The emphasis on models hasn’t completely eliminated laws from scientific discourse and philosophical discussion. Instead, I want to argue that much of physics lies beyond the strict domain of laws. I shall argue that in important cases the physics, or physical understanding, does not lie either in laws or in their properties, such as universality, consistency and symmetry. I shall argue that the domain of application commonly attributed to laws is too narrow. That is, laws can still play an important, (...) though peculiar, role outside their strict domain of validity. I shall argue also that, by way of a trade-off, while the actual domain of application of laws should be seen as much broader. At the same time, what I call ‘anomic’ representational elements reveal themselves as central to the descriptive and explanatory power of theories and model: boundary conditions, state descriptions, structures, constraints, limits and mechanisms. I conclude with a brief consideration of how my discussion has consequences for discussion of understanding, unification, approximation and dispositional properties. I focus on examples from physics, macroscopic and microscopic, phenomenological and fundametal: shock waves, propagation of cracks, symmetry breaking, and others. This law-eccentric kind of knowledge is central to both modeling the world and intervening in it. (shrink)

Abstract‘Possibilist Explanation’ is a promising account of scientific explanation which avoids the familiar problems of “how-possibly explanations”. It explains an event by showing how-actually it was epistemically possible, instead of why it was epistemically necessary. Its explanandum is the epistemic possibility of an actual event previously considered epistemically impossible. To define PE, two new concepts are introduced: ‘permissive condition’ and ‘possibilist law’. A permissive condition for an event is something that does not entail the event itself, but a necessary condition (...) for it. A ‘Possibilist Law’ is a kind of scientific law that predicts that in the absence of a necessary condition N, the event E is not possible. Both PE and PL are legitimate and neglected parts of scientific knowledge and are especially suitable for human sciences. (shrink)

This article agrees with Philip Kitcher that we should aim for a well-ordered science, one that answers the right questions in the right ways. Crucial to this is to address questions of use: Which scientific account is right for which system in which circumstances? This is a difficult question: evidence that may support a scientific claim in one context may not support it in another. Drawing on examples in physics and other sciences, this article argues that work on the warrant (...) of theories in philosophy of science needs to change. Emphasis should move from the warrant of theories in the abstract to questions of evidence for use. (shrink)

Randomized controlled trials (RCTs) are widely taken as the gold standard for establishing causal conclusions. Ideally conducted they ensure that the treatment ‘causes’ the outcome—in the experiment. But where else? This is the venerable question of external validity. I point out that the question comes in two importantly different forms: Is the specific causal conclusion warranted by the experiment true in a target situation? What will be the result of implementing the treatment there? This paper explains how the probabilistic theory (...) of causality implies that RCTs can establish causal conclusions and thereby provides an account of what exactly that causal conclusion is. Clarifying the exact form of the conclusion shows just what is necessary for it to hold in a new setting and also how much more is needed to see what the actual outcome would be there were the treatment implemented. (shrink)

What kinds of evidence reliably support predictions of effectiveness for health and social care interventions? There is increasing reliance, not only for health care policy and practice but also for more general social and economic policy deliberation, on evidence that comes from studies whose basic logic is that of JS Mill's method of difference. These include randomized controlled trials, case–control studies, cohort studies, and some uses of causal Bayes nets and counterfactual-licensing models like ones commonly developed in econometrics. The topic (...) of this paper is the 'external validity' of causal conclusions from these kinds of studies. We shall argue two claims. Claim, negative: external validity is the wrong idea; claim, positive: 'capacities' are almost always the right idea, if there is a right idea to be had. If we are right about these claims, it makes big problems for policy decisions. Many advice guides for grading policy predictions give top grades to a proposed policy if it has two good Mill's-method-of difference studies that support it. But if capacities are to serve as the conduit for support from a method-of-difference study to an effectiveness prediction, much more evidence, and much different in kind, is required. We will illustrate the complexities involved with the case of multisystemic therapy, an internationally adopted intervention to try to diminish antisocial behaviour in young people. (shrink)

Mechanisms are now taken widely in philosophy of science to provide one of modern science’s basic explanatory devices. This has raised lively debate concerning the relationship between mechanisms, laws and explanation. This paper focuses on cases where a mechanism gives rise to a ceteris paribus law, addressing two inter-related questions: What kind of explanation is involved? and What is going on in the world when mechanism M affords behavior B described in a ceteris paribus law? We explore various answers offered (...) by ‘new mechanists’ and others before setting out and explaining our own answers: mechanistic explanations are a species of oldfashioned covering-law explanation and this often accounts in part for their explanatory power; and B is what it takes for some set of principles that govern the features of M’s parts in their arrangement in M all to be instanced together. (shrink)

