Theologians and philosophers have argued against an interventionist view of divine action for centuries. Although God could intervene in the natural order, they believe that God does not and will not. This chapter first considers the arguments against the traditional, interventionist view of divine action. There are five main reasons why divine intervention has come under fire in recent decades: (i) an incompetent god; (ii) a capricious or inconsistent god; (iii) the problem of evil; (iv) the god of the gaps; (...) and (v) conflicts with science. The chapter then presents a brief discussion of the laws of nature, some specific noninterventionist models, and an assessment of the most popular such model based on quantum mechanics. It ends with a reexamination of the motives for noninterventionism and a new way to understand what the fight is about. (shrink)

It is often assumed that there is a hard line between theistic evolution (TE) and intelligent design (ID). Many theistic evolutionists subscribe to the idea that God only acts through natural processes, as opposed to the ID assertion that God, at certain points in natural history, has acted in a direct manner; directly causing particular features of the world. In this article, I argue that theistic evolutionists subscribe to what might be called Natural Divine Causation (NDC). NDC does not merely (...) provide a nonsupernaturalist and noninterventionist model of divine action, it provides a line of demarcation between TE and ID. I make the critique that NDC is philosophically untenable and argue, consequently, that the line between TE and ID is blurred. (shrink)

A recent noninterventionist account of divine agency has been proposed that marries the probabilistic nature of quantum mechanics to the instability of chaos theory. On this account, God is able to bring about observable effects in the macroscopic world by determining the outcome quantum events. When this determination occurs in the presence of chaos, the ability to influence large systems is multiplied. This paper argues that although the proposal is highly intuitive, current research in dynamics shows that it is (...) far less plausible than previously thought. Chaos coupled to quantum mechanics proves to be a shaky foundation for models of divine agency. (shrink)

Is the human mind uniquely nonphysical or even spiritual, such that divine intentions can meet physical realities? As scholars in science and religion have spent decades attempting to identify a 'causal joint' between God and the natural world, human consciousness has been often privileged as just such a locus of divine-human interaction. However, this intuitively dualistic move is both out of step with contemporary science and theologically insufficient. By discarding the God-nature model implied by contemporary noninterventionist divine action theories, (...) one is freed up to explore theological and metaphysical alternatives for understanding divine action in the mind. Sarah Lane Ritchie suggests that a theologically robust theistic naturalism offers a more compelling vision of divine action in the mind. By affirming that to be fully natural is to be involved with God's active presence, one may affirm divine action not only in the human mind, but throughout the natural world. (shrink)

Recent years have seen a shift in divine action debates. Turning from noninterventionist, incompatibilist causal joint models, representatives of a “theological turn” in divine action have questioned the metaphysical assumptions of approaches seeking indeterministic aspects of nature wherein God might act. Various versions of theistic naturalism offer specific theological frameworks that reimagine the basic God–world relationship. But do these explicitly theological approaches to divine action take scientific knowledge and methodology seriously enough? And do such approaches adequately address the (...) problem of how uncreated, immaterial realities could affect physical, material processes? This article examines various features of the theological turn in divine action—recognizing it as a welcome step in science and religion, while challenging its current adequacy. (shrink)

" In Imagination and the Meaningful Brain, psychoanalyst Arnold Modell claims that subjective human experience must be included in any scientific...

If models can be true, where is their truth located? Giere (Explaining science, University of Chicago Press, Chicago, 1998) has suggested an account of theoretical models on which models themselves are not truth-valued. The paper suggests modifying Giere’s account without going all the way to purely pragmatic conceptions of truth—while giving pragmatics a prominent role in modeling and truth-acquisition. The strategy of the paper is to ask: if I want to relocate truth inside models, how do (...) I get it, what else do I need to accept and reject? In particular, what ideas about model and truth do I need? The case used as an illustration is the world’s first economic model, that of von Thünen (1826/1842) on agricultural land use in the highly idealized Isolated State. (shrink)

