In this article, I explore the compatibility of inference to the best explanation (IBE) with several influential models and accounts of scientific explanation. First, I explore the different conceptions of IBE and limit my discussion to two: the heuristic conception and the objective Bayesian conception. Next, I discuss five models of scientific explanation with regard to each model’s compatibility with IBE. I argue that Kitcher’s unificationist account supports IBE; Railton’s deductive–nomological–probabilistic model, Salmon’s statistical-relevance model, and van Fraassen’s (...) erotetic account are incompatible with IBE; and Salmon’s causal–mechanical model is merely consistent with IBE. In short, many influential models of scientific explanation do not support IBE. I end by outlining three possible conclusions to draw: (1) either philosophers of science or defenders of IBE have seriously misconstrued the concept of explanation, (2) philosophers of science and defenders of IBE do not use the term ‘explanation’ univocally, and (3) the ampliative conception of IBE, which is compatible with any model of scientific explanation, deserves a closer look. (shrink)

Ever since the advent of molecular biology in the 1970s, mechanical models have become the dogma in the field, where a "true" understanding of any subject is equated to a mechanistic description. This has been to the detriment of the biomedical sciences, where, barring some exceptions, notable new feats of understanding have arguably not been achieved in normal and disease biology, including neurodegenerative disease and cancer pathobiology. I argue for a "mechanism-plus-X" paradigm, where mainstay elements of mechanistic models (...) such as hierarchy and correlation are combined with nomological principles such as general operative rules and generative principles. Depending on the question at hand and the nature of the inquiry, X could range from proven physical laws to speculative biological generalizations, such as the notional principle of cellular synchrony. I argue that the "mechanism-plus-X" approach should ultimately aim to move biological inquiries out of the deadlock of oft-encountered mechanistic pitfalls and reposition biology to its former capacity of illuminating fundamental truths about the world. (shrink)

We address the need for a model by considering two competing theories regarding the origin of life: (i) the Metabolism First theory, and (ii) the RNA World theory. We discuss two interrelated points, namely: (i) Models are valuable tools for understanding both the processes and intricacies of origin-of-life issues, and (ii) Insights from models also help us to evaluate the core objection to origin-of-life theories, called “the inefficiency objection”, which is commonly raised by proponents of both the Metabolism (...) First theory and the RNA World theory against each other. We use Simpson’s Paradox (SP) as a tool for challenging this objection. We will use models in various senses, ranging from taking them as representations of reality to treating them as theories/accounts that provide heuristics for probing reality. In this paper, we will frequently use models and theories interchangeably. Additionally, we investigate Conway’s Game of Life and contrast it with our SP-based approach to emergence-of-life issues. Finally, we discuss some of the consequences of our view. A scientific model is testable in three senses: (i) a logical sense, (ii) a nomological sense, and (iii) a current technological sense. The SP-based model is testable in the first two senses but it is not feasible to test it using current technology. (shrink)

Using as case studies two early diagrams that represent mechanisms of the cell division cycle, we aim to extend prior philosophical analyses of the roles of diagrams in scientific reasoning, and specifically their role in biological reasoning. The diagrams we discuss are, in practice, integral and indispensible elements of reasoning from experimental data about the cell division cycle to mathematical models of the cycle’s molecular mechanisms. In accordance with prior analyses, the diagrams provide functional explanations of the cell cycle (...) and facilitate the construction of mathematical models of the cell cycle. But, extending beyond those analyses, we show how diagrams facilitate the construction of mathematical models, and we argue that the diagrams permit nomological explanations of the cell cycle. We further argue that what makes diagrams integral and indispensible for explanation and model construction is their nature as locality aids: they group together information that is to be used together in a way that sentential representations do not. (shrink)

Coherence and correspondence are classical contenders as theories of truth. In this paper we examine them instead as interacting factors in the dynamics of belief across epistemic networks. We construct an agent-based model of network contact in which agents are characterized not in terms of single beliefs but in terms of internal belief suites. Individuals update elements of their belief suites on input from other agents in order both to maximize internal belief coherence and to incorporate ‘trickled in’ elements of (...) truth as correspondence. Results, though often intuitive, prove more complex than in simpler models (Hegselmann & Krause 2002, 2006; Grim, Singer, Reade & Fisher 2015). The optimistic finding is that pressures toward internal coherence can exploit and expand on small elements of truth as correspondence is introduced into epistemic networks. Less optimistic results show that pressures for coherence can also work directly against the incorporation of truth, particularly when coherence is established first and new data is introduced later. (shrink)

In a recent article, Erasmus, Brunet, and Fisher (2021) argue that Artificial Neural Networks (ANNs) are explainable. They survey four influential accounts of explanation: the Deductive-Nomological model, the Inductive-Statistical model, the Causal-Mechanical model, and the New-Mechanist model. They argue that, on each of these accounts, the features that make something an explanation is invariant with regard to the complexity of the explanans and the explanandum. Therefore, they conclude, the complexity of ANNs (and other Machine Learning models) does not (...) make them less explainable. In this reply, it is argued that Erasmus et al. left out one influential account of explanation from their discussion: the Unificationist model. It is argued that, on the Unificationist model, the features that makes something an explanation is sensitive to complexity. Therefore, on the Unificationist model, ANNs (and other Machine Learning models) are not explainable. It is emphasized that Erasmus et al.’s general strategy is correct. The literature on explainable Artificial Intelligence can benefit by drawing from philosophical accounts of explanation. However, philosophical accounts of explanation do not settle the problem of whether ANNs are explainable because they do not unanimously declare that explanation is invariant with regard to complexity. (shrink)

Opinionated state of the art paper on scientific explanation. Analysis and discussion of the most relevant models and theories in the contemporary literature, namely, the deductive-nomological model, the models of inductive-statistical and statistical relevance, the pragmatic theory of why questions, the unifying theory of standard arguments, and the causal/non-causal counterfactual theory.