This paper argues that even when simple analogue models picture parallel worlds, they generally still serve as isolating tools. But there are serious obstacles that often stop them isolating in just the right way. These are obstacles that face any model that functions as a thought-experiment but they are especially pressing for economic models because of the paucity of economic principles. Because of the paucity of basic principles, economic models are rich in structural assumptions. Without these no interesting conclusions can (...) be drawn. This, however, makes trouble when it comes to exporting conclusions from the model to the world. One uncontroversial constraint on induction from special cases is to beware of extending conclusions to situations that we know are different in relevant respects. In the case of economic models it is clear by inspection that the unrealistic structural assumptions of the model are intensely relevant to the conclusion. Any inductive leap to a real situation seems a bad bet. (shrink)

Opponents of ceteris paribus laws are apt to complain that the laws are vague and untestable. Indeed, claims to this effect are made by Earman, Roberts and Smith in this volume. I argue that these kinds of claims rely on too narrow a view about what kinds of concepts we can and do regularly use in successful sciences and on too optimistic a view about the extent of application of even our most successful non-ceteris paribus laws. When it comes to (...) testing, we test ceteris paribus laws in exactly the same way that we test laws without the ceteris paribus antecedent. But at least when the ceteris paribus antecedent is there we have an explicit acknowledgment of important procedures we must take in the design of the experiments — i.e., procedures to control for “all interferences” even those we cannot identify under the concepts of any known theory. (shrink)

Causation is in trouble—at least as it is pictured in current theories in philosophy and in economics as well, where causation is also once again in fashion. In both disciplines the accounts of causality on offer are either modelled too closely on one or another favoured method for hunting causes or on assumptions about the uses to which causal knowledge can be put—generally for predicting the results of our efforts to change the world. The first kind of account supplies no (...) reason to think that causal knowledge, as it is pictured, is of any use; the second supplies no reason to think our best methods will be reliable for establishing causal knowledge. So, if these accounts are all there is to be had, how do we get from method to use? Of what use is knowledge of causal laws that we work so hard to obtain? (shrink)

Causation is in trouble—at least as it is pictured in current theories in philosophy and in economics as well, where causation is also once again in fashion. In both disciplines the accounts of causality on offer are either modelled too closely on one or another favoured method for hunting causes or on assumptions about the uses to which causal knowledge can be put—generally for predicting the results of our efforts to change the world. The first kind of account supplies no (...) reason to think that causal knowledge, as it is pictured, is of any use; the second supplies no reason to think our best methods will be reliable for establishing causal knowledge. So, if these accounts are all there is to be had, how do we get from method to use? Of what use is knowledge of causal laws that we work so hard to obtain? (shrink)

In their rich and intricate paper ‘Independence, Invariance, and the Causal Markov Condition’, Daniel Hausman and James Woodward ([1999]) put forward two independent theses, which they label ‘level invariance’ and ‘manipulability’, and they claim that, given a specific set of assumptions, manipulability implies the causal Markov condition. These claims are interesting and important, and this paper is devoted to commenting on them. With respect to level invariance, I argue that Hausman and Woodward's discussion is confusing because, as I point out, (...) they use different senses of ‘intervention’ and ‘invariance’ without saying so. I shall remark on these various uses and point out that the thesis is true in at least two versions. The second thesis, however, is not true. I argue that in their formulation, the manipulability thesis is patently false and that a modified version does not fare better. Furthermore, I think their proof that manipulability implies the causal Markov condition is not conclusive. In the deterministic case it is valid but vacuous, whereas it is invalid in the probabilistic case. 1 Introduction 2 Intervention, invariance and modularity 3 The causal Markov condition: CM1 and CM2 4 From MOD to the causal Markov condition and back 5 A second argument for CM2 6 The proof of the causal Markov condition for probabilistic causes 7 ‘Cartwright's objection’ defended 8 Metaphysical defenses of the causal Markov condition 9 Conclusion. (shrink)

Que papel exercem os modelos nas investigações científicas? Que características deve ter um modelo para que seja designado como científico? Como operam os modelos nas ciências humanas e qual seu impacto nas ações humanas? Esses são alguns dos questionamentos que dão ensejo às discussões propostas por Luiz Henrique de Araújo Dutra em sua obra Pragmática de modelos, cuja terceira edição, revista e ampliada, fora recentemente lançada pela Editora Agrya.

Jeffrey Friedman has attempted to make a case for limiting state social engineering that is based on the skeptical epistemology of Sir Karl Popper. But Popper's epistemology is flawed, both in its rejection of a priori theorizing and its insistence on empirical falsification rather than confirmation. Classical liberalism of the sort that Friedman advocates requires, as its basis, positive knowledge of economics and social reality—not Popperian skepticism.