Abstract.Since the gene splicing debates of the 1980s, the public has been exposed to an ongoing sequence of genetic and reproductive technologies. Many issue areas have outcomes that lose track of people's inner values or engender opposing religious viewpoints defying final resolution. This essay relocates the discussion of what is an acceptable application from the individual to the societal level, examining technologies that stand to address large numbers of people and thus call for policy resolution, rather than individual fiat, in (...) their application. A major source of guidance is the “Genetic Frontiers” series of professional dialogues and conferences held by the National Conference for Community and Justice from 2002 to 2004. Genetic testing, human gene therapy, genetic engineering of plants and animals, and stem cell technology are examined. While differences in perspective on the beginning of life persist, a stepwise approach to the examination of genetic testing reveals areas of general agreement. Stewardship of life, human co‐creativity with the divine, and social justice help define the bounds of application of genetic engineering and therapy; compassionate care plays a major role in establishing stem cell policy. Active, sustained dialogue is a useful resource for enabling sharing of religious values and crystallization of policies. (shrink)

Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal (...) class='Hi'>models provide understanding misguided? In this paper, using the case of deep neural networks, I argue that it is not the complexity or black box nature of a model that limits how much understanding the model provides. Instead, it is a lack of scientific and empirical evidence supporting the link that connects a model to the target phenomenon that primarily prohibits understanding. (shrink)

Aristotle is oftentimes viewed through a strictly philosophical lens as heir to Plato and has having introduced logical rigor where an emphasis on the theory of Forms formerly prevailed. It must be appreciated that Aristotle was the son of a physician, and that his inculcation of the thought of other Greek philosophers addressing health and the natural elements led to an extremely broad set of biologically- and medically-related writings. As this article proposes, Aristotle deepened the fourfold theory of the elements (...) with anatomic and physiologic observations. In books like History of Animals, Parts of Animals, and the lost Anatomai, he actively dissected organisms and recorded his findings. The corpus of medically-related literature Aristotle developed had a direct influence on subsequent Greek thinkers, including Galen, and on Medieval Islamic and modern Western practitioners such as William Harvey. Aristotle's ideas continue to influence modern medical thinkers in Europe and America through both his interpretation by European philosophers gaining the attention of medical humanists, and his writings' enduring impact on medical researchers balancing scientific with more personalistic approaches to medicine. (shrink)

The estrangement between genetic scientists and theologians originating in the 1960s is reflected in novel combinations of human thought (subject) and genes (investigational object), paralleling each other through the universal process known in chaos theory as self-similarity. The clash and recombination of genes and knowledge captures what Philip Hefner refers to as irony, one of four voices he suggests transmit the knowledge and arguments of the religion-and-science debate. When viewed along a tangent connecting irony to leadership, journal dissemination, and the (...) activities of the "public intellectual" and the public at large, the sequence of voices is shown to resemble the passage of genetic information from DNA to mRNA, tRNA, and protein, and from cell nucleus to surrounding environment. In this light, Hefner's inquiry into the voices of Zygon is bound up with the very subject matter Zygon covers. (shrink)

Scientific models invariably involve some degree of idealization, abstraction, or nationalization of their target system. Nonetheless, I argue that there are circumstances under which such false models can offer genuine scientific explanations. After reviewing three different proposals in the literature for how models can explain, I shall introduce a more general account of what I call model explanations, which specify the conditions under which models can be counted as explanatory. I shall illustrate this new framework by (...) applying it to the case of Bohr's model of the atom, and conclude by drawing some distinctions between phenomenological models, explanatory models, and fictional models. (shrink)

This article shows how the MISS account of models—as isolations and surrogate systems—accommodates and elaborates Sugden’s account of models as credible worlds and Hausman’s account of models as explorations. Theoretical models typically isolate by means of idealization, and they are representatives of some target system, which prompts issues of resemblance between the two to arise. Models as representations are constrained both ontologically (by their targets) and pragmatically (by the purposes and audiences of the modeller), and (...) these relations are coordinated by a model commentary. Surrogate models are often about single mechanisms. They are distinguishable from substitute models, which are examined without any concern about their connections with the target. Models as credible worlds are surrogate models that are believed to provide access to their targets on account of their credibility (of which a few senses are distinguished). (shrink)

one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...

