This paper examines geometrical arguments from Galileo's Mechanics and Two New Sciences to discern the influence of the Aristotelian Mechanical Problems on Galileo's dynamics. A common scientific procedure is found in the Aristotelian author's treatment of the balance and lever and in Galileo's rules concerning motion along inclined planes. This scientific procedure is understood as a development of Eudoxan proportional reasoning, as it was used in Eudoxan astronomy rather than simply as it appears in Euclid's Elements. Topics treated include the (...) significance of the circle in Galileo's demonstrations, the substitution of rectilinear elements for heterogeneous factors like weight and curvilinear distance, and the way in which elements of a motion are used to measure other elements of the same motion. The indirectness of Galileo's proofs, his conception of speed as relative and comparative, and the meaning of his concept of moment all come into clearer focus. Conclusions are drawn about Galilean idealization, and also about the contrast of literal versus figural modes of explanation in Galileo's science. (shrink)

In this paper we present a new framework of idealization in biology. We characterize idealizations as a network of counterfactual and hypothetical conditionals that can exhibit different "degrees of contingency". We use this idea to say that, in departing more or less from the actual world, idealizations can serve numerous epistemic, methodological or heuristic purposes within scientific research. We defend that, in part, this structure explains why idealizations, despite being deformations of reality, are so successful in scientific practice. For illustrative (...) purposes, we provide an example from population genetics, the Wright-Fisher Model. (shrink)

In this paper we present a new framework of idealization in biology. We characterize idealizations as a network of counterfactual and hypothetical conditionals that can exhibit different “degrees of contingency”. We use this idea to say that, in departing more or less from the actual world, idealizations can serve numerous epistemic, methodological or heuristic purposes within scientific research. We defend that, in part, this structure explains why idealizations, despite being deformations of reality, are so successful in scientific practice. For illustrative (...) purposes, we provide an example from population genetics, the Wright-Fisher Model. (shrink)

The guest editors would like to thank the University of Paris and the ENSA Paris-Val de Seine for having provided premises to successfully host the 2018 "Measurement at the Crossroads" conference in Paris.Our thanks extend to our funding sources: the conference was made possible thanks to the generous support of the Institut Humanités, Sciences et Sociétés, the SPHERE laboratory and the Laboratoire Matériaux et Phénomènes Quantiques of the University of Paris, the department of History and Philosophy of Science of the (...) University of Paris, the Laboratoire National de métrologie et d'Essais, and the University of Geneva.We would like to thank the many people who contributed to the organization of... (shrink)

In The Explanatory Dispensability of Idealizations, Sam Baron suggests a possible strategy enabling the indispensability argument to break the symmetry between mathematical claims and idealization assumptions in scientific models. Baron’s distinction between mathematical and non-mathematical idealization, I claim, is in need of a more compelling criterion, because in scientific models idealization assumptions are expressed through mathematical claims. In this paper I argue that this mutual dependence of idealization and mathematics cannot be read in terms of symmetry and that Baron’s non-causal (...) notion of mathematical difference-making is not effective in justifying any symmetry-breaking between mathematics and idealization. The function of making a difference that Baron attributes to mathematics cannot be referred to physical facts, but to the features of quantities, such as step lengths or time intervals taken into account in the models. It appears, indeed, that it does not follow from Baron’s argument that idealizations do not help to carry the explanatory load at least for two reasons: mathematics is not independent of idealizations in modelling and idealizations help mathematics to carry the explanatory load of a model in different degrees. (shrink)

In many applications of physics, boundary conditions have an essential role. The purpose of this paper is to examine from both a historical and philosophical perspective one such boundary condition, namely, the no-slip condition of fluid dynamics. The historical perspective is based on the works of George Stokes and serves as the foundation for the philosophical perspective. It is seen that historically the acceptance of the no-slip condition was problematic. Philosophically, the no-slip condition is interesting since the use of the (...) no-slip condition illustrates nicely the use of scientific models. But more importantly, both the use and justification of the no-slip condition illustrate clearly how theories can holistically approach the world through model construction. Further, since much of the debate over scientific realism occurs in the realm of models, a case is made that an understanding of the role of the no-slip condition has something to offer to this debate. (shrink)

