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

In this 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)

Among the many functions of models, explanation is central to the functioning and aims of science. However, the discussions surrounding modeling and explanation in philosophy have largely remained separate from each other. This chapter seeks to bridge the gap by focusing on the puzzle of model-based explanation, asking how different philosophical accounts answer the following question: if idealizations and fictions introduce falsehoods into models, how can idealized and fictional models provide true explanations? The chapter (...) provides a selective and critical overview of the available strategies for solving this puzzle, mainly focusing on idealized models and how they explain. (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)

F.A. Hayek argued that the sciences of complex phenomena, including (perhaps especially) economics, are limited to incomplete “explanations of the principle” and “pattern predictions.” According to Hayek, these disciplines suffer from (what I call) a data problem, i.e., the hopelessness of populating theoretical models with data adequate to full explanations and precise predictions. In Hayek’s terms, explanations in these fields are always a matter of “degree.” However, Hayek’s methodology implies a distinct theory problem: theoretical models of complex phenomena (...) may be underspecified so that, even were all the data available, a full explanation could not be inferred from the model. Where the sciences of complex phenomena are subject to both the data and theory problems, explanations and predictions will be of even lesser “predictive degree.” The paper also considers how to interpret Hayek’s claim that pattern predictions are falsifiable. (shrink)

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)

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)

This article is an experiment. Consider a minimalist model of cognition (models, means of model-building and history of their evolution). In this model, explanation could be defined as a means allowing to advance: production of models and means of model-building (thus, yielding 1st class understanding), exploration and use of them (2nd class), and/or teaching (3rd class). At minimum, 3rd class understanding is necessary for an explanation to be respected.

This paper aims to contribute to the existing literature on normative cognition by providing a lineage explanation of human social norm psychology. This approach builds upon theories of goal-directed behavioral control in the reinforcement learning and control literature, arguing that this form of control defines an important class of intentional normative mental states that are instrumental in nature. I defend the view that great ape capacities for instrumental reasoning and our capacity (or family of capacities) for shared intentionality coadapted (...) to each other and argue that the evolution of this capacity has allowed the representation of social norms and the emergence of our capacity for normative guidance. (shrink)

Economists use various models to explain why it is that firms are capable of pricing above marginal cost. In this paper, we will examine two of them: the Cournot and Bertrand duopoly models. Economists generally accept both models as good explanations of the phenomenon, but the two models contradict each other in various important ways. The puzzle is that two inconsistent explanations are both regarded as good explanations for the same phenomenon. This becomes especially worrisome when (...) the two models are offering divergent policy recommendations. This report presents that puzzle by laying out how the two models contradict each other in a myriad of ways and then offers five possible solutions to that puzzle from various economists, philosophers of science, and philosophers of economics. (shrink)

The focus in the literature on scientific explanation has shifted in recent years towards model-based approaches. In recent work, Alisa Bokulich has argued that idealization has a central role to play in explanation. Bokulich claims that certain highly-idealized, structural models can be explanatory, even though they are not considered explanatory by causal, mechanistic, or covering law accounts of explanation. This paper focuses on Bokulich’s account in order to make the more general claim that there are problems (...) with maintaining that a structural criterion can capture the way that highly-idealized models explain. This paper examines Bokulich’s claim that the structural model explanation of quantum wavefunction scarring, featuring semiclassical mechanics, is deeper than the explanation provided by the local quantum model. The challenge for Bokulich is to show that the semiclassical model answers a wider range of w-questions, as this is her method of assessing structural information. I look at two reasonable approaches employing w-questions, and I argue that neither approach is ultimately satisfactory. Because structural similarity has preferences for more fundamental models, I argue that the local quantum model provides explanations that at least as deep as the semiclassical ones. The criterion either wrongly identifies all models as explanatory, or prefers models from fundamental theory. Either way, it cannot capture the way that highly-idealized models explain. (shrink)