(1) In the first part of this paper, I review Chomsky's meandering journey from the formalism/mentalism of Syntactic Structures, through several methodological positions, to the minimalist theory of his latest work. Infected with mentalism from first to last, each and every position vitiates Chomsky's repeated claims that his theories will provide useful guidance to later theories in such fields as cognitive psychology and cognitive neuroscience. With the guidance of his insights, he claims, psychologists and neuroscientists will be able to avoid (...) costly dead-end lines of research. -/- (2) This never happened. As I have shown, this never could have happened. (See Johnston, 2018). What has happened, instead, is that current neurolinguistic research (with the arguable exception of the now-dated Lemma Model of Willem Levelt) proceeds without reference to Chomsky. It also wholeheartedly rejects the mentalism of the associated Language of Thought theory of Jerry Fodor. (See Johnston, 2018). -/- (3) I make this argument in the first part of this paper. I would also like to point out that most of my argument was developed in 1972, when I was a graduate student. I know of no other sustained criticisms of Chomsky at that time, and certainly none along the lines I had developed back then. -/- (4) In the second part of this paper, I present my own account of the methodology of science. When I was a graduate student, philosophy of science was dominated by an attempt to describe a methodology common to all the specific sciences, i.e. Hempel’s deductive-nomological model. These days, Hempel’s emphasis on the methodological unity of science has been rejected by such “dis-unity” philosophers of science as Ian Hacking, Patrick Suppes and Nancy Cartwright (see Cat, 2021). -/- (5) I view this change as the swing of a pendulum or, to change the metaphor, a journey from one end point of a continuum to another. As the level of abstraction at which one tries to describe scientific method is raised, the descriptions become increasingly general. Whether or not unity-of-science theories become so general as to be vacuous, is ultimately a subjective judgment. And so I expect that philosophers will eventually become tired of increasingly specific “close to the workbench” descriptions of how scientists work, and begin to turn back to methodological “big pictures”, finding in them powerful abstractions rather than empty irrelevancies. -/- (6) In the second part of this paper, I present my own account of the methodology of science, which I would situate somewhere between the “unity” and “dis-unity” accounts. However, I am not a scientist. My own views about scientific method have three origins: -/- (6a) my work as a graduate student from 1966 until I passed my comprehensive exams in 1973 (at a different university); -/- (6b) reading every issue of Scientific American from 1972 until nearly 2000, (at which point I continued to read it only sporadically, since I concluded that, around that time, it had evolved from a serious science magazine to a popular science magazine); and -/- (6c) my three-year immersion in the cognitive neuroscience of language after I retired, based on repeated study of and note-taking for (Banesh & Compton, 2018), (Kemmerer, 2015), several other books and, finally, numerous articles not hidden behind a paywall. -/- So, as always with my writings: caveat emptor. (shrink)

Call an explanation in which a non-mathematical fact is explained—in part or in whole—by mathematical facts: an extra-mathematical explanation. Such explanations have attracted a great deal of interest recently in arguments over mathematical realism. In this article, a theory of extra-mathematical explanation is developed. The theory is modelled on a deductive-nomological theory of scientific explanation. A basic DN account of extra-mathematical explanation is proposed and then redeveloped in the light of two difficulties that the basic theory faces. The final (...) view appeals to relevance logic and uses resources in information theory to understand the explanatory relationship between mathematical and physical facts. 1Introduction2Anchoring3The Basic Deductive-Mathematical Account4The Genuineness Problem5Irrelevance6Relevance and Information7Objections and Replies 7.1Against relevance logic7.2Too epistemic7.3Informational containment8Conclusion. (shrink)

In this paper I will introduce a problem for at least those Humeans who believe that the future is open. More particularly, I will argue that the following aspect of scientific practice cannot be explained by openfuture- Humeanism: There is a distinction between states that we cannot bring about (which are represented in scientific models as nomologically impossible) and states that we merely happen not to bring about. Open-future-Humeanism has no convincing account of this distinction. Therefore it fails to (...) explain why we cannot bring about certain states of affairs, it cannot explain what I call the “recalcitrance of nature”. (shrink)

Non-Humean accounts of the metaphysics of nature posit either laws or powers in order to account for natural necessity and world-order. We argue that such monistic views face fundamental problems. On the one hand, neo-Aristotelians cannot give unproblematic power-based accounts of the functional laws among quantities offered by physical theories, as well as of the place of conservation laws and symmetries in a lawless ontology; in order to capture these characteristics, commitment to governing laws is indispensable. On the other hand, (...) ontologies that entirely exclude some kind of power ascription to worldly entities face what we call the Governing Problem: such ontologies do not have the resources to give an adequate account of how laws play their governing role. We propose a novel dualist model, which, we argue, has the resources to solve the difficulties encountered by its two dominant competitors, without inheriting the problems of either view. According to the dualist model, both laws and powers are equally fundamental and irreducible to each other, and both are needed in order to give a satisfactory account of the nomological structure of the world. The dualist model constitutes thus a promising alternative to current monistic views in the metaphysics of science. (shrink)