Paul Roth claims that “interpretivists” in the philosophy of social sciences like Charles Taylor assume a positivist caricature of natural science to motivate their arguments against naturalism in the social sciences. Roth argues that not only is adopting the view of meaning relied upon by those he sometimes refers to as the “friends of understanding” unmotivated once the critique of positivism has been taken on board, he argues further that Quine has shown why this “meaning realism” is unavailable in principle. (...) Roth bolsters his use of Quine against interpretivists by referring to Kripke’s reading of Wittgenstein on rule-following. But McDowell has shown how Kripke overlooks an alternative reading of those remarks, which provides “interpretivists” with arguments against mainstream naturalism and which makes no use of anything resembling “meaning realism.” This opening for interpretivists is actually already present in Roth’s discussion of the distinction between “thin” and “thick” description. This suggests how mainstream naturalism itself might be rethought to accommodate interpretivism. (shrink)

In this paper I criticize a view of functional localization in neuroscience, which I call “computational absolutism”. “Absolutism” in general is the view that each part of the brain should be given a single, univocal function ascription. Traditional varieties of absolutism posit that each part of the brain processes a particular type of information and/or performs a specific task. These function attributions are currently beset by physiological evidence which seems to suggest that brain areas are multifunctional—that they process distinct information (...) and perform different tasks depending on context. Many theorists take this contextual variation as inimical to successful localization, and claim that we can avoid it by changing our functional descriptions to computational descriptions. The idea is that we can have highly generalizable and predictive functional theories if we can discover a single computation performed by each area regardless of the specific context in which it operates. I argue, drawing on computational models of perceptual area MT, that this computational version of absolutism fails to come through on its promises. In MT, the modeling field has not produced a univocal computational description, but instead a plurality of models analyzing different aspects of MT function. Moreover, CA cannot appeal to theoretical unification to solve this problem, since highly general models, on their own, neither explain nor predict what MT does in any particular context. I close by offering a perspective on neural modeling inspired by Nancy Cartwright’s and Margaret Morrison’s views of modeling in the physical sciences. (shrink)

This paper's purpose is to set forth the conditions of explanation in the domain of formal modelling of social action. Explanation is defined as an adequate account of the underlying factors bringing about a phenomenon. The modelling of a social phenomenon can claim explanatory value in this sense if the following two conditions are fulfilled. (1) The generative mechanisms involved translate the effects of real factors abstracted from their phenomenal context, not those of purely ideal ones. (2) The explanatory hypotheses, (...) which account for the effects of explanatory factors, and the purely descriptive hypotheses, which introduce conceptual simplifications and summarise complex secondary mechanisms, are relatively independent from each other with regard to the phenomenon represented. This condition subjects the model to testing by alternatives through the development of purely descriptive hypotheses in the sense of explanatory or analytical realism. (shrink)

This paper addresses the political constraints on science through a pragmatist critique of Philip Kitcher’s account of “well-ordered science.” A central part of Kitcher’s account is his analysis of the significance of items of scientific research: contextual and purpose-relative scientific significance replaces mere truth as the aim of inquiry. I raise problems for Kitcher’s account and argue for an alternative, drawing on Peirce’s and Dewey’s theories of problem-solving inquiry. I conclude by suggesting some consequences for understanding the proper conduct of (...) science in a democracy. (shrink)

Niels Bohr’s model of the hydrogen atom is widely cited as an example of an inconsistent scientific theory because of its reliance on classical electrodynamics together with assumptions about interactions between matter and electromagnetic radiation that could not be reconciled with CED. This view of Bohr’s model is controversial, but we believe a recently proposed approach to reasoning with inconsistent commitments offers a promising formal reading of how Bohr’s model worked. In this paper we present this new way of reasoning (...) with inconsistent commitments and compare it with other approaches before applying it to Bohr’s model and offering some suggestions for how it might be extended to account for subsequent developments in old quantum theory. (shrink)

We show that five important elements of the ‘nomological package’— laws, counterfactuals, chances, dispositions, and counterfactuals—needn’t be a problem for the Growing-Block view. We begin with the framework given in Briggs and Forbes (in The real truth about the unreal future. Oxford studies in metaphysics. Oxford University Press, Oxford, 2012 ), and, taking laws as primitive, we show that the Growing-Block view has the resources to provide an account of possibility, and a natural semantics for non-backtracking causal counterfactuals. We show (...) how objective chances might ground a more fine-grained concept of feasibility, and furnished a places in the structure where causation and dispositions might fit. The Growing-Block view, thus understood, provides the resources to explain the close link between modality and tense, so that it predicts modal change as time passes. This account lets us capture not only what the future might hold for us, and also what might have been. (shrink)

Taking Bogen and Woodward's discussion of data and phenomena as his starting point, McAllister presents a challenge to scientific realism. I discuss this challenge and offer a suggestion for how the scientific realist could respond to both its epistemic and ontological aspects. In so doing, I urge that the scientific realist should not reject ontological pluralism from the start, but should seek to explore versions of scientific realism that leave open the possibility of certain kinds of pluralist ontology. I investigate (...) the available options and use a law-constitutive approach to offer a strategy for the scientific realist who is open-minded about ontological pluralism. (shrink)