Recent work in the methodology of connectionist explanation has I'ocrrsccl on the notion of levels of explanation. Specific issucs in conncctionisrn hcrc intersect with rvider areas of debate in the philosophy of psychology and thc philosophy of science generally. The issues I raise in this chapter, then, are not unique to cognitive science; but they arise in new and important contexts when connectionism is taken seriously as a model of cognition. The general questions are the relation between levels (...) and the status of levels which have no obvious relation to others. In speaking of levels, what is the connection, if there is one, between explanation and ontology? Which, if any, conccpt of reduction is applicable to connectionist systems? What kind of legitinrtcy can the constructs of common sense psychology, or of that vclsion ol intentional realism represented by classical symbol-systems n I, hirvc irr ir full-scale connectionist theory of mind? (shrink)

This is a model of consciousness. The hard problem of consciousness, what it feels like, is answered. The work builds on medical research analyzing the source and mechanisms associated with our feelings. It goes further by describing a generic model with wide applicability. The model is fully consistent with medical pathways in humans, but easily extends to animals and AI. The essence of the model is the interplay between associative memory and physiology. The model is a clear and concrete counterexample (...) to the famous philosophical objections to a scientific explanation. (shrink)

Stanford’s argument against scientific realism focuses on theories, just as many earlier arguments from inconceivability have. However, there are possible arguments against scientific realism involving unconceived (or inconceivable) entities of different types: observations, models, predictions, explanations, methods, instruments, experiments, and values. This paper charts such arguments. In combination, they present the strongest challenge yet to scientific realism.

In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. In this paper, I claim that mechanistic accounts of computation should allow for a broad variation of (...) class='Hi'>models of computation. In particular, some non-standard models should not be excluded a priori. The relationship between mathematical models of computation and mechanistically adequate models is studied in more detail. (shrink)

Active materials are self-propelled non-living entities which, in some circumstances, exhibit a number of cognitively interesting behaviors such as gradient-following, avoiding obstacles, signaling and group coordination. This has led to scientific and philosophical discussion of whether this may make them useful as minimal models of cognition (Hanczyc, 2014; McGivern, 2019). Batterman and Rice (2014) have argued that what makes a minimal model explanatory is that the model is ultimately in the same universality class as the target system, which underpins (...) why it exhibits the same macrobehavior. We appeal to recent research in basal cognition (Lyon et al., 2021) to establish appropriate target systems and essential features of cognition as a target of modeling. Looking at self-propelled oil droplets, a type of active material, we do not find that organization alone indicates that these systems exhibit the essential features of cognition. We then examine the specific behaviors of oil droplets but also fail to find that these demonstrate the essential features of cognition. Without a universality class, Batterman & Rice’s account of the explanatory power of minimal models simply does not apply to cognition. However, we also want to stress that it is not intended to; cognition is not the same type of behavioral phenomena as those found in physics. We then look to the minimal cognition methodology of Beer (1996, 2020a, b) to show how active materials can be explanatorily valuable regardless of their cognitive status because they engage in specific behaviors that have traditionally been expected to involve internal representational dynamics, revealing misconceptions about the cognitive underpinnings of certain, specific behaviors in target systems where such behaviors are cognitive. Further, Beer’s models can also be genuinely explanatory by providing dynamical explanations. (shrink)

Biomedical science has been remarkably successful in explaining illness by categorizing diseases and then by identifying localizable lesions such as a virus and neoplasm in the body that cause those diseases. Not surprisingly, researchers have aspired to apply this powerful paradigm to addiction. So, for example, in a review of the neuroscience of addiction literature, Hyman and Malenka (2001, p. 695) acknowledge a general consensus among addiction researchers that “[a]ddiction can appropriately be considered as a chronic medical illness.” Like other (...) diseases, “Once addiction has taken hold, it tends to follow a chronic course.” (Koob and La Moal 2006, p. ?). Working from this perspective, much effort has gone into characterizing the symptomology of addiction and the brain changes that underlie them. Evidence for involvement of dopamine transmission changes in the ventral tegmental area (VTA) and nucleus accumbens (NAc) have received the greatest attention. Kauer and Malenka (2007, p. 844) put it well: “drugs of abuse can co-opt synaptic plasticity mechanisms in brain circuits involved in reinforcement and reward processing”. Our goal in this chapter to provide an explicit description of the assumptions of medical models, the different forms they may take, and the challenges they face in providing explanations with solid evidence of addiction. <br>. (shrink)