Toy models are highly idealized and extremely simple models. Although they are omnipresent across scientific disciplines, toy models are a surprisingly under-appreciated subject in the philosophy of science. The main philosophical puzzle regarding toy models is that it is an unsettled question what the epistemic goal of toy modeling is. One promising proposal for answering this question is the claim that the epistemic goal of toy models is to provide individual scientists with understanding. The aim (...) of this paper is to precisely articulate and to defend this claim. In particular, we will distinguish between autonomous and embedded toy models, and, then, argue that important examples of autonomous toy models are sometimes best interpreted to provide how-possibly understanding, while embedded toy models yield how-actually understanding, if certain conditions are satisfied. (shrink)

Fundamental theories are hard to come by. But even if we had them, they would be too complicated to apply. Quantum chromodynamics is a case in point. This theory is supposed to govern all strong interactions, but it is extremely hard to apply and test at energies where protons, neutrons and ions are the effective degrees of freedom. Instead, scientists typically use highly idealized models such as the MIT Bag Model or the Nambu Jona-Lasinio Model to account for phenomena (...) in this domain, to explain them and to gain nderstanding. Based on these models, which typically isolate a single feature of QCD and disregard many others, scientists attempt to get a better understanding of the physics of strong interactions. But does this practice make sense? Is it justified to use these models for the purposes at hand? Interestingly, these models do not even provide an accurate description of the mass spectrum of protons, neutrons and pions and their lowest lying excitations well - despite several adjustable parameters. And yet, the models are heavily used. I'll argue that a qualitative story, which establishes an explanatory link between the fundamental theory and a model, plays an important role in model acceptance in these cases. (shrink)

Most scientific models are not physical objects, and this raises important questions. What sort of entity are models, what is truth in a model, and how do we learn about models? In this paper I argue that models share important aspects in common with literary fiction, and that therefore theories of fiction can be brought to bear on these questions. In particular, I argue that the pretence theory as developed by Walton (1990, Mimesis as make-believe: on (...) the foundations of the representational arts. Harvard University Press, Cambridge/MA) has the resources to answer these questions. I introduce this account, outline the answers that it offers, and develop a general picture of scientific modelling based on it. (shrink)

We discuss potential biorisks from large language models (LLMs). AI assistants based on LLMs such as ChatGPT have been shown to significantly reduce barriers to entry for actors wishing to synthesize dangerous, potentially novel pathogens and chemical weapons. The harms from deploying such bioagents could be further magnified by AI-assisted misinformation. We endorse several policy responses to these dangers, including prerelease evaluations of biomedical AIs by subject-matter experts, enhanced surveillance and lab screening procedures, restrictions on AI training data, and (...) access controls on biomedical AI. We conclude with a suggestion about future research directions in bioethics. (shrink)

I argue that ML models used in science function as highly idealized toy models. If we treat ML models as a type of highly idealized toy model, then we can deploy standard representational and epistemic strategies from the toy model literature to explain why ML models can still provide epistemic success despite their lack of similarity to their targets.

Reference models of the earth’s interior play an important role in the acquisition of knowledge about the earth’s interior and the earth as a whole. Such models are used as a sort of standard reference against which data are compared. I argue that the use of reference models merits more attention than it has gotten so far in the literature on models, for it is an example of a method of doing science that has a long (...) and significant history, and a study of reference models could increase our understanding of this methodology. (shrink)

I argue against an account of scientific representation suggested by the semantic, or structuralist, conception of scientific theories. Proponents of this conception often employ the term “model” to refer to bare “structures”, which naturally leads them to attempt to characterize the relation between models and reality as a purely structural one. I argue instead that scientific models are typically “representations”, in the pragmatist sense of the term: they are inherently intended for specific phenomena. Therefore in general scientific (...) class='Hi'>models are not (merely) structures. I then explore some consequences of this pragmatist account of representation, and argue that it sheds light upon the distinction between theories and models. I finish by briefly addressing some critical comments due to Bas Van Fraassen. (shrink)

Thirty years after the conference that gave rise to The Structure of Scientific Theories, there is renewed interest in the nature of theories and models. However, certain crucial issues from thirty years ago are reprised in current discussions; specifically: whether the diversity of models in the science can be captured by some unitary account; and whether the temporal dimension of scientific practice can be represented by such an account. After reviewing recent developments we suggest that these issues can (...) be accommodated within the partial structures formulation of the semantic or model-theoretic approach. (shrink)