The deductive nomological (DN) model has been the basis for discussions about scientific explanations for decades. The overcoming of the logical empiricist program together with the raise of several counter-examples to the DN model have progressively led to a renewal of the reflections on this topic. The first step of this paper is to clarify the framework in which the epistemological question of scientific explanation is adressed. We make a proposal for a universal structure of scientific models, which (...) constitute the basic epistemic unit of our analysis. It is then possible, within this framework, to clarify some discussions about scientific explanation, and to offer a new account of it. The latter tries to benefit from the advantages of the DN model, as resting on a law, together with neutralizing some of its typical criticisms. The work presented here is both abstract, exhibiting formal structures as general patterns of explanation, and concrete with real examples taken from actual scientific disciplines. (shrink)

A finer-grained delineation of a given explanandum reveals a nexus of closely related causal and non- causal explanations, complementing one another in ways that yield further explanatory traction on the phenomenon in question. By taking a narrower construal of what counts as a causal explanation, a new class of distinctively mathematical explanations pops into focus; Lange’s characterization of distinctively mathematical explanations can be extended to cover these. This new class of distinctively mathematical explanations is illustrated with the Lotka-Volterra equations. There (...) are at least two distinct ways those equations might hold of a system, one of which yields straightforwardly causal explanations, but the other of which yields explanations that are distinctively mathematical in terms of nomological strength. In the first, one first picks out a system or class of systems, finds that the equations hold in a causal -explanatory way; in the second, one starts with the equations and explanations that must apply to any system of which the equations hold, and only then turns to the world to see of what, if any, systems it does in fact hold. Using this new way in which a model might hold of a system, I highlight four specific avenues by which causal and non- causal explanations can complement one another. (shrink)

In a recent paper, Erasmus et al. (2021) defend the idea that the ambiguity of the term “explanation” in explainable AI (XAI) can be solved by adopting any of four different extant accounts of explanation in the philosophy of science: the Deductive Nomological, Inductive Statistical, Causal Mechanical, and New Mechanist models. In this chapter, I show that the authors’ claim that these accounts can be applied to deep neural networks as they would to any natural phenomenon is mistaken. (...) I also provide a more general argument as to why the notion of explainability as it is currently used in the XAI literature bears little resemblance to the traditional concept of scientific explanation. It would be more fruitful to use the label “understandable AI” to avoid the confusion that surrounds the goal and purposes of XAI. In the second half of the chapter, I argue for a pragmatic conception of understanding that is better suited to play the central role attributed to explanation in XAI. Following De Regt (2017) and Kuorikoski and Ylikoski (2015), the conditions of satisfaction for understanding an ML system are fleshed out in terms of an agent’s success in using the system. (shrink)

In this dissertation I achieve the following: (1) I present motivating criteria for a general comprehensive theory of scientific explanation. I review historical approaches to modeling explanation in light of these criteria. (2) I present New Mechanist Explanation ("NME") as the leading candidate for a contemporary, complete theory of scientific explanation. (3) I present constraints on the applicability of New Mechanism in modeling biology, chemistry, and physics. I argue for the unsuitability of NME as a candidate for a general theory (...) of explanation due to its significant omissions of explanatory content and subsequent incompleteness. (4) I present arguments for the indispensable explanatory power of mathematics in science, noting that much of NME's failures are owed to its poor integration of mathematical explanation as applied to science. (5) I propose a Rational-Relational theory of explanation(“RRE”). I present RRE in detail and demonstrate it as a true working general theory of explanation which best meets the motivating criteria presented in (1). I disambiguate RRE from structural explanation ("SE"). I show that historical models of explanation, including the deductive nomological (DNE) model, statistical relevance ("SRE") model, structural model (SE) and unification model ("UE") may be successfully treated as sub-classes of explanation within the scope of RRE. I provide a rubric for selecting amongst sub-theories of explanation under RRE in the purpose of highlighting particular features of relational explanations. (6) In conclusion, I argue that philosophers of science should move forward using RRE as a general model of scientific explanation as a working alternative to the incomplete model of NME. (shrink)

This paper models God and time in the framework of modern physics. God bridges and simultaneously exists in (1) a universe with infinite tenseless time and (2) a created parallel universe with tensed time and a point origin. The primary attributes of God are inexhaustible love, inexhaustible perception, and inexhaustible force. The model also incorporates modern physics theories that include relativity, the conservation of energy, quantum mechanics, and multiverse geometry. For example, creation out of nothing and divine intervention are (...) subject to physical processes and likewise nomological possibility. I will call this model semiclassical theism. (shrink)

An account of distinctively mathematical explanation (DME) should satisfy three desiderata: it should account for the modal import of some DMEs; it should distinguish uses of mathematics in explanation that are distinctively mathematical from those that are not (Baron [2016]); and it should also account for the directionality of DMEs (Craver and Povich [2017]). Baron’s (forthcoming) deductive-mathematical account, because it is modelled on the deductive-nomological account, is unlikely to satisfy these desiderata. I provide a counterfactual account of DME, the (...) Narrow Ontic Counterfactual Account (NOCA), that can satisfy all three desiderata. NOCA appeals to ontic considerations to account for explanatory asymmetry and ground the relevant counterfactuals. NOCA provides a unification of the causal and the non-causal, the ontic and the modal, by identifying a common core that all explanations share and in virtue of which they are explanatory. (shrink)

Deductionism assimilates nature to conceptual artifacts (models, equations), and tacitly holds that real physical systems are such artifacts. Some physical concepts represent properties of deductive systems rather than of nature. Properties of mathematical or deductive systems can thereby sometimes falsely be ascribed to natural systems.