This article defends the principle of sufficient reason (PSR) from a simple and direct valid argument according to which PSR implies that there is a truth that explains every truth, namely an omni-explainer. Many proponents of PSR may be willing to bite the bullet and maintain that, if PSR is true, then there is an omni-explainer. I object to this strategy by defending the principle that explanation is irreflexive. Then I argue that proponents of PSR can resist the conclusion (...) that there is an omni-explainer by denying that explanation distributes over conjunction. In the final section, I consider a plausible revision of this assumption. I argue there that, given the revised assumption, PSR seems to yield a striking picture of the explanatory structure of the universe. I explain why the resulting model does not appear utterly implausible to me. (shrink)

Frank Jackson often writes as if his descriptivist account of public language meanings were just plain common sense. How else are we to explain how different speakers manage to communicate using a public language? And how else can we explain how individuals arrive at confident judgments about the reference of their words in hypothetical scenarios? Our aim in this paper is to show just how controversial the psychological assumptions behind in Jackson’s semantic theory really are. First, we explain how Jackson’s (...) theory goes well beyond the commonsense platitudes he cites in its defence. Second, we sketch an alternative explanation of those platitudes, the jazz model of meaning, which we argue is more psychologically realistic. We conclude that the psychological picture presupposed by Jackson’s semantic theory stands in need of a much more substantial defence than he has so far offered. (shrink)

Building upon Nancy Cartwright's discussion of models in How the Laws of Physics Lie, this paper addresses solid state research in transition metal oxides. Historical analysis reveals that in this domain models function both as the culmination of phenomenology and the commencement of theoretical explanation. Those solid state chemists who concentrate on the description of phenomena pertinent to specific elements or compounds assess models according to different standards than those who seek explanation grounded in approximate (...) applications of the Schroedinger equation. Accurate accounts of scientific debate in this field must include both perspectives. (shrink)

This study analyses the predictions of the General Theory of Relativity (GTR) against a slightly modified version of the standard central mass solution (Schwarzschild solution). It is applied to central gravity in the solar system, the Pioneer spacecraft anomalies (which GTR fails to predict correctly), and planetary orbit distances and times, etc (where GTR is thought consistent.) -/- The modified gravity equation was motivated by a theory originally called ‘TFP’ (Time Flow Physics, 2004). This is now replaced by the ‘Geometric (...) Model’, 2014 [20], which retains the same theory of gravity. This analysis is offered partially as supporting detail for the claim in [20] that the theory is realistic in the solar system and explains the Pioneer anomalies. The overall conclusion is that the model can claim to explain the Pioneer anomalies, contingent on the analysis being independently verified and duplicated of course. -/- However the interest lies beyond testing this theory. To start with, it gives us a realistic scale on which gravity might vary from the accepted theory, remain consistent with most solar-scale astronomical observations. It is found here that the modified gravity equation would appear consistent with GTR for most phenomena, but it would retard the Pioneer spacecraft by about the observed amount (15 seconds or so at time). Hence it is a possible explanation of this anomaly, which as far as I know remains unexplained now for 20 years. -/- It also shows what many philosophers of science have emphasized: the pivotal role of counterfactual reasoning. By putting forward an exact alternative solution, and working through the full explanation, we discover a surprising ‘counterfactual paradox’: the modified theory slightly weakens GTR gravity – and yet the effect is to slow down the Pioneer trajectory, making it appear as if gravity is stronger than GTR. The inference that “there must be some tiny extra force…” (Musser, 1998 [1]) is wrong: there is a second option: “…or there may be a slightly weaker form of gravity than GTR.” . (shrink)