The kinds of models discussed in this paper function as measuring instruments. We will concentrate on two necessary steps for measurement: (1) the search of a mathematical representation of the phenomenon; (2) this representation should cover an invariant relationship between the properties of the phenomenon to be measured and observable accociated attributes of a measuring instrument. Therefore, the measuring instrument should function as a nomological machine. However, invariant relationships are not necessarily ceteris paribus regularities, but could also occur when the (...) influence of the environment is negligible. Then we are able to achieve accurate measurements outside the laboratory. (shrink)

Este ensayo busca mostrar que la ciencia macroeconómica desde hace mucho tiempo no es una disciplina cuyas investigaciones están encuadradas dentro del denominado empirismo lógico y tampoco sus controversias se dirimen dentro del algúnparadigma al estilo de Thomas Kuhn, sino que está conformada por un conjunto de propuestas teóricas que conforman lo que Laudan denomina como “tradiciones de investigación”. Aunque los fenómenos que estudia la macroeconomía son externos a la consciencia del investigador, del diseñador de política económica y del público (...) en general, sus realizaciones tienden más hacia las propuestas de un realismo perspectivistade corte naturalista y que sus hallazgos expresan verdades acerca de las “tendencias” y “capacidades” que subyacen en los fenómenos económicos.This essay tries to show that macroeconomic science from a long time rather to make economic research taking account neo positivist principles and point of view is a discipline with different perspectives and theories within “research traditions” as Larry Laudan said. Although, whether the macroeconomic phenomena is outside of researchers, public policy makers, and people in general, the understanding of macroeconomic as a science trends to be a form of perspective realism with a methodological commitment to naturalism, using models as primary representational entities of economic problems, and where truth are about its trends and capacities as suggested Ronald GiereandNancy Cartwright. (shrink)

– The paper defends a naturalistic version of modal actualism according to which what is metaphysically possible is determined by dispositions found in the actual world. We argue that there is just one world—this one—and that all genuine possibilities are anchored by the dispositions exemplified in this world. This is the case regardless of whether or not those dispositions are manifested. As long as the possibility is one that would obtain were the relevant disposition manifested, it is a genuine possibility. (...) Furthermore, by starting from actual dispositional properties and branching out, we are able to include possibilities that are quite far removed from any state of affairs that happens to obtain, while still providing a natural and actual grounding of possibility. Stressing the importance of ontological considerations in any theory of possibility, it is argued that the account of possibility in terms of dispositional properties provides a more palatable ontology than those of its competitors. Coming at it from the other direction, the dispositional account of possibility also provides motivation for taking an ontology of dispositions more seriously. As well as the relevant dispositional notions required to lay out the view, the paper discusses the dispositional realism needed as the basis for the account of possibility. (shrink)

This article outlines a philosophy of science in practice that focuses on the engineering sciences. A methodological issue is that these practices seem to be divided by two different styles of scientific reasoning, namely, causal-mechanistic and mathematical reasoning. These styles are philosophically characterized by what Kuhn called ?disciplinary matrices?. Due to distinct metaphysical background pictures and/or distinct ideas of what counts as intelligible, they entail distinct ideas of the character of phenomena and what counts as a scientific explanation. It is (...) argued that the two styles cannot be reduced to each other. At the same time, although they are incompatible, they must not be regarded as competing. Instead, they produce different kinds of epistemic results, which serve different kinds of epistemic functions. Moreover, some scientific breakthroughs essentially result from relating them. This view of complementary styles of scientific reasoning is supported by pluralism about metaphysical background pictures. (shrink)

Functional robustness refers to a system’s ability to maintain a function in the face of perturbations to the causal structures that support performance of that function. Modularity, a crucial element of standard methods of causal inference and difference-making accounts of causation, refers to the independent manipulability of causal relationships within a system. Functional robustness appears to be at odds with modularity. If a function is maintained despite manipulation of some causal structure that supports that function, then the relationship between that (...) structure and function fails to be manipulable independent of other causal relationships within the system. Contrary to this line of reasoning, I argue that functional robustness often attends feedback control, rather than failures of modularity. Feedback control poses its own challenges to causal explanation and inference, but those challenges do not undermine modularity—and indeed, modularity is crucial to grappling with them. (shrink)