The aim of this paper is to argue that the adoption of an unrestricted principle of bivalence is compatible with a metaphysics that (i) denies that the future is real, (ii) adopts nomological indeterminism, and (iii) exploits a branching structure to provide a semantics for future contingent claims. To this end, we elaborate what we call Flow Fragmentalism, a view inspired by Kit Fine (2005)’s non-standard tense realism, according to which reality is divided up into maximally coherent collections of (...) tensed facts. In this way, we show how to reconcile a genuinely A-theoretic branching-time model with the idea that there is a branch corresponding to the thin red line, that is, the branch that will turn out to be the actual future history of the world. (shrink)

Fodor and Pylyshyn's critique of connectionism has posed a challenge to connectionists: Adequately explain such nomological regularities as systematicity and productivity without postulating a "language of thought" (LOT). Some connectionists like Smolensky took the challenge very seriously, and attempted to meet it by developing models that were supposed to be non-classical. At the core of these attempts lies the claim that connectionist models can provide a representational system with a combinatorial syntax and processes sensitive to syntactic structure. (...) They are not implementation models because, it is claimed, the way they obtain syntax and structure sensitivity is not "concatenative," hence "radically different" from the way classicists handle them. In this paper, I offer an analysis of what it is to physically satisfy/realize a formal system. In this context, I examine the minimal truth-conditions of LOT Hypothesis. From my analysis it will follow that concatenative realization of formal systems is irrelevant to LOTH since the very notion of LOT is indifferent to such an implementation level issue as concatenation. I will conclude that to the extent to which they can explain the law-like cognitive regularities, a certain class of connectionist models proposed as radical alternatives to the classical LOT paradigm will in fact turn out to be LOT models, even though new and potentially very exciting ones. (shrink)

This paper explains and defends the idea that metaphysical necessity is the strongest kind of objective necessity. Plausible closure conditions on the family of objective modalities are shown to entail that the logic of metaphysical necessity is S5. Evidence is provided that some objective modalities are studied in the natural sciences. In particular, the modal assumptions implicit in physical applications of dynamical systems theory are made explicit by using such systems to define models of a modal temporal logic. Those (...) assumptions arguably include some necessitist principles. -/- Too often, philosophers have discussed ‘metaphysical’ modality — possibility, contingency, necessity — in isolation. Yet metaphysical modality is just a special case of a broad range of modalities, which we may call ‘objective’ by contrast with epistemic and doxastic modalities, and indeed deontic and teleological ones (compare the distinction between objective probabilities and epistemic or subjective probabilities). Thus metaphysical possibility, physical possibility and immediate practical possibility are all types of objective possibility. We should study the metaphysics and epistemology of metaphysical modality as part of a broader study of the metaphysics and epistemology of the objective modalities, on pain of radical misunderstanding. Since objective modalities are in general open to, and receive, natural scientific investigation, we should not treat the metaphysics and epistemology of metaphysical modality in isolation from the metaphysics and epistemology of the natural sciences. -/- In what follows, Section 1 gives a preliminary sketch of metaphysical modality and its place in the general category of objective modality. Section 2 reviews some familiar forms of scepticism about metaphysical modality in that light. Later sections explore a few of the many ways in which natural science deals with questions of objective modality, including questions of quantified modal logic. (shrink)

The functionalist approach to kinds has suffered recently due to its association with law-based approaches to induction and explanation. Philosophers of science increasingly view nomological approaches as inappropriate for the special sciences like psychology and biology, which has led to a surge of interest in approaches to natural kinds that are more obviously compatible with mechanistic and model-based methods, especially homeostatic property cluster theory. But can the functionalist approach to kinds be weaned off its dependency on laws? Dan Weiskopf (...) has recently offered a reboot of the functionalist program by replacing its nomological commitments with a model-based approach more closely derived from practice in psychology. Roughly, Weiskopf holds that the natural kinds of psychology will be the functional properties that feature in many empirically successful cognitive models, and that those properties need not be localized to parts of an underlying mechanism. I here skeptically examine the three modeling practices that Weiskopf thinks introduce such non-localizable properties: fictionalization, reification, and functional abstraction. In each case, I argue that recognizing functional properties introduced by these practices as autonomous kinds comes at clear cost to those explanations’ counterfactual explanatory power. At each step, a tempting functionalist response is parochialism: to hold that the false or omitted counterfactuals fall outside the modeler’s explanatory aims, and so should not be counted against functional kinds. I conclude by noting the dangers this attitude poses to scientific disagreement, inviting functionalists to better articulate how the individuation conditions for functional kinds might outstrip the perspective of a single modeler. (shrink)