Undoubtedly the Penrose-Hameroff Orch OR model may be considered as a good theory for describing information processing mechanisms and holistic phenomena in the human brain, but it doesn’t give us satisfactory explanation of human perception. In this work a new approach explaining our perception is introduced, which is in good agreement with Orch OR model and other mainstream science theories such as string theory, loop quantum gravity and holographic principle. It is shown that human perception cannot be explained in (...) the terms of elementary particles and we should introduce new indivisible holistic objects with geometry based on smooth infinitesimal analysis - elastic membranes. The example of such a membrane is our Universe which is an indivisible whole. It is shown that our perception may be considered as the result of elastic oscillations of two dimensional (2D) elastic membranes with closed topology embedded in our bodies. Only one elastic membrane responsible for its perceptions will correspond to the selected organism, but there may be other membranes, even at the cell level. In other words, reality may be considered as the process of time evolution of holistic energetically very weak macro objects - elastic membranes with the geometry based on smooth infinitesimal analysis. An embedded membrane in this multidimensional world will look different for the external and internal observers: from the outside it will look like a material object with smooth infinitesimal geometry, while from the inside our Universe-like space-time fabric. When interacting with elementary particles and other membranes, a membrane will transform their energy into its elastic energy (a new form of energy) - the energy of stretching of the infinitesimal segments. The theory postulates that these elastic deformations will not be observable from the point of view of the internal observer. Heisenberg’s uncertainty principle will work in this physics only from the point of view of the internal observer. For the external observer each embedded elastic membrane may be stretched and even a very small region will become observable. For example, living organisms play the role of internal observers of the Universe, and at the same time they serve as external observers for 2D membranes embedded into our Universe. We can observe our 2D self-membranes through our perceptions, which are encoded in elastic oscillations of the elastic membrane. According to the theory, elastic membranes occupy energetically favorable positions around microtubules involved into Orch OR. The theory not only gives us a really multidimensional holistic picture of reality, but it also provides us with a new method for understanding such phenomena as perception, self-awareness and will. (shrink)

Explanation of logic of psychoses: schizophrenia and bi-polar, with empirical confirmation - e.g. IQ decreases the likelihood of psychosis, and bi-polar is more likely than schizophrenia... MA thesis in 1998 (Comenius University), Presented at Art exhibition "From Animation", London, Holland Park (W8 6LU), Conferences in Santorini, Daejon, Adelaide 2016.

Computer simulations constitute a significant scientific tool for promoting scientific understanding of natural phenomena and dynamic processes. Substantial leaps in computational force and software engineering methodologies now allow the design and development of large-scale biological models, which – when combined with advanced graphics tools – may produce realistic biological scenarios, that reveal new scientific explanations and knowledge about real life phenomena. A state-of-the-art simulation system termed Reactive Animation (RA) will serve as a study case to examine the contemporary philosophical (...) debate on the scientific value of simulations, as we demonstrate its ability to form a scientific explanation of natural phenomena and to generate new emergent behaviors, making possible a prediction or hypothesis about the equivalent real-life phenomena. (shrink)

Descriptive accounts of the nature of explanation in neuroscience and the global goals of such explanation have recently proliferated in the philosophy of neuroscience and with them new understandings of the experimental practices of neuroscientists have emerged. In this paper, I consider two models of such practices; one that takes them to be reductive; another that takes them to be integrative. I investigate those areas of the neuroscience of learning and memory from which the examples used to (...) substantiate these models are culled, and argue that the multiplicity of experimental protocols used in these research areas presents specific challenges for both models. In my view, these challenges have been overlooked largely because philosophers have hitherto failed to pay sufficient attention to fundamental features of experimental practice. I demonstrate that when we do pay attention to such features, evidence for reduction and integrative unity in neuroscience is simply not borne out. I end by suggesting some new directions for the philosophy of neuroscience that pertain to taking a closer look at the nature of neuroscientific experiments. (shrink)

Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions. These models are a useful pedagogical device for teaching trained professionals how to predict what decisions will be made by the complex system, and most importantly how the system might break. However, when considering any such model it’s important to remember Box’s maxim that "All models are wrong but some are useful." (...) We focus on the distinction between these models and explanations in philosophy and sociology. These models can be understood as a "do it yourself kit" for explanations, allowing a practitioner to directly answer "what if questions" or generate contrastive explanations without external assistance. Although a valuable ability, giving these models as explanations appears more difficult than necessary, and other forms of explanation may not have the same trade-offs. We contrast the different schools of thought on what makes an explanation, and suggest that machine learning might benefit from viewing the problem more broadly. (shrink)

Mathematical models provide explanations of limited power of specific aspects of phenomena. One way of articulating their limits here, without denying their essential powers, is in terms of contrastive explanation.