In science policy, it is generally acknowledged that science-based problem-solving requires interdisciplinary research. For example, policy makers invest in funding programs such as Horizon 2020 that aim to stimulate interdisciplinary research. Yet the epistemological processes that lead to effective interdisciplinary research are poorly understood. This article aims at an epistemology for interdisciplinary research, in particular, IDR for solving ‘real-world’ problems. Focus is on the question why researchers experience cognitive and epistemic difficulties in conducting IDR. Based on a study of educational (...) literature it is concluded that higher-education is missing clear ideas on the epistemology of IDR, and as a consequence, on how to teach it. It is conjectured that the lack of philosophical interest in the epistemology of IDR is due to a philosophical paradigm of science, which prevents recognizing severe epistemological challenges of IDR, both in the philosophy of science as well as in science education and research. The proposed alternative philosophical paradigm entails alternative philosophical presuppositions regarding aspects such as the aim of science, the character of knowledge, the epistemic and pragmatic criteria for accepting knowledge, and the role of technological instruments. This alternative philosophical paradigm assume the production of knowledge for epistemic functions as the aim of science, and interprets ‘knowledge’ as epistemic tools that must allow for conducting epistemic tasks by epistemic agents, rather than interpreting knowledge as representations that objectively represent aspects of the world independent of the way in which it was constructed. The engineering paradigm of science involves that knowledge is indelibly shaped by how it is constructed. Additionally, the way in which scientific disciplines construct knowledge is guided by the specificities of the discipline, which can be analyzed in terms of disciplinary perspectives. This implies that knowledge and the epistemic uses of knowledge cannot be understood without at least some understanding of how the knowledge is constructed. Accordingly, scientific researchers need so-called metacognitive scaffolds to assist in analyzing and reconstructing how ‘knowledge’ is constructed and how different disciplines do this differently. In an engineering paradigm of science, these metacognitive scaffolds can also be interpreted as epistemic tools, but in this case as tools that guide, enable and constrain analyzing and articulating how knowledge is produced. In interdisciplinary research, metacognitive scaffolds assist interdisciplinary communication aiming to analyze and articulate how the discipline constructs knowledge. (shrink)

The complex societal challenges of the twenty-first Century require scientific researchers and academically educated professionals capable of conducting scientific research in complex problem contexts. Our central claim is that educational approaches inspired by a traditional empiricist epistemology insufficiently foster the required deep conceptual understanding and higher-order thinking skills necessary for epistemic tasks in scientific research. Conversely, we argue that constructivist epistemologies provide better guidance to educational approaches to promote research skills. We also argue that teachers adopting a constructivist learning theory (...) do not necessarily embrace a constructivist epistemology. On the contrary, in educational practice, novel educational approaches that adopt constructivist learning theories often maintain traditional empiricist epistemologies. Philosophers of science can help develop educational designs focused on learning to conduct scientific research, combining constructivist learning theory with constructivist epistemology. We illustrate this by an example from a bachelor’s program in Biomedical Engineering, where we introduce conceptual models and modeling as an alternative to the traditional focus on hypothesis testing in conducting scientific research. This educational approach includes the so-called B&K method for constructing scientific models to scaffold teaching and learning conceptual modeling. (shrink)

Scientific research is reconstructed as a language game along the lines of Robert Brandom's inferentialism. Researchers are assumed to aim at persuading their colleagues of the validity of some claims. The assertions each scientist is allowed or committed to make depend on her previous claims and on the inferential norms of her research community. A classification of the most relevant types of inferential rules governing such a game is offered, and some ways in which this inferentialist approach can be used (...) for assessing scientific knowledge and practices are explored. Some similarities and differences with a game-theoretic analysis are discussed. (shrink)

In our paper we propose a philosophicalanalysis, based on the notion ofphenomenological model, of Nuclear Physics. Inthis way, we will show some peculiarities ofthis branch of physics.

How is scientific knowledge used, adapted, and extended in deriving phenomena and real-world systems? This paper aims at developing a general account of 'applying science' within the exemplar-based framework of Data-Oriented Processing (DOP), which is also known as Exemplar-Based Explanation (EBE). According to the exemplar-based paradigm, phenomena are explained not by deriving them all the way down from theoretical laws and boundary conditions but by modelling them on previously derived phenomena that function as exemplars. To accomplish this, DOP proposes to (...) maintain a corpus of derivation trees of previous phenomena together with a matching algorithm that combines subtrees from the corpus to derive new phenomena. By using a notion of derivational similarity, a new phenomenon can be modelled as closely as possible on previously explained phenomena. I will propose an instantiation of DOP which integrates theoretical and phenomenological modelling and which generalises over various disciplines, from fluid mechanics to language technology. I argue that DOP provides a solution for what I call Kuhn's problem and that it redresses Kitcher's account of explanation. (shrink)