This paper addresses a fundamental line of research in neuroscience: the identification of a putative neural processing core of the cerebral cortex, often claimed to be “canonical”. This “canonical” core would be shared by the entire cortex, and would explain why it is so powerful and diversified in tasks and functions, yet so uniform in architecture. The purpose of this paper is to analyze the search for canonical explanations over the past 40 years, discussing the theoretical frameworks informing this research. (...) It will highlight a bias that, in my opinion, has limited the success of this research project, that of overlooking the dimension of cortical development. The earliest explanation of the cerebral cortex as canonical was attempted by David Marr, deriving putative cortical circuits from general mathematical laws, loosely following a deductive-nomological account. Although Marr’s theory turned out to be incorrect, one of its merits was to have put the issue of cortical circuit development at the top of his agenda. This aspect has been largely neglected in much of the research on canonical models that has followed. Models proposed in the 1980s were conceived as mechanistic. They identified a small number of components that interacted as a basic circuit, with each component defined as a function. More recent models have been presented as idealized canonical computations, distinct from mechanistic explanations, due to the lack of identifiable cortical components. Currently, the entire enterprise of coming up with a single canonical explanation has been criticized as being misguided, and the premise of the uniformity of the cortex has been strongly challenged. This debate is analyzed here. The legacy of the canonical circuit concept is reflected in both positive and negative ways in recent large-scale brain projects, such as the Human Brain Project. One positive aspect is that these projects might achieve the aim of producing detailed simulations of cortical electrical activity, a negative one regards whether they will be able to find ways of simulating how circuits actually develop. (shrink)

Husserl’s early picture of explanation in the sciences has never been completely provided. This lack represents an oversight, which we here redress. In contrast to currently accepted interpretations, we demonstrate that Husserl does not adhere to the much maligned deductive-nomological (DN) model of scientific explanation. Instead, via a close reading of early Husserlian texts, we reveal that he presents a unificationist account of scientific explanation. By doing so, we disclose that Husserl’s philosophy of scientific explanation is no mere anachronism. (...) It is, instead, tenable and relevant. We discuss how Husserl and other contemporary thinkers draw theoretical inspiration from the same source—namely, Bernard Bolzano. Husserl’s theory of scientific explanation shares a common language and discusses the same themes as, for example, Phillip Kitcher and Kit Fine. To advance our novel reading, we discuss Husserl’s investigations of grounding, inter-lawful explanation, intra-mathematical explanation, and scientific unification. (shrink)

I critically examine the assumption that the theoretical structure that varies under theoretical symmetries is redundant and should be eliminated from a metaphysical picture of the universe, following a ‘symmetry to reality’ inference. I do so by analysing the status of coordinate change symmetries taking a pragmatic approach. I argue that coordinate systems function as indexical devices, and play an important pragmatic role for representing concrete physical systems. I examine the implications of considering this pragmatic role seriously, taking what I (...) call a perspectivist stance. My conclusion is that under a perspectivist stance, all symmetries (including local gauge symmetries) potentially have a direct empirical status: they point to dynamical aspects that are invariant under changes of operationalisation, and they constitute a guide not to reality, but to nomology and kinship. (shrink)

How does vagueness interact with metaphysical modality and with restrictions of it, such as nomological modality? In particular, how do definiteness, necessity (understood as restricted in some way or not), and actuality interact? This paper proposes a model-theoretic framework for investigating the logic and semantics of that interaction. The framework is put forward in an ecumenical spirit: it is intended to be applicable to all theories of vagueness that express vagueness using a definiteness (or: determinacy) operator. We will show (...) how epistemicists, supervaluationists, and theorists of metaphysical vagueness like Barnes and Williams (2010) can interpret the framework.  We will also present a complete axiomatization of the logic we recommend to both epistemicists and local supervaluationists. . (shrink)

Our examination of universal origins and fine-tuning will begin with a discussion of infl ationary scenarios grafted onto Big Bang cosmology and the proof that all infl ationary spacetimes are past-incomplete. After diverting into a lengthy critical examination of the “different physics” offered by quantum cosmologists at the past-boundary of the universe, we will proceed to dissect the inadequacies of infl ationary explanations and string-theoretic constructs in the context of three cosmological models that have received much attention: the Steinhardt-Turok (...) cyclic ekpyrotic model (which does not invoke inflation), the Gasperini-Veneziano pre-Big Bang infl ationary model, and the inflationary string landscape model advanced by Susskind, Polchinski, Bousso, and Linde. We will argue that none of these highly speculative string cosmologies removes the necessity of a beginning to the process of universe generation, and we will emphasize the implications of this fact. Then, since the inflationary “mechanism” only really addresses the fi ne-tuning of the initial conditions of the universe and not the conditions embodied in its finely tuned laws and constants, we will analyze the adequacy of the string multiverse in its three versions (cyclic ekpyrotic, pre-Big Bang, and landscape) for explaining the nomological structure and values of these precisely tuned life-compatible universal parameters. When all is said and done, it will be clear that transcendent intelligent agency is not just the only causally suffi cient and therefore metaphysically sound explanation for universal origins and fine-tuning, but it is also much more parsimonious, elegant, and resonant with meaning than all of the ad hoc machinations of multiverse cosmology. (shrink)

In recent years, New Mechanism has become one of the most popular and widely discussed philosophical accounts of scientific explanation. Some of its proponents see it as a successor to traditional deductive nomological and statistical approaches to the philosophy of explanation. New Mechanists thus argue for the generality of their approach as a model of scientific explanation. Here we will show that the generality of NME as an account of scientific explanation is restricted. Most significantly, NME is widely recognized (...) to have trouble in accounting for explanation in traditional physics. Yet, in the face of obstacles to NME in the physical sciences, New Mechanists have yet to provide a convincing defense of the generality of their view. In this paper, I (1) summarize when and how NME works, (2) describe briefly what NME is not and can’t be, (3) outline some areas of contemporary scientific explanation where New Mechanism misses the mark; and (4) demonstrate that New Mechanism does not constitute a general theory of scientific explanation but rather covers a restricted scope of explanations. (shrink)