I offer a new metacognitive account of the feeling of agency over bodily actions. On this model the feeling of agency is the metacognitive monitoring of two cues: i) smoothness of action: done via monitoring the output of the comparison between actual and predicted sensory consequences of action and ii) action outcome: done via monitoring the outcome of action and its success relative to a prior intention. Previous research has shown that the comparator model offers a powerful explanation of (...) the feeling of agency. However, within the literature there is a growing sense of unease with the model; a consensus seems to be building that the model is not up to the task of explaining all of the new discoveries made regarding the feeling of agency since its inception. Most problematically there are paradigms which deeply challenge the comparator model by suggesting that a weak feeling of agency can be elicited even when no motor prediction is formed. The new account offered here inherits the explanatory power of the comparator model whilst avoiding this problem. (shrink)

In Economics Rules, Dani Rodrik (2015) argues that what makes economics powerful despite the limitations of each and every model is its diversity of models. Rodrik suggests that the diversity of models in economics improves its explanatory capacities, but he does not fully explain how. I offer a clearer picture of how models relate to explanations of particular economic facts or events, and suggest that the diversity of models is a means to better economic explanations.

Philosophers have cataloged a range of genealogical methods by which different sorts of normative conclusions can be established. Although such methods provide diverging ways of pursuing genealogical inquiry, they typically converge in eschewing historiographic methodology, in favor of a uniquely philosophical approach. In contrast, one genealogist who drew on historiographic methodology is Michel Foucault. This article presents the motivations and advantages of Foucault's genealogical use of such a methodology. It advances two mains claims. First, that Foucault's early 1970s work employs (...) a distinct genealogical method, which borrows from contemporary historiographic models of explanation to expand the range of objects that are proper to genealogical accounts of historical change. I demonstrate how Foucault modifies two central commitments of Nietzsche by broadening the dimensions of genealogical inquiry and explanation. Second, that historical method has normative relevance for genealogy, insofar as different historiographic choices can lead to different normative conclusions. I motivate this second claim by explaining how Foucault's multidimensional genealogical method expands both (a) the range of objects that are subject to evaluative assessment, and (b) the set of possible prescriptive recommendations that follow from such assessment. (shrink)

The Protagoras is the touchstone of Socrates’ moral intellectualist stance. The position in a nutshell stipulates that the proper reevaluation of a desire is enough to neutralize it.[1] The implication of this position is that akrasia or weakness of will is not the result of desire (or fear for that matter) overpowering reason but is due to ignorance. -/- Socrates’ eliminativist position on weakness of will, however, flies in the face of the common-sense experience regarding akratic action and thus Aristotle (...) was at pains to render Socrates’ account of moral incontinence intelligible. The key improvement Aristotle makes to Socrates’s model is to underscore that the conditioning of the akratic’s body plays a critical role in determining the power of one’s appetites and, accordingly, the capacity of one to resist the temptations these appetites present for rational evaluation. As Aristotle puts it, “For the incontinent man is like the people who get drunk quickly and on little wine, i.e., on less than most people.” (1151a 3-4). Aristotle presents what I shall call a somatic paradigm (i.e. the drunkard analogy) in order to tackle the problem of akrasia and it is this somatic solution that marks a significant improvement over Socrates’s intellectualist or informational model or so the tradition tells us. -/- In this paper, I wish to push back on the above Aristotelian explanation. I argue that when one fully examines Socrates’ account of weakness of will that Aristotle’s solution is less effective than is traditionally thought. In fact, Socrates can bring Aristotle’s model into his own; just as Aristotle absorbs what is right about Socrates’s model, namely, that akratic action utilizes reason but to a limited degree, Socrates in Meno (77C-78A) develops his own somatic model of weakness of will that connects to the intellectualist paradigm of the Protagoras. To achieve this rapprochement between the two models, I zero in on the description provided by Socrates of those individuals who desire bad things knowing they are bad as “ill-starred” or “bad spirited” (κακοδαίμων ). The “bad-spirited” is the coward and, in contrast to Aristotle’s drunkard, becomes fearful quickly from little danger. This additional somatic component, when connected to Socrates’s position on akrasia in Protagoras adds a new twist to Socrates’s model in the following way: while no one wishes to be ill-starred such that more harm than good will befall one, one may become so as a result of the bad choices one knowingly makes. -/- -/- [1] “After him came Socrates, who spoke better and further about this subject, but even he was not successful. For he used to make the virtues into sciences, and this is impossible. For the sciences all involve reason, and reason is to be found in the intellectual part of the soul. So that all the virtues, according to him arise in the rational part of the soul. The result is that in making the virtues into sciences he is doing away with the nonrational part of the soul and is thereby doing away with passion and character…” (Aristotle, Magna Moralia 1.1. 1182 a15-26). (shrink)