Boolean-valued models generalize classical two-valued models by allowing arbitrary complete Boolean algebras as value ranges. The goal of my dissertation is to study Boolean-valued models and explore their philosophical and mathematical applications.In Chapter 1, I build a robust theory of first-order Boolean-valued models that parallels the existing theory of two-valued models. I develop essential model-theoretic notions like “Boolean-valuation,” “diagram,” and “elementary diagram,” and prove a series of theorems on Boolean-valued models, including the (strengthened) Soundness (...) and Completeness Theorem, the Löwenheim–Skolem Theorems, the Elementary Chain Theorem, and many more.Chapter 2 gives an example of a philosophical application of Boolean-valued models. I apply Boolean-valued models to the language of mereology to model indeterminacy in the parthood relation. I argue that Boolean-valued semantics is the best degree-theoretic semantics for the language of mereology. In particular, it trumps the well-known alternative—fuzzy-valued semantics. I also show that, contrary to what many have argued, indeterminacy in parthood entails neither indeterminacy in existence nor indeterminacy in identity, though being compatible with both.Chapter 3 (joint work with Bokai Yao) gives an example of a mathematical application of Boolean-valued models. Scott and Solovay famously used Boolean-valued models on set theory to obtain relative consistency results. In Chapter 3, I investigate two ways of extending the Scott–Solovay construction to set theory with urelements. I argue that the standard way of extending the construction faces a serious problem, and offer a new way that is free from the problem.Abstract prepared by Xinhe Wu.E-mail: [email protected]. (shrink)

A different way of thinking about how the sciences are organized is suggested by the use of cross‐disciplinary computational methods as the organizing unit of science, here called computational templates. The structure of computational models is articulated using the concepts of construction assumptions and correction sets. The existence of these features indicates that certain conventionalist views are incorrect, in particular it suggests that computational models come with an interpretation that cannot be removed as well as a prior justification. (...) A form of selective realism is described which denies that one can simply read the ontological commitments from the theory itself. (shrink)

In a series of papers, 137–158; 1994, Midwest Studies in Philosophy, 23, 61–74, 1999) Fine develops his hylomorphic theory of embodiments. In this article, we supply a formal semantics for this theory that is adequate to the principles laid down for it in. In Section 1, we lay out the theory of embodiments as Fine presents it. In Section 2, we argue on Cantorian grounds that the theory needs to be stabilized, and sketch some ways forward, discussing various choice points (...) in modeling the view. In Section 3, we develop a formal semantics for the theory of embodiments by constructing embodiments in stages and restricting the domain of the second-order quantifiers. In Section 4 we give a few illustrative examples to show how the models deliver Finean hylomorphic consequences. In Section 5, we prove that Fine’s principles are sound with respect to this semantics. In Section 6 we present some inexpressibility results concerning Fine’s various notions of parthood and show that in our formal semantics these notions are all expressible using a single mereological primitive. In Section 7, we prove several mereological results stemming from the model theory, showing that the mereology is surprisingly robust. In Section 8, we draw some philosophical lessons from the formal semantics, and in particular respond to Koslicki’s main objection to Fine’s theory. In the appendix we present proofs of the inexpressibility results of Section 6. (shrink)

We construct a variety of inner models exhibiting features usually obtained by forcing over universes with large cardinals. For example, if there is a supercompact cardinal, then there is an inner model with a Laver indestructible supercompact cardinal. If there is a supercompact cardinal, then there is an inner model with a supercompact cardinal κ for which 2κ = κ+, another for which 2κ = κ++ and another in which the least strongly compact cardinal is supercompact. If there is (...) a strongly compact cardinal, then there is an inner model with a strongly compact cardinal, for which the measurable cardinals are bounded below it and another inner model W with a strongly compact cardinal κ, such that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${H^{V}_{\kappa^+} \subseteq {\rm HOD}^W}$$\end{document}. Similar facts hold for supercompact, measurable and strongly Ramsey cardinals. If a cardinal is supercompact up to a weakly iterable cardinal, then there is an inner model of the Proper Forcing Axiom and another inner model with a supercompact cardinal in which GCH + V = HOD holds. Under the same hypothesis, there is an inner model with level by level equivalence between strong compactness and supercompactness, and indeed, another in which there is level by level inequivalence between strong compactness and supercompactness. If a cardinal is strongly compact up to a weakly iterable cardinal, then there is an inner model in which the least measurable cardinal is strongly compact. If there is a weakly iterable limit δ of <δ-supercompact cardinals, then there is an inner model with a proper class of Laver-indestructible supercompact cardinals. We describe three general proof methods, which can be used to prove many similar results. (shrink)