Le réalisme structural est une tentative d’établir un compromis entre le réalisme scientifique et l’empirisme, en restreignant le réalisme à la structure relationnelle des théories scientifiques. Il se décline en deux versions, épistémique et ontique. Le réalisme structural ontique propose de concevoir les relations nomologiques décrites par les théories comme des éléments primitifs de la réalité. Il est motivé, notamment, par le fait que sous sa forme épistémique, le réalisme structural ne se distingue pas réellement d’une position empiriste. Cependant, il (...) fait face à des difficultés, en particulier pour différencier relations physiques et mathématiques et rendre compte de l’ancrage expérimental des théories. Il est possible d’établir un parallèle entre ces difficultés et le problème de la mesure en mécanique quantique, qui concerne lui aussi les rapports entre modèle théorique et expérience : on constate alors qu’un réalisme structural épistémique est plus à même d’y répondre. Une solution de compromis entre le réalisme structural ontique et le réalisme structural épistémique pourrait permettre de conserver les avantages des deux positions. -/- Structural realism attempts to make a compromise between scientific realism and empiricism, by restricting our realist commitment to the relational structure of scientific theories. There are two main versions of the position: ontic, or epistemic. According to ontic structural realism, the nomological relations expressed by theories are the primitive entities of reality. This ontic version is motivated in particular by arguments to the effect that epistemic versions are not really distinct from mere empiricism. However according to some authors, it’s not clear that ontic structural realism can differentiate between physical and mathematical relations, and account for the relations between scientific theories and their experimental basis. These difficulties can be related to the measurement problem in quantum mechanics, which also concerns the link between theoretical models and experiments. It appears that epistemic structural realism is in a better position to respond to these difficulties. A compromise between both versions of structural realism could allow us to keep the advantages of both. (shrink)

Al final de su libro “La conciencia inexplicada”, Juan Arana señala que la nomología, explicación según las leyes de la naturaleza, requiere de una nomogonía, una consideración del origen de las leyes. Es decir, que el orden que observamos en el mundo natural requiere una instancia previa que ponga ese orden específico. Sabemos que desde la revolución científica la mejor manera de explicar dicha nomología ha sido mediante las matemáticas. Sin embargo, en las últimas décadas se han presentado algunas propuestas (...) basadas en modelos matemáticos que fundamentarían muchos aspectos de la realidad. Dos claros ejemplos provienen de Roger Penrose y Max Tegmark. Esto lleva a pensar en una posición no solo nomológica sino además nomogónica de la matemática. ¿Puede la Naturaleza estar fundada por las matemáticas como señalan algunos físico-matemáticos? Y en ese caso, ¿sería pertinente buscar una nomo-génesis de esta índole en la constitución de la conciencia? -/- At the end of his book “La conciencia inexplicada”, Juan Arana points out that nomology, explanation according to the laws of nature requires a nomogony, an account of the origin of the laws. This means that the order that we can observe in the natural World demands something prior to posit that specific order. Since the scientific revolution we know that the best way to explain that nomology has been through mathematics. Anyway, in recent decades a number of proposals based on mathematical models that found many aspects of reality has been offered. Two clear examples come from Roger Penrose and Max Tegmark. This drives us to think of a position of mathematics as not only nomological but also nomogonical. Can Nature be founded by mathematics as some physicists and mathematicians point out? And, in this case, would be relevant this kind of approach to search a nomo-genesis in the constitution of consciousness? (shrink)

According to the Nomological Argument, observed regularities in nature are best explained by an appeal to a supernatural being. A successful explanation must avoid two perils. Some explanations provide too little structure, predicting a universe without regularities. Others provide too much structure, thereby precluding an explanation of certain types of lawlike regularities featured in modern scientific theories. We argue that an explanation based in the creative, intentional action of a supernatural being avoids these two perils whereas leading competitors do (...) not. Although our argument falls short of a full defense, it does suggest that the Nomological Argument is worthy of philosophical attention. (shrink)

Our universe features a harmonious match between laws and states: applying its laws to its states generates other states. This is a striking fact. Matters might have been otherwise. The universe might have been stillborn in a state unengaged by its laws. The problem of nomological harmony is that of explaining the noted striking fact. After introducing and developing this problem, we canvass candidate solutions and identify some of their virtues and vices. Candidate solutions invoke the likes of a (...) designer, axiarchic meta-laws, multiverses, essential causal powers, and Humean laws. (shrink)

Since causal processes can be prevented and interfered with, law-governed causation is a challenge for necessitarian theories of laws of nature. To show that there is a problematic friction between necessity and interference, I focus on David Armstrong's theory; with one proviso, his lawmaker, nomological necessity, is supposed to be instantiated as the causation of the law's second relatum whenever its first relatum is instantiated. His proviso is supposed to handle interference cases, but fails to do so. In order (...) to be able to handle interferences, any theory which utilizes a kind of necessitation as lawmaker has to downgrade what it treats as necessity to something more akin to (Newtonian) forces. (shrink)

Current work in language models (LMs) helps us speed up or even skip thinking by accelerating and automating cognitive work. But can LMs help us with critical thinking -- thinking in deeper, more reflective ways which challenge assumptions, clarify ideas, and engineer new concepts? We treat philosophy as a case study in critical thinking, and interview 21 professional philosophers about how they engage in critical thinking and on their experiences with LMs. We find that philosophers do not find LMs (...) to be useful because they lack a sense of selfhood (memory, beliefs, consistency) and initiative (curiosity, proactivity). We propose the selfhood-initiative model for critical thinking tools to characterize this gap. Using the model, we formulate three roles LMs could play as critical thinking tools: the Interlocutor, the Monitor, and the Respondent. We hope that our work inspires LM researchers to further develop LMs as critical thinking tools and philosophers and other 'critical thinkers' to imagine intellectually substantive uses of LMs. (shrink)

Science and fiction seem to lie at opposite ends of the cognitive-epistemic spectrum. The former is typically seen as the study of hard, real-world facts in a rigorous manner. The latter is treated as an instrument of play and recreation, dealing in figments of the imagination. Initial appearances notwithstanding, several central features of scientific modeling in fact suggest a close connection with the imagination and recent philosophers have developed detailed accounts of models that treat them, in one way or (...) another, as akin to fictions. This chapter will critically discuss the fictions approach as an epistemology of scientific modeling. (shrink)

This paper provides a general introduction to the use of causal models in the metaphysics of causation, specifically structural equation models and directed acyclic graphs. It reviews the formal framework, lays out a method of interpretation capable of representing different underlying metaphysical relations, and describes the use of these models in analyzing causation.

This paper addresses the question of what constitutes an apt interpreted model for the purpose of analyzing causation. I first collect universally adopted aptness principles into a basic account, flagging open questions and choice points along the way. I then explore various additional aptness principles that have been proposed in the literature but have not been widely adopted, the motivations behind their proposals, and the concerns with each that stand in the way of universal adoption. I conclude that the remaining (...) work of articulating aptness for a SEM analysis of causation is tied up with issue to do with modality, ontology, and mereology. Continuing this work is therefore likely to shed light on the relationship between these areas and causation more generally. (shrink)

The zombie, mocking all nomological arguments, gives rise to axiological considerations that also result in a vindication of the nomological paradigm. So the ‘philosophical benefit of zombies’ ultimately proves to be that they lead to an understanding they were originally invented to refute.

I argue that normative formal epistemology (NFE) is best understood as modelling, in the sense that this is the reconstruction of its methodology on which NFE is doing best. I focus on Bayesianism and show that it has the characteristics of modelling. But modelling is a scientific enterprise, while NFE is normative. I thus develop an account of normative models on which they are idealised representations put to normative purposes. Normative assumptions, such as the transitivity of comparative credence, are (...) characterised as modelling idealisations motivated normatively. I then survey the landscape of methodological options: what might formal epistemologists be up to? I argue the choice is essentially binary: modelling or theorising. If NFE is theorising it is doing very poorly: generating false claims with no clear methodology for separating out what is to be taken seriously. Modelling, by contrast, is a successful methodology precisely suited to the management of useful falsehoods. Regarding NFE as modelling is not costless, however. First, our normative inferences are less direct and are muddied by the presence of descriptive idealisations. Second, our models are purpose-specific and limited in their scope. I close with suggestions for how to adapt our practice. (shrink)

The juxtaposition of models of God and Christian faith may seem repugnant to many, as models are tentative and faith aims at an abiding certainty. In fact, for many Christians, using models of God in worship amounts to idolatry. By examining Biblical and extra-Biblical views of idolatry, I argue that models are not idols. To the contrary, the practice of God-modeling inoculates Christians against one of the most seductive idols of our age: the love of certainty. (...) Furthermore, by examining meditations upon certainty in Melville’s Moby Dick and the early discourses of the Buddha, I suggest that overweening conviction is a vice that hinders rather than guarantees Christian discipleship, and that Christian faith is better defined as any or all of the following: relative confidence in propositions, faithful relationship, and a virtue of disciplined credulity. (shrink)

In this paper I investigate, within the framework of realistic interpretations of the wave function in nonrelativistic quantum mechanics, the mathematical and physical nature of the wave function. I argue against the view that mathematically the wave function is a two-component scalar field on configuration space. First, I review how this view makes quantum mechanics non- Galilei invariant and yields the wrong classical limit. Moreover, I argue that interpreting the wave function as a ray, in agreement many physicists, Galilei invariance (...) is preserved. In addition, I discuss how the wave function behaves more similarly to a gauge potential than to a field. Finally I show how this favors a nomological rather than an ontological view of the wave function. (shrink)

One might be inclined to assume, given the mouse donning its cover, that the behavior of interest in Nicole Nelson's book Model Behavior (2018) is that of organisms like mice that are widely used as “stand-ins” for investigating the causes of human behavior. Instead, Nelson's ethnographic study focuses on the strategies adopted by a community of rodent behavioral researchers to identify and respond to epistemic challenges they face in using mice as models to understand the causes of disordered human (...) behaviors associated with mental illness. Although Nelson never explicitly describes the knowledge production activities in which her behavioral geneticist research subjects engage as “exemplary”, the question of whether or not these activities constitute “model behavior(s)”—generalizable norms for engaging in scientific research—is one of the many thought-provoking questions raised by her book. As a philosopher of science interested in this question, I take it up here. (shrink)

This paper introduces and defends an account of model-based science that I dub model pluralism. I argue that despite a growing awareness in the philosophy of science literature of the multiplicity, diversity, and richness of models and modeling practices, more radical conclusions follow from this recognition than have previously been inferred. Going against the tendency within the literature to generalize from single models, I explicate and defend the following two core theses: any successful analysis of models must (...) target sets of models, their multiplicity of functions within science, and their scientific context and history and for almost any aspect x of phenomenon y, scientists require multiple models to achieve scientific goal z. (shrink)

Models as Make-Believe offers a new approach to scientific modelling by looking to an unlikely source of inspiration: the dolls and toy trucks of children's games of make-believe.

Should models of consciousness be detailed _mechanistic_ models of particular types of systems, or should they be _minimal_ models that abstract away from the underlying mechanistic details and provide generalisations? Detailed mechanistic models may afford a complete and precise account of consciousness in human beings and other, physiologically similar mammals. But they do not provide a good model of consciousness in other animals, such as non-vertebrates, let alone artificial systems. Minimal models can be applicable to (...) a wide range of different conscious systems. But do they provide genuine explanations that are autonomous from explanations by detailed mechanistic models? This paper provides a taxonomy of minimal models and measures of consciousness, clarifies their relation to detailed mechanistic models, and highlights benefits of different minimalist approaches to consciousness. (shrink)

Despite an enormous philosophical literature on models in science, surprisingly little has been written about data models and how they are constructed. In this paper, I examine the case of how paleodiversity data models are constructed from the fossil data. In particular, I show how paleontologists are using various model-based techniques to correct the data. Drawing on this research, I argue for the following related theses: first, the ‘purity’ of a data model is not a measure of (...) its epistemic reliability. Instead it is the fidelity of the data that matters. Second, the fidelity of a data model in capturing the signal of interest is a matter of degree. Third, the fidelity of a data model can be improved ‘vicariously’, such as through the use of post hoc model-based correction techniques. And, fourth, data models, like theoretical models, should be assessed as adequate for particular purposes. (shrink)

Batterman and Rice ([2014]) argue that minimal models possess explanatory power that cannot be captured by what they call ‘common features’ approaches to explanation. Minimal models are explanatory, according to Batterman and Rice, not in virtue of accurately representing relevant features, but in virtue of answering three questions that provide a ‘story about why large classes of features are irrelevant to the explanandum phenomenon’ ([2014], p. 356). In this article, I argue, first, that a method (the renormalization group) (...) they propose to answer the three questions cannot answer them, at least not by itself. Second, I argue that answers to the three questions are unnecessary to account for the explanatoriness of their minimal models. Finally, I argue that a common features account, what I call the ‘generalized ontic conception of explanation’, can capture the explanatoriness of minimal models. (shrink)

Detailed examinations of scientific practice have revealed that the use of idealized models in the sciences is pervasive. These models play a central role in not only the investigation and prediction of phenomena, but in their received scientific explanations as well. This has led philosophers of science to begin revising the traditional philosophical accounts of scientific explanation in order to make sense of this practice. These new model-based accounts of scientific explanation, however, raise a number of key questions: (...) Can the fictions and falsehoods inherent in the modeling practice do real explanatory work? Do some highly abstract and mathematical models exhibit a noncausal form of scientific explanation? How can one distinguish an exploratory "how-possibly" model explanation from a genuine "how-actually" model explanation? Do modelers face tradeoffs such that a model that is optimized for yielding explanatory insight, for example, might fail to be the most predictively accurate, and vice versa? This chapter explores the various answers that have been given to these questions. (shrink)

The striking difference between the orthodox nomological necessitation view of laws and the claims made recently by Scientific Essentialism is that on the latter interpretation laws are metaphysically necessary while they are contingent on the basis of the former. This shift is usually perceived as an upgrading: essentialism makes the laws as robust as possible. The aim of my paper—in which I contrast Brian Ellis’s Scientific Essentialism and David Armstrong’s theory of nomological necessity—is threefold. (1) I first underline (...) the familiar fact that metaphysical necessity (of Kripkean “water is necessarily H2O” kind) is not a stronger kind of necessity than nomological necessity but an entirely different kind of thing: nomological, but not metaphysical necessity, is an intra-world necessitation which Armstrong (almost) identifies with causation; metaphysical, but not nomological necessitation, has a canonical link to possible world considerations and counterfactual reasoning. Hence, the change from one necessity to the other is not an upgrading but a substantial shift. (2) I will explain how the essentialists, who promote this shift, are nonetheless able to retain the features of nomological necessity. (3) I also explore, for both the essentialist and the Armstrongian, whether they could extract a modal force from intra-world nomological necessity which it does not have per se. I argue that such a modal force is, indeed, obtainable for them. I will close the paper with some remarks and questions about the relation between Kripkean metaphysical necessity and the modal version of nomological necessity as defined in (3). (shrink)

I provide a theory of causation within the causal modeling framework. In contrast to most of its predecessors, this theory is model-invariant in the following sense: if the theory says that C caused (didn't cause) E in a causal model, M, then it will continue to say that C caused (didn't cause) E once we've removed an inessential variable from M. I suggest that, if this theory is true, then we should understand a cause as something which transmits deviant or (...) non-inertial behavior to its effect. (shrink)