This Research Topic aimed at deepening our understanding of the levels and explanations that are of interest for cognitive sci- entists, neuroscientists, psychologists, behavioral scientists, and philosophers of science. Indeed, contemporary developments in neuroscience and psy- chology suggest that scientists are likely to deal with a multiplicity of levels, where each of the different levels entails laws of behavior appropriate to that level (Berntson et al., 2012). Also, gathering and modeling data at the different levels of analysis is not suffi- (...) cient: the integration of information across levels of analysis is a crucial issue. Given such state of affairs, a number of interesting questions arise. How can the autonomy of explanatory levels be properly understood in behavioral explanation? Is reductionism a satis- factory strategy? How can high-level and low-level models be constrained in order to be actually explanatory of both behav- ioral and neurological or molecular evidence? What is the kind of relationship between those models? (shrink)

Agent-based models (ABMs) are one type of simulation model used in the context of the COVID-19 pandemic. In contrast to equation-based models, ABMs are algorithms that use individual agents and attribute changing characteristics to each one, multiple times during multiple iterations over time. This paper focuses on three philosophical aspects of ABMs as models of causal mechanisms, as generators of emergent phenomena, and as providers of explanation. Based on my discussion, I conclude that while ABMs cannot (...) help much with causal inference, they can be viewed as etio-prognostic explanations of illness occurrence and outcome. (shrink)

This paper addresses the recent rise of the use of alternative medicine in Western countries. It offers a novel explanation of that phenomenon in terms of cognitive and economic factors related to the free-market and patient-centric approach to medicine that is currently in place in those countries, in contrast to some alternative explanations of this phenomenon. Moreover, the paper addresses this troubling trend in terms of the serious harms associated with the use of alternative medical modalities. The explanatory theory (...) defended here is then predicated on the idea that an extreme patient-centric model of medical practice that treats largely ignorant patients as consumers of medical products and services endowed with an essentially unrestricted power of freedom to choose treatments predictably leads serious and avoidable harms. Some important moral and epistemological consequences of this model are then articulated and corrective measures are suggested. (shrink)

The relationship between topological explanation and mechanistic explanation is unclear. Most philosophers agree that at least some topological explanations are mechanistic explanations. The crucial question is how to make sense of this claim. Zednik (Philos Psychol 32(1):23–51, 2019) argues that topological explanations are mechanistic if they (i) describe mechanism sketches that (ii) pick out organizational properties of mechanisms. While we agree with Zednik’s conclusion, we critically discuss Zednik’s account and show that it fails as a general account of (...) how and when topological explanations are mechanistic. First, if topological explanations were just mechanism sketches, this implies that they could be enriched by replacing topological terms with mechanistic detail. This, however, conflicts how topological explanations are used in scientific practice. Second, Zednik’s account fails to show how topological properties can be organizational properties of mechanisms that have a place in mechanistic explanation. The core issue is that Zednik’s account ignores that topological properties often are _global_ properties while mechanistic explanantia refer to _local_ properties. We demonstrate how these problems can be solved by a recent account of mechanistic completeness (Craver and Kaplan in Br J Philos Sci 71(1):287–319, 2020; Kohár and Krickel in Calzavarini and Viola (eds) Neural mechanisms—new challenges in the philosophy of neuroscience, Springer, New York, 2021) and use a multilayer network model of Alzheimer’s Disease to illustrate this. (shrink)