In many applications of physics, boundary conditions have an essential role. The purpose of this paper is to examine from both a historical and philosophical perspective one such boundary condition, namely, the no-slip condition of fluid dynamics. The historical perspective is based on the works of George Stokes and serves as the foundation for the philosophical perspective. It is seen that historically the acceptance of the no-slip condition was problematic. Philosophically, the no-slip condition is interesting since the use of the (...) no-slip condition illustrates nicely the use of scientific models. But more importantly, both the use and justification of the no-slip condition illustrate clearly how theories can holistically approach the world through model construction. Further, since much of the debate over scientific realism occurs in the realm of models, a case is made that an understanding of the role of the no-slip condition has something to offer to this debate. (shrink)

Euclidean geometry, statics, and classical mechanics, being in some sense the simplest physical theories based on a full-fledged mathematical apparatus, are well suited to a historico-philosophical analysis of the way in which a physical theory differs from a purely mathematical theory. Through a series of examples including Newton’s Principia and later forms of mechanics, we will identify the interpretive substructure that connects the mathematical apparatus of the theory to the world of experience. This substructure includes models of experiments, models of (...) measurement, and modular connections with partial theories. It evolves during the life of a theory as physicists learn how to apply it in various contexts. It should nevertheless be regarded as an integral part of a genuine physical theory since the theory would otherwise degenerate into pure mathematics. (shrink)

It is argued that core areas of philosophy can benefit from reflection on cross-disciplinary research (CDR). We start by giving a brief account of CDR, describing its variability and some of the ways in which philosophers can interact with it. We then provide an argument in principle for the conclusion that CDR is philosophically fecund, arguing that since CDR highlights fundamental differences among disciplinary research worldviews, it can be used to motivate new philosophical problems and supply new insights into old (...) problems. We close by providing an argument by example that uses the epistemology of peer disagreement to establish the potential of CDR for core philosophical areas. With this argument, we aim to demonstrate how the complex research contexts that CDR affords can point the way toward important avenues of epistemological research by highlighting potential limitations of key epistemological components, such as peerage and uniqueness. (shrink)

The ‘value-free ideal’ has been called into question for several reasons. It does not include “epistemic values”—viewed as characteristic of ‘good science’—and rejects the so-called ‘contextual’, ‘non-cognitive’ or ‘non-epistemic’ values—all of them personal, moral, or political values. This paper analyzes a possible complementary argument about the dubitable validity of the value-free ideal, specifically focusing on social sciences, with a two-fold strategy. First, it will consider that values are natural facts in a broad or ‘liberal naturalist’ sense and, thus, a legitimate (...) part of those sciences. Second, the paper will not reject the value-free ideal; rather, it will construe this ideal in a special way, not casting values aside in sciences, but bringing them to the table and rationally discussing them. Today’s predominant naturalistic view has tended to ‘naturalize’ values by looking for physicalist explanations for them—a move resisted by defenders of normativism in social sciences. At the same time, a contending ‘liberal naturalist’ stream has emerged, claiming that not all natural entities can be explained by the methods and concepts of physical sciences, and favors a non-materialist naturalism which includes mind, consciousness, meaning and value as fundamental parts of nature that cannot be reduced to matter. Hence, it may be posited that non-epistemic values could be ‘naturally’ included in the field of human sciences. (shrink)