Unlike basic sciences, scientific research in advanced technologies aims to explain, predict, and describe not phenomena in nature, but phenomena in technological artefacts, thereby producing knowledge that is utilized in technological design. This article first explains why the covering‐law view of applying science is inadequate for characterizing this research practice. Instead, the covering‐law approach and causal explanation are integrated in this practice. Ludwig Prandtl’s approach to concrete fluid flows is used as an example of scientific research in the engineering sciences. (...) A methodology of distinguishing between regions in space and/or phases in time that show distinct physical behaviours is specific to this research practice. Accordingly, two types of models specific to the engineering sciences are introduced. The diagrammatic model represents the causal explanation of physical behaviour in distinct spatial regions or time phases; the nomo‐mathematical model represents the phenomenon in terms of a set of mathematically formulated laws. (shrink)

This paper deals with the problem of derivational redundancy in scientific explanation, i.e. the problem that there can be extremely many different explanatory derivations for a natural phenomenon while students and experts mostly come up with one and the same derivation for a phenomenon (modulo the order of applying laws). Given this agreement among humans, we need to have a story of how to select from the space of possible derivations of a phenomenon the derivation that humans come up with. (...) In this paper we argue that the problem of derivational redundancy can be solved by a new notion of “shortest derivation”, by which we mean the derivation that can be constructed by the fewest (and therefore largest) partial derivations of previously derived phenomena that function as “exemplars”. We show how the exemplar-based framework known as “Data-Oriented Parsing” or “DOP” can be employed to select the shortest derivation in scientific explanation. DOP’s shortest derivation of a phenomenon maximizes what is called the “derivational similarity” between a phenomenon and a corpus of exemplars. A preliminary investigation with exemplars from classical and fluid mechanics shows that the shortest derivation closely corresponds to the derivations that humans construct. Our approach also proposes a concrete solution to Kuhn’s problem of how we know on which exemplar a phenomenon can be modeled. We argue that humans model a phenomenon on the exemplar that is derivationally most similar to the phenomenon, i.e. the exemplar from which the largest subtree(s) can be used to derive the phenomenon. (shrink)

Despite the currently perceived urgent need among contemporary philosophers of chemistry for adjudicating between two rival metaphysical conceptual frameworks—is chemistry primarily a science of substances or processes?—this essay argues that neither provides us with what we need in our attempts to explain and comprehend chemical operations and phenomena. First, I show the concept of a chemical property can survive the abandoning of the metaphysical framework of substance. While this abandonment means that we will need to give up essential properties, contingent (...) properties can give us all the stability we need to account for chemical continuity as well as change. I then go on to show that this attention to clusters of contingent properties does not force us into the arms of an alternative process metaphysical framework either. Finally, I sketch a view I call particularism with respect to chemical properties on analogy with moral particularism. I conclude by sketching some of the implications for the field of philosophy of chemistry of my proposal that we abandon our interest in the metaphysical question of what chemistry is primarily about in favor of a broadly scientific particularism with respect to kinds and properties. (shrink)

As climate policy decisions are decisions under uncertainty, being based on a range of future climate change scenarios, it becomes a crucial question how to set up this scenario range. Failing to comply with the precautionary principle, the scenario methodology widely used in the Third Assessment Report of the International Panel on Climate Change (IPCC) seems to violate international environmental law, in particular a provision of the United Nations Framework Convention on Climate Change. To place climate policy advice on a (...) sound methodological basis would imply that climate simulations which are based on complex climate models had, in stark contrast to their current hegemony, hardly an epistemic role to play in climate scenario analysis at all. Their main function might actually consist in ‘foreseeing future ozone-holes’. In order to argue for these theses, I explain first of all the plurality of climate models used in climate science by the failure to avoid the problem of underdetermination. As a consequence, climate simulation results have to be interpreted as modal sentences, stating what is possibly true of our climate system. This indicates that climate policy decisions are decisions under uncertainty. Two general methodological principles which may guide the construction of the scenario range are formulated and contrasted with each other: modal inductivism and modal falsificationism. I argue that modal inductivism, being the methodology implicitly underlying the third IPCC report, is severely flawed. Modal falsificationism, representing the sound alternative, would in turn require an overhaul of the IPCC practice. (shrink)

Functionalism about kinds is still the dominant style of thought in the special sciences, like economics, psychology, and biology. Generally construed, functionalism is the view that states or processes can be individuated based on what role they play rather than what they are constituted of or realized by. Recently, Weiskopf has posited a reformulation of functionalism on the model-based approach to explanation. We refer to this reformulation as ‘new functionalism’. In this paper, we seek to defend new functionalism and to (...) recast it in light of the concrete explanatory aims of the special sciences. In particular, we argue that the assessment of the explanatory legitimacy of a functional kind needs to take into account the explanatory purpose of the model in which the functional kind is employed. We aim at demonstrating this by appealing to model-based explanations from the social and behavioral sciences. Specifically, we focus on preferences and signals as functional kinds. Our argument is intended to have the double impact of deflecting criticisms against new functionalism from the perspective of mechanistic decomposition while also expanding the scope of new functionalism to encompass the social and behavioral sciences. (shrink)

Unless one embraces activities as foundational, understanding activities in mechanisms requires an account of the means by which entities in biological mechanisms engage in their activities—an account that does not merely explain activities in terms of more basic entities and activities. Recent biological research on molecular motors exemplifies such an account, one that explains activities in terms of free energy and constraints. After describing the characteristic “stepping” activities of these molecules and mapping the stages of those steps onto the stages (...) of the motors’ hydrolytic cycles, researchers pieced together from images of the molecules in different hydrolyzation states accounts of how the chemical energy in ATP is transformed in the constrained environments of the motors into the characteristic activities of the motors. We argue that New Mechanism’s standard set of analytic categories—entities, activities, and organization—should be expanded to include constraints and energetics. Not only is such an expansion required descriptively to capture research on molecular motors but, more importantly from a philosophical point of view, it enables a non-regressive account of activities in mechanisms. In other words, this expansion enables a philosophical account of mechanistic explanation that avoids a regress of entities and activities “all the way down.” Rather, mechanistic explanation bottoms out in constraints and energetics. (shrink)

The essential precondition of implementing interventionist techniques of causal reasoning is that particular variables are identified as so-called intervention variables. While the pertinent literature standardly brackets the question how this can be accomplished in concrete contexts of causal discovery, the first part of this paper shows that the interventionist nature of variables cannot, in principle, be established based only on an interventionist notion of causation. The second part then demonstrates that standard observational methods that draw on Bayesian networks identify intervention (...) variables only if they also answer the questions that can be answered by interventionist techniques—which are thus rendered dispensable. The paper concludes by suggesting a way of identifying intervention variables that allows for exploiting the whole inferential potential of interventionist techniques. (shrink)

In this article we develop a pragmatist-inspired notion of intelligence that should lead to a better understanding of the notion of scientific expertise. The notion of intelligence is drawn from Dewey and is therefore used here in its technical sense. Our thesis is that scientific knowledge is a necessary but not sufficient condition for scientific expertise; intelligence should also be added. Conceived of as the capacity to apply general knowledge to particulars, we reach the conclusion that intelligence is a necessary (...) requirement for scientific experts in the wake of Dewey’s logic of inquiry. In particular, we argue that an all-important task that scientific experts are asked to accomplish, and which puts their expertise to the test, is to transform indeterminate situations into problematic situations, and that such a goal can only be achieved if scientific experts succeed in paying attention to all the contingent and precarious aspects that make the situation they face unique. (shrink)

There is good reason to suppose that our best physical theories, quantum mechanics and special relativity, are false if taken together and literally. If they are in fact false, then how should they count as providing knowledge of the physical world? One might imagine that, while strictly false, our best physical theories are nevertheless in some sense probably approximately true. This paper presents a notion of local probable approximate truth in terms of descriptive nesting relations between current and subsequent theories. (...) This notion helps explain how false physical theories might nevertheless provide physical knowledge of a variety that is particularly salient to diachronic empirical inquiry. (shrink)

This article argues for a different outlook on the concept of extension, especially for the reference of general terms in scientific practice. Scientific realist interpretations of the two predominant theories of meaning, namely Descriptivism and Causal Theory, contend that a stable cluster of descriptions or an initial baptism fixes the extension of a general term such as a natural kind term. This view in which the meaning of general terms is presented as monosemantic and the referents as stable, homogeneous, and (...) unchangeable, however, does not reflect the various practices involved in the investigation of research materials and the related application of general terms in scientific practice. By drawing on the taxonomic diversity, particularly of structure-based classifications in chemical databases, this article illustrates the limited utility of such a concept of extension. Research materials often exhibit a plurality of material dimensions that, within different research contexts, allow for various and often equally significant taxonomic demarcations. In light of this, the extension of a general term cannot be uniquely determined by a supposedly independent nature of the referent but is relative to the model context under which the materials are investigated. This significance and plurality of the model context, I claim, needs to be mirrored in an account of meaning that is supposed to reflect scientific reality. On this account, the aim of this article is to present an alternative perspective on the concept of extension to accommodate the diverse material practices that determine the application of general terms in science. (shrink)

There are three distinct questions associated with Simpson's paradox, (i) Why or in what sense is Simpson's paradox a paradox? (ii) What is the proper analysis of the paradox? (iii) How one should proceed when confronted with a typical case of the paradox? We propose a "formar" answer to the first two questions which, among other things, includes deductive proofs for important theorems regarding Simpson's paradox. Our account contrasts sharply with Pearl's causal (and questionable) account of the first two questions. (...) We argue that the "how to proceed question?" does not have a unique response, and that it depends on the context of the problem. We evaluate an objection to our account by comparing ours with Blyth's account of the paradox. Our research on the paradox suggests that the "how to proceed question" needs to be divorced from what makes Simpson's paradox "paradoxical.". (shrink)