In a recent special issue dedicated to Dani Rodrik’s (2015) influential monograph Economics Rules, Grüne-Yanoff and Marchionni (2018) raise a potentially damning problem for Rodrik’s suggestion that progress in economics should be understood and measured laterally, by a continuous expansion of new models. They argue that this could lead to an “embarrassment of riches”, i.e. the rapid expansion of our model library to such an extent that we become unable to choose between the available models, and thus needs (...) to be solved to make ‘model pluralism’ viable. Drawing on Veit’s (2019a) ‘model pluralism’ account, this paper argues that model pluralism as a thesis about the relationship between science and nature undermines the very idea of a general model selection framework for policy making. (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 essay develops an inferential account of model explanation, based on Mauricio Suárez’s inferential conception of scientific representation and Alisa Bokulich’s counterfactual account of model explanation. It is suggested that the fact that a scientific model can explain is essentially linked to how a modeler uses an established model to make various inferences about the target system on the basis of results derived from the model. The inference practice is understood as a two-step activity, with the first step (...) involving making counterfactual statements about the model itself and the second step involving making hypothetical statements transferring over claims derived from the model onto the target. To illustrate how this two-step activity proceeds, an agent-based simulation model is discussed. (shrink)

Marc Lange has recently raised three objections to the account of minimal model explanations offered by Robert Batterman and Collin Rice. In this article, I suggest that these objections are misguided. I suggest that the objections raised by Lange stem from a misunderstanding of the what it is that minimal model explanations seek to explain. This misunderstanding, I argue, consists in Lange’s seeing minimal model explanations as relating special types of models to particular target systems rather than seeing minimal (...) model explanations as looking to explain robust patterns of behavior that are exhibited by a variety of physically diverse systems. (shrink)

As the demand for explainable deep learning grows in the evaluation of language technologies, the value of a principled grounding for those explanations grows as well. Here we study the state-of-the-art in explanation for neural models for natural-language processing (NLP) tasks from the viewpoint of philosophy of science. We focus on recent evaluation work that finds brittleness in explanations obtained through attention mechanisms.We harness philosophical accounts of explanation to suggest broader conclusions from these studies. From this analysis, (...) we assert the impossibility of causal explanations from attention layers over text data. We then introduce NLP researchers to contemporary philosophy of science theories that allow robust yet non-causal reasoning in explanation, giving computer scientists a vocabulary for future research. (shrink)

The purpose of the article is to provide the evolving international trends of modern management models and authorial vision of model of state governance system in Ukraine, its subsystems, in particular, the system of provision of administrative services that is appropriate for the contemporary times. Methodology. On the basis of scientific and theoretical approaches to the definitions of terms “state governance” and “public governance”, there was an explanation of considerable difference between them and, taking into consideration, the mentality (...) of Ukrainian society and peculiar weak side in self-organization, the authors offered to form authorial model of governance on the basis of historically traditional for Ukraine model of state governance and to add some elements of management concepts that proved their significance, efficiency and priority in practice. Results. The authors emphasized the following two prevailing modern management models in the international practice: “new state management” and “good governance”. The first concept offered for consideration served as a basis for the semantic content of state activity that reflects more the state of administrative reformation. Practical meaning. A practical introduction of management to the domestic model of governance creates the range of contradictions that do not allow implementing herein concept. Pursuant to authors, the second one allows in considerable measure to reform state governance, considering historically developed peculiarities of this model. Moreover, the involvement of concept herein into introduction of informational and communicational technologies in the process of governance eliminates the necessity of power decentralization, it allows to form real net structure and, at the same, to keep vertical power structure, to involve citizens for formation and taking of management decisions, to form electronic communicational channel of feedback, to provide citizens with electronic administrative services. All indicated advantages of the concept certify about the necessity to reform state governance exactly in this field. Meaning/ Distinction. This article raises a question about the significance of formation and sequence of state policy in Ukraine aimed at creating an information-oriented society, space, as well as informational and technological infrastructure. (shrink)