In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...) computational neuroscience that creates difficulties for the mechanist project. Carandini and Heeger (Nat Rev Neurosci 13:51–62, 2012) propose that many neural response properties can be understood in terms of canonical neural computations. These are “standard computational modules that apply the same fundamental operations in a variety of contexts.” Importantly, these computations can have numerous biophysical realisations, and so straightforward examination of the mechanisms underlying these computations carries little explanatory weight. Through a comparison between this modelling approach and minimal models in other branches of science, I argue that computational neuroscience frequently employs a distinct explanatory style, namely, efficient coding explanation. Such explanations cannot be assimilated into the mechanistic framework but do bear interesting similarities with evolutionary and optimality explanations elsewhere in biology. (shrink)

It is widely recognized that scientific theories are often associated with strictly inconsistent models, but there is little agreement concerning the epistemic consequences. Some argue that model inconsistency supports a strong perspectivism, according to which claims serving as interpretations of models are inevitably and irreducibly perspectival. Others argue that in at least some cases, inconsistent models can be unified as approximations to a theory with which they are associated, thus undermining this kind of perspectivism. I examine the (...) arguments for perspectivism, and contend that its strong form is defeasible in principle, not merely in special cases. The argument rests on the plausibility of scientific knowledge concerning non-perspectival, dispositional facts about modelled systems. This forms the basis of a novel suggestion regarding how to understand the knowledge these models afford, in terms of a contrastive theory of what-questions. (shrink)

What sort of claims do scientific models make and how do these claims then underwrite empirical successes such as explanations and reliable policy interventions? In this paper I propose answers to these questions for the class of models used throughout the social and biological sciences, namely idealized deductive ones with a causal interpretation. I argue that the two main existing accounts misrepresent how these models are actually used, and propose a new account. *Received July 2006; revised August (...) 2008. †To contact the author, please write to: Department of Philosophy, University of Missouri, St. Louis, 599 Lucas Hall (MC 73), One University Blvd., St. Louis, MO 63121-4400; e-mail: [email protected]. (shrink)

How should biological behaviour be modelled? A relatively new approach is to investigate problems in neuroethology by building physical robot models of biological sensorimotor systems. The explication and justification of this approach are here placed within a framework for describing and comparing models in the behavioural and biological sciences. First, simulation models – the representation of a hypothesis about a target system – are distinguished from several other relationships also termed “modelling” in discussions of scientific explanation. Seven (...) dimensions on which simulation models can differ are defined and distinctions between them discussed: 1. Relevance: whether the model tests and generates hypotheses applicable to biology. 2. Level: the elemental units of the model in the hierarchy from atoms to societies. 3. Generality: the range of biological systems the model can represent. 4. Abstraction: the complexity, relative to the target, or amount of detail included in the model. 5. Structural accuracy: how well the model represents the actual mechanisms underlying the behaviour. 6. Performance match: to what extent the model behaviour matches the target behaviour. 7. Medium: the physical basis by which the model is implemented. No specific position in the space of models thus defined is the only correct one, but a good modelling methodology should be explicit about its position and the justification for that position. It is argued that in building robot models biological relevance is more effective than loose biological inspiration; multiple levels can be integrated; that generality cannot be assumed but might emerge from studying specific instances; abstraction is better done by simplification than idealisation; accuracy can be approached through iterations of complete systems; that the model should be able to match and predict target behaviour; and that a physical medium can have significant advantages. These arguments reflect the view that biological behaviour needs to be studied and modelled in context, that is, in terms of the real problems faced by real animals in real environments. Key Words: animal behaviour; levels; models; neuroethology; realism; robotics; simulation. (shrink)

This paper offers an account of data manipulation in scientific experiments. It will be shown that in many cases raw, unprocessed data is not produced, but rather a form of processed data that will be referred to as a data model. The language of data models will be used to provide a framework within which to understand a recent debate about the status of data and data manipulation. It will be seen that a description in terms of data (...) class='Hi'>models allows one to understand cases in which data acquisition and data manipulation cannot be separated into two independent activities. (shrink)