Kripke (Wittgenstein on rules and private language: an elementary exposition. Harvard University Press, Cambridge Mass, 1982 ) rejected a naturalistic dispositional account of meaning (hereafter semantic dispositionalism) in a skeptical argument about rule-following he attributes to Wittgenstein (Philosophical investigation. Basil Blackwell, Oxford, 1958 ). Most philosophers who oppose Kripke’s criticisms of semantic dispositionalism take the stance that the argument proves too much: semantic dispositionalism is similar to much of our respected science in some important aspects, and hence to discard the (...) former would mean to give up the latter, which is obviously wrong. In this paper, I shall discuss and reject a recent defense of Kripke by Kusch (Analysis 65(2):156–163 2005 ; Sceptical guide to meaning and rules: defending Kripke’s Wittgenstein. McGill-Queen’s, London, 2006 ). Kusch attempts to show that semantic dispositionalism differs from the sciences, and consequently, Kripke’s attack can only target semantic dispositionalism, but not the sciences. Specifically, Kusch identifies some important features of the sciences with regard to how it employs idealization and ceteris paribus clauses, and argues that the ways in which semantic dispositionalism uses them are dramatically different. I argue that, upon close examination, the two are more similar than otherwise in each of those features. (shrink)

The semantic view of theoriesis one according to which theoriesare construed as models of their linguisticformulations. The implications of thisview for scientific realism have been little discussed. Contraryto the suggestion of various champions of the semantic view,it is argued that this approach does not makesupport for a plausible scientific realism anyless problematic than it might otherwise be.Though a degree of independence of theory fromlanguage may ensure safety frompitfalls associated with logical empiricism, realism cannot be entertained unless models or (abstractedand/or idealized) (...) aspects thereof are spelled out in terms of linguistic formulations (such as mathematical equations),which can be interpreted in terms of correspondencewith the world. The putative advantage of thesemantic approach – its linguistic independence – isthus of no help to the realist. I consider recent treatmentsof the model-theoretic view (Suppe, Giere, Smith), and find that although some of these accounts harbour the promiseof realism, this promise is deceptive. (shrink)

This paper defends the viability of de-idealization strategies in economic modeling against recent criticism. De-idealization occurs when an idealized assumption of a theoretical model is replaced with a more realistic one. Recently, some scholars have raised objections against the possibility or fruitfulness of de-idealizing economic models, suggesting that economists do not employ this kind of strategy. We present a detailed case study from the theory of industrial organization, discussing three different models, two of which can be construed as de-idealized versions (...) of the first (the so-called Bertrand model of oligopoly). We conclude that recent pessimism about de-idealization in economics is largely unfounded, and that de-idealization strategies are not only possible but also widely employed in economics. (shrink)

There is no denying the Central Dogma’s impact on the biological sciences. Since the Dogma’s formulation by Francis Crick in 1958, however, many have debated the Dogma’s empirical adequacy. My aim is to move beyond these discussions, and instead consider the Central Dogma’s significance to contemporary biological practice. To do this, I consider four distinct approaches for determining the non-descriptive methodological significance of a scientific principle. I argue that these approaches fail to vindicate the Central Dogma, and that, under many (...) of these approaches, the Dogma amounts to a triviality. (shrink)

On the relation between experiment and thought experiment in the natural sciences. To understand the reciprocal autonomy and complementarity of thought and real experiment, it is necessary to distinguish between a ‘positive’ (empirical or formal) and a transcendental perspective. Empirically and formally, real and thought experiments are indistinguishable. However, from a reflexive-transcendental viewpoint thought experiment is at the same time irreducible and complementary to real experiment. This is due to the fact that the hypothetical-anticipatory moment is in principle irreducible to (...) physical reality—even though it refers to physical reality and is bound with the empirical use of our understanding. The presence of counterfactuals is the condition of the possibility for thought experiments to become in principle real ones, by means of a series of technical realisations that gradually approximate the idealisations that they contain. (shrink)

I discuss how modern cosmology illustrates under-determination of theoretical hypotheses by data, in ways that are different from most philosophical discussions. I emphasise cosmology's concern with what data could in principle be collected by a single observer ; and I give a broadly sceptical discussion of cosmology's appeal to the cosmological principle as a way of breaking the under-determination.I confine most of the discussion to the history of the observable universe from about one second after the Big Bang, as described (...) by the mainstream cosmological model: in effect, what cosmologists in the early 1970s dubbed the ‘standard model’, as elaborated since then. But in the closing Section 4, I broach some questions about times earlier than one second. (shrink)

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

Theories often run into paradoxes. Some of these are outright contradictions, sending the would-be champions of the theory back to the drawing board. Others are paradoxical in the sense of being bizarre and unexpected. The latter are sometimes mistakenly thought to be instances of the former. That is, they are thought to be more than merely weird; they are mistakenly thought to be self-refuting. Showing that they are not self-contradictory but merely a surprise is often a challenge. Notions of explanation (...) and understanding are often at issue. For instance, we might explain—or explain away—a paradox by invoking some mechanism provided by the theory and showing how it does not really lead to a logically incoherent .. (shrink)

Berkeley, Newton, Explanation, and Causation -/- I argue in this paper that Berkeley’s conception of natural law explanations, which echoes Newton’s, fails to solve a fundamental problem, which I label “explanatory asymmetry"; that the model of explanation Berkeley uses fails to distinguish between explanations and justifications, particularly since Berkeley denies real (efficient causes) in non-minded nature. At the end I suggest Berkeley might endorse a notion of understanding, say in astronomy or mechanics, which could be distinguished from explanation.

In the First of the Three Dialogues, Berkeley’s Hylas, responding to Philonous’s question whether extension and motion are separable from secondary qualities, says: What! Is it not an easy matter, to consider extension and motion by themselves,... Pray how do the mathematicians treat of them?

Berkeley in his Introduction to the Principles of Human knowledge uses geometrical examples to illustrate a way of generating “universal ideas,” which allegedly account for the existence of general terms. In doing proofs we might, for example, selectively attend to the triangular shape of a diagram. Presumably what we prove using just that property applies to all triangles.I contend, rather, that given Berkeley’s view of extension, no Euclidean triangles exist to attend to. Rather proof, as Berkeley would normally assume, requires (...) idealizing diagrams; treating them as if they obeyed Euclidean constraints. This convention solves the problem of representative generalization. View HTML Send article to KindleTo send this article to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle. Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply. Find out more about the Kindle Personal Document Service.Berkeley and Proof in GeometryVolume 51, Issue 3RICHARD J. BROOK DOI: https://doi.org/10.1017/S0012217312000686Your Kindle email address Please provide your Kindle [email protected]@kindle.com Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Send article to Dropbox To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to Dropbox. Berkeley and Proof in GeometryVolume 51, Issue 3RICHARD J. BROOK DOI: https://doi.org/10.1017/S0012217312000686Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Send article to Google Drive To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to Google Drive. Berkeley and Proof in GeometryVolume 51, Issue 3RICHARD J. BROOK DOI: https://doi.org/10.1017/S0012217312000686Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Export citation Request permission. (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)

The fact that the same equations or mathematical models reappear in the descriptions of what are otherwise disparate physical systems can be seen as yet another manifestation of Wigner's “unreasonable effectiveness of mathematics.” James Clerk Maxwell famously exploited such formal similarities in what he called the “method of physical analogy.” Both Maxwell and Hermann von Helmholtz appealed to the physical analogies between electromagnetism and hydrodynamics in their development of these theories. I argue that a closer historical examination of the different (...) ways in which Maxwell and Helmholtz each deployed this analogy gives further insight into debates about the representational and explanatory power of mathematical models. (shrink)

In semiclassical mechanics one finds explanations of quantum phenomena that appeal to classical structures. These explanations are prima facie problematic insofar as the classical structures they appeal to do not exist. Here I defend the view that fictional structures can be genuinely explanatory by introducing a model-based account of scientific explanation. Applying this framework to the semiclassical phenomenon of wavefunction scarring, I argue that not only can the fictional classical trajectories explain certain aspects of this quantum phenomenon, but also that (...) an explanation that does not make reference to these classical structures is, in a certain sense, deficient. (shrink)

In The Explanatory Dispensability of Idealizations, Sam Baron suggests a possible strategy enabling the indispensability argument to break the symmetry between mathematical claims and idealization assumptions in scientific models. Baron’s distinction between mathematical and non-mathematical idealization, I claim, is in need of a more compelling criterion, because in scientific models idealization assumptions are expressed through mathematical claims. In this paper I argue that this mutual dependence of idealization and mathematics cannot be read in terms of symmetry and that Baron’s non-causal (...) notion of mathematical difference-making is not effective in justifying any symmetry-breaking between mathematics and idealization. The function of making a difference that Baron attributes to mathematics cannot be referred to physical facts, but to the features of quantities, such as step lengths or time intervals taken into account in the models. It appears, indeed, that it does not follow from Baron’s argument that idealizations do not help to carry the explanatory load at least for two reasons: mathematics is not independent of idealizations in modelling and idealizations help mathematics to carry the explanatory load of a model in different degrees. (shrink)

This article illustrates how during early modernity Italian and Dutch cultures and particularly artistic traditions contributed differently to both the theoretical and practical developments of science. To achieve this goal, it will firstly compare the two forms of detextualization of space operated by Italian artists and by Dutch artists. Finally, it will indicate how each detextualization allowed for the development within the science of the mathematical tradition by the Italian Culture and the experimental tradition by the Dutch culture.

Richard Levins’s (Am Sci 54(4):421–431, 1966) paper sets a landmark for the significance of scientific model-making in biology. Colombo and Palacios (Biol Philos 36(5):1–26. 10.1007/s10539-021-09818-x, 2021) have recently built their critique of the explanatory power of the Free Energy Principle on Levins’s insight into the relationship between generality, realism, and precision. This paper addresses the issue of the plausibility of biological explanations that are grounded in the Free Energy Principle (FEP) and deals with the question of the realist fortitude of (...) FEP’s theoretical framework. It indicates that what is required for establishing the plausibility of the explanation of a target system given a model of that system is the dosage or the harmony between the generality and accuracy of explanatory models. This would also provide a basis for seeing how scientific realism could be a viable option with respect to FEP. (shrink)

N. Bostrom’s simulation argument and two additional assumptions imply that we likely live in a computer simulation. The argument is based upon the following assumption about the workings of realistic brain simulations: The hardware of a computer on which a brain simulation is run bears a close analogy to the brain itself. To inquire whether this is so, I analyze how computer simulations trace processes in their targets. I describe simulations as fictional, mathematical, pictorial, and material models. Even though the (...) computer hardware does provide a material model of the target, this does not suffice to underwrite the simulation argument because the ways in which parts of the computer hardware interact during simulations do not resemble the ways in which neurons interact in the brain. Further, there are computer simulations of all kinds of systems, and it would be unreasonable to infer that some computers display consciousness just because they simulate brains rather than, say, galaxies. (shrink)

This paper discusses a conception of physics as a collection of theories that, from a logical point of view, is inconsistent. It is argued that this logical conception of the relations between physical theories is too crude. Mathematical subtleties allow for a much more nuanced and sophisticated understanding of the relations between different physical theories.

This paper examines contemporary attempts to explicate the explanatory role of mathematics in the physical sciences. Most such approaches involve developing so-called mapping accounts of the relationships between the physical world and mathematical structures. The paper argues that the use of idealizations in physical theorizing poses serious difficulties for such mapping accounts. A new approach to the applicability of mathematics is proposed.

Infinite idealizations appear in our best scientific explanations of phase transitions. This is thought by some to be paradoxical. In this paper I connect the existing literature on the phase transition paradox to work on the concept of indispensