has been largely unexplored. The aim of this paper is to establish and critique several ramifications of KTR in mainstream epistemology. The first section of the paper develops, over a series of arguments, the claim that MacFarlane's (2005, 2010) core argument for KTR ultimately motivates (for (...) better or worse) the extension of a truth-relativist semantics to a subset of understanding attributions – attributions of understanding-why. I conclude by presenting some reasons to think that even if KTR were otherwise plausible, a truth-relativist semantics for understanding-why attributions is not. These claims, taken together, constitute a kind of epistemological argument against MacFarlane-style truth-relativism for knowledge attributions. (shrink)

A theory of conceptual development must specify the innate representational primitives, must characterize the ways in which the initial state differs from the adult state, and must characterize the processes through which one is transformed into the other. The Origin of Concepts (henceforth TOOC) defends three theses. With respect to the initial state, the innate stock of primitives is not limited to sensory, perceptual, or sensorimotor representations; rather, there are also innate conceptual representations. With respect to developmental change, conceptual development (...) consists of episodes of qualitative change, resulting in systems of representation that are more powerful than, and sometimes incommensurable with, those from which they are built. With respect to a learning mechanism that achieves conceptual discontinuity, I offer Quinian bootstrapping. TOOC concludes with a discussion of how an understanding of conceptual development constrains a theory of concepts. (shrink)

Reductive intellectualists about knowledge-how hold, contra Ryle, that knowing how to do something is just a kind of propositional knowledge. In a similar vein, traditional reductivists about understanding-why insist, in accordance with a tradition beginning with Aristotle, that the epistemic standing one attains when one understands why something is so is itself just a kind of propositional knowledge—viz., propositional knowledge of causes. A point that has been granted on both sides of these debates is that if these reductive proposals are (...) right, then knowledge-how and understanding-why should be susceptible to the same extent as knowledge-that is to being undermined by epistemic luck. This paper reports experimental results that test these luck-based predictions. Interestingly, these results suggest a striking positive correlation between self-reported philosophical expertise and attributions of knowledge-how, understanding-why and knowledge-that which run contrary to reductive proposals. We contextualize these results by showing how they align very well with a particular kind of overarching non-reductive proposal, one that two of the authors have defended elsewhere according to which knowledge-how and understanding-why, but not knowledge-that, essentially involve cognitive achievement. We conclude by situating the interpretive narrative advanced within contemporary discussions about the role of expertise in philosophical judgment. (shrink)

I set out two theses. The first is Lynn Robertson’s: (a) spatial awareness is a cause of object perception. A natural counterpoint is: (b) spatial awareness is a cause of your ability to make accurate verbal reports about a perceived object. Zenon Pylyshyn has criticized both. I argue that nonetheless, the burden of the evidence supports both (a) and (b). Finally, I argue conscious visual perception of an object has a different causal role to both: (i) non-conscious perception of the (...) object, and (ii) experience, e.g. hallucination, that may be subjectively indiscriminable from, but is not, perception of the object. (shrink)

Este trabajo propone una herramienta teórica con la que es posible comparar diferentes explicaciones dirigidas a un mismo objeto de estudio. Esta herramienta se compone de tres conjuntos de virtudes: epistémicas, analíticas y pragmáticas. Para apoyar lo anterior se ofrecen dos estudios de caso, el primero compara dos explicaciones psicológicas sobre el espectro autista, el segundo compara dos explicaciones sobre el origen de los números desde una perspectiva empirista.

This contribution claims that the two fundamental notions of causation at work in the health sciences are manipulative and mechanistic, and investigates what kinds of evidence matter for the assessment of causal relations. This article is a development of our 2007 article, ‘Plurality of Causality’, where we argue for a pluralistic account of causation with an eye to econometrics and a single medical example. The present contribution has a wider focus, and considers the notion of evidence within a whole range (...) of disciplines belonging to the health sciences. Section 1 addresses the relations between kinds of evidence and causal accounts, and it is shown how different notions of causation can be employed in various medical cases. Section 2 calls attention to issues crucial for any adequate epistemological theory of causation, such as the distinctions between types and tokens, observational and experimental regimes, explanation and prediction. Lastly, the notion of context is articulated, highlighted in its role in the assessment of causal links. All these issues are tackled in the framework of what we label a ‘bottom–up’ epistemology. (shrink)

I introduce the notion of a ‘control variable’ which gives us a way of seeing how mental causation could be an unproblematic case of causation in general, rather than being some sui generis form of causation. Psychological variables may be the control variables for a system for which there are no physical control variables, even in a deterministic physical world. That explains how there can be psychological causation without physical causation, even in a deterministic physical world.

Our use of ‘I’, or something like it, is implicated in our self-regarding emotions, in the concern to survive, and so seems basic to ordinary human life. But why does that pattern of use require a referring term? Don't Lichtenberg's formulations show how we could have our ordinary pattern of use here without the first person? I argue that what explains our compulsion to regard the first person as a referring term is our ordinary causal thinking, which requires us to (...) find a persisting object as the mechanism that underpins the causal structure we naturally ascribe to the self. I thus argue against Peacocke's picture (2012), on which it's the cogito that explains one's knowledge of one's own existence. (shrink)

Recent work by Brian Skyrms offers a very general way to think about how information flows and evolves in biological networks — from the way monkeys in a troop communicate, to the way cells in a body coordinate their actions. A central feature of his account is a way to formally measure the quantity of information contained in the signals in these networks. In this paper, we argue there is a tension between how Skyrms talks of signalling networks and his (...) formal measure of information. Although Skyrms refers to both how information flows through networks and that signals carry information, we show that his formal measure only captures the latter. We then suggest that to capture the notion of flow in signalling networks, we need to treat them as causal networks. This provides the formal tools to define a measure that does capture flow, and we do so by drawing on recent work defining causal specificity. Finally, we suggest that this new measure is crucial if we wish to explain how evolution creates information. For signals to play a role in explaining their own origins and stability, they can’t just carry information about acts: they must be difference-makers for acts. (shrink)

In this article, I consider an important challenge to the popular theory of scientific inference commonly known as ‘inference to the best explanation’, one that has received scant attention.1 1 The problem is that there exists a wide array of rival models of explanation, thus leaving IBE objectionably indeterminate. First, I briefly introduce IBE. Then, I motivate the problem and offer three potential solutions, the most plausible of which is to adopt a kind of pluralism about the rival models of (...) explanation. However, I argue that how ranking explanations on this pluralistic account of IBE remains obscure and pluralism leads to contradictory results. In light of these objections, I attempt to dissolve the problem by showing why IBE does not require a ‘model’ of explanation and by giving an account of what explanation consists in within the context of IBE. (shrink)

In this paper, I consider the relationship between Inference to the Best Explanation and Bayesianism, both of which are well-known accounts of the nature of scientific inference. In Sect. 2, I give a brief overview of Bayesianism and IBE. In Sect. 3, I argue that IBE in its most prominently defended forms is difficult to reconcile with Bayesianism because not all of the items that feature on popular lists of “explanatory virtues”—by means of which IBE ranks competing explanations—have confirmational import. (...) Rather, some of the items that feature on these lists are “informational virtues”—properties that do not make a hypothesis \ more probable than some competitor \ given evidence E, but that, roughly-speaking, give that hypothesis greater informative content. In Sect. 4, I consider as a response to my argument a recent version of compatibilism which argues that IBE can provide further normative constraints on the objectively correct probability function. I argue that this response does not succeed, owing to the difficulty of defending with any generality such further normative constraints. Lastly, in Sect. 5, I propose that IBE should be regarded, not as a theory of scientific inference, but rather as a theory of when we ought to “accept” H, where the acceptability of H is fixed by the goals of science and concerns whether H is worthy of commitment as research program. In this way, IBE and Bayesianism, as I will show, can be made compatible, and thus the Bayesian and the proponent of IBE can be friends. (shrink)

The purpose of this article is to examine two important issues concerning the agency theory of causality: the charge of anthropomorphism and the relation of simultaneous causation. After a brief outline of the agency theory, sections 2–4 contain the refutation of the three main forms in which the charge of anthropomorphism is to be found in the literature. It will appear that it is necessary to distinguish between the subjective and the objective aspect of the concept of causation. This will (...) lead, in section 5, to contrast two kinds of anthropomorphism, one which has been rightly rejected by modern science and one which is fully compatible with the objective reality of the causal processes. Finally, section 6 will apply the preceding considerations to simultaneous causation. On the one hand, in a basic sense, there can be no simultaneous causal relations. On the other hand, simultaneous causation arises when we consider the natural change by abstracting from the agent and from her/his projects of interven.. (shrink)

It is consistent with the evidence in The Origin of Concepts to conjecture that infants' causal representations, like their numerical representations, are not continuous with adults', so that bootstrapping is needed in both cases.

Kevin Laland and colleagues have put forward a number of arguments motivating an extended evolutionary synthesis. Here I examine Laland et al.'s central concept of reciprocal causation. Reciprocal causation features in many arguments supporting an expanded evolutionary framework, yet few of these arguments are clearly delineated. Here I clarify the concept and make explicit three arguments in which it features. I identify where skeptics can—and are—pushing back against these arguments, and highlight what I see as the empirical, explanatory, and methodological (...) issues at stake. (shrink)

Cultural disparity—the variation across cultural traits such as knowledge, skill, and belief—is a complex phenomenon, studied by a number of researchers with an expanding empirical toolkit. While there is a growing consensus as to the processes that generate cultural variation and change, general explanatory frameworks require additional tools for identifying, organising, and relating the complex causes that underpin the production of cultural disparity. Here I develop a case study in the cognitive science of religion, and demonstrate how concepts and distinctions (...) drawn from work on contrastive explanation and manipulationist accounts of causation provide such tools for distinguishing explanatory levels, organising causal narratives, and accounting for cross-cultural patterns. (shrink)