There are three distinct questions associated with Simpson’s paradox. Why or in what sense is Simpson’s paradox a paradox? What is the proper analysis of the paradox? How one should proceed when confronted with a typical case of the paradox? We propose a “formal” answer to the first two questions which, among other things, includes deductive proofs for important theorems regarding Simpson’s paradox. Our account contrasts sharply with Pearl’s causal account of the first two questions. We argue that the “how (...) to proceed question?” does not have a unique response, and that it depends on the context of the problem. We evaluate an objection to our account by comparing ours with Blyth’s account of the paradox. Our research on the paradox suggests that the “how to proceed question” needs to be divorced from what makes Simpson’s paradox “paradoxical.”. (shrink)

Soon after the 2008 financial crisis, Gillian Tett, an anthropologist and the US Managing Editor of the Financial Times, suggested that regulators’ and practitioners’ inability to anticipate and respond to deep problems in the financial industry could be traced back to what she called “silo thinking,” wherein experts in one area know nothing about the methods and research of other areas. As she put it, “the essential challenges for investors today…”—and, we might add, for regulators and academics—is “to understand the (...) micro-details of the silos, and see how all the macro-pieces add up”.In years since, many researchers in many fields have sought to identify causes of the... (shrink)

This article attacks “open systems” arguments that because constant conjunctions are not generally observed in the real world of open systems we should be highly skeptical that universal laws exist. This work differs from other critiques of open system arguments against laws of nature by not focusing on laws themselves, but rather on the inference from open systems. We argue that open system arguments fail for two related reasons; 1) because they cannot account for the “systems” central to their argument (...) (nor the implied systems labeled “exogenous factors” in relation to the system of interest) and 2) they are nomocentric, fixated on laws while ignoring initial and antecedent conditions that are able to account for systems and exogenous factors within a fundamentalist framework. (shrink)

Biological and cognitive sciences rely heavily on the idea of information transmitted between natural events or processes. This paper critically assesses some current philosophical views of natural information and defends a view of natural information as Nomic and Factive. Dretske offered a Factive view of information, and recent work on the topic has tended to reject this aspect of his view in favor of a non-Factive, probabilistic approach. This paper argues that the reasoning behind this move to non-Factivity is flawed (...) and mixes up different problems with Dretske’s original view. I show that one of these problems—strictness—has to do with Nomicity rather than Factivity. The other problem—reference class ambiguity—is not solvable just in terms of a theory of natural information. On the Dretske-inspired view I defend, natural information is Factive and Nomic but is insufficient to determine the cognitive or biological content of a natural process. In sum I present an examination what natural information is and what role it can play in our understanding of living and thinking things. (shrink)

When Ron Giere introduced perspectivism into philosophy of science, he provided a perspectivist analysis of both scientific instruments and scientific theorizing. Today, there is a burgeoning literature that extends Giere’s analysis of theorizing, with many philosophers examining the perspectivist approach to aspects of theorizing such as models, laws, explanations, and so on. However, relatively little attention has been paid to Giere’s analysis of instruments. In this article, I hope to fill this gap. I argue that the perspectivist analysis of instruments (...) should be rejected. First, I give a general account of the kind of instrumentation relevant to instrumental perspectivism, drawing on Cartwright’s notion of nomological machines, which forms the basis of my criticism of Giere’s argument for instrumental perspectivism. Next, I present the case against instrumental perspectivism. I argue that instrumental perspectivism is dependent on theoretical perspectivism in a way that robs it of philosophical significance, and that it introduces new puzzles while adding little to our understanding of instruments. (shrink)

Scientific models represent aspects of the empirical world. I explore to what extent this representational relationship, given the specific properties of models, can be analysed in terms of propositions to which truth or falsity can be attributed. For example, models frequently entail false propositions despite the fact that they are intended to say something "truthful" about phenomena. I argue that the representational relationship is constituted by model users "agreeing" on the function of a model, on the fit with data and (...) on the aspects of a phenomenon that are modelled. Model users weigh the propositions entailed by a model and from this decide which of these propositions are crucial to the acceptance and continued use of the model. Thus, models represent phenomena when certain propositions they entail are true, but this alone does not exhaust the representational relationship. Therefore, the constraints that produce the choice of the relevant propositions in a model must also be examined and their analysis contributes to understanding the relationship between models and phenomena. (shrink)

: This paper contains the analysis of nine interviews with UK scientists on the topic of scientific models. Scientific models are an important, very controversially discussed topic in philosophy of science. A reasonable expectation is that philosophical conceptions of models ought to be in agreement with scientific practice. Questioning practicing scientists on their use of and views on models provides material against which philosophical positions can be measured.