I argue that there are no plausible non-representational explanations of episodes of hallucination. To make the discussion more specific, I focus on visual hallucinations in Charles Bonnet syndrome. I claim that the character of such hallucinatory experiences cannot be explained away non-representationally, for they cannot be taken as simple failures of cognizing or as failures of contact with external reality—such failures being the only genuinely non-representational explanations of hallucinations and cognitive errors in general. I briefly introduce a recent computational model (...) of hallucination, which relies on generative models in the brain, and argue that the model is a prime example of a representational explanation referring to representational mechanisms. The notion of the representational mechanism is elucidated, and it is argued that hallucinations—and other kinds of representations—cannot be exorcised from the cognitive sciences. (shrink)

I compare Frith and colleagues’ influential comparator account of how the sense of agency is elicited to the multifactorial weighting model advocated by Synofzik and colleagues. I defend the comparator model from the common objection that the actual sensory consequences of action are not needed to elicit the sense of agency. I examine the comparator model’s ability to explain the performance of healthy subjects and those suffering from delusions of alien control on various self-attribution tasks. It transpires that the comparator (...) model needs case-by-case adjustment to deal with problematic data. In response to this, the multifactorial weighting model of Synofzik and colleagues is introduced. Although this model is incomplete, it is more naturally constrained by the cases that are problematic for the comparator model. However, this model may be untestable. I conclude that currently the comparator model approach has stronger support than the multifactorial weighting model approach. (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)

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)

In the spirit of explanatory pluralism, this chapter argues that causal and noncausal explanations of a phenomenon are compatible, each being useful for bringing out different sorts of insights. After reviewing a model-based account of scientific explanation, which can accommodate causal and noncausal explanations alike, an important core conception of noncausal explanation is identified. This noncausal form of model-based explanation is illustrated using the example of how Earth scientists in a subfield known as aeolian geomorphology are explaining (...) the formation of regularlyspaced sand ripples. The chapter concludes that even when it comes to everyday "medium-sized dry goods" such as sand ripples, where there is a complete causal story to be told, one can find examples of noncausal scientific explanations. (shrink)

Moral philosophers are, among other things, in the business of constructing moral theories. And moral theories are, among other things, supposed to explain moral phenomena. Consequently, one’s views about the nature of moral explanation will influence the kinds of moral theories one is willing to countenance. Many moral philosophers are (explicitly or implicitly) committed to a deductive model of explanation. As I see it, this commitment lies at the heart of the current debate between moral particularists and moral (...) generalists. In this paper I argue that we have good reasons to give up this commitment. In fact, I show that an examination of the literature on scientific explanation reveals that we are used to, and comfortable with, non-deductive explanations in almost all areas of inquiry. As a result, I argue that we have reason to believe that moral explanations need not be grounded in exceptionless moral principles. (shrink)

A common kind of explanation in cognitive neuroscience might be called functiontheoretic: with some target cognitive capacity in view, the theorist hypothesizes that the system computes a well-defined function (in the mathematical sense) and explains how computing this function constitutes (in the system’s normal environment) the exercise of the cognitive capacity. Recently, proponents of the so-called ‘new mechanist’ approach in philosophy of science have argued that a model of a cognitive capacity is explanatory only to the extent that it (...) reveals the causal structure of the mechanism underlying the capacity. If they are right, then a cognitive model that resists a transparent mapping to known neural mechanisms fails to be explanatory. I argue that a functiontheoretic characterization of a cognitive capacity can be genuinely explanatory even absent an account of how the capacity is realized in neural hardware. (shrink)

By now a consensus has emerged that people, when subjected to high-stakes decisions through automated decision systems, have a moral right to have these decisions explained to them. However, furnishing such explanations can be costly. So the right to an explanation creates what we call the cost problem: providing subjects of automated decisions with appropriate explanations of the grounds of these decisions can be costly for the companies and organisations that use these automated decision systems. In this paper, we (...) explore whether large language models could prove significant in overcoming the cost problem. We provide an initial case for believing that they can but only with serious ethical costs. (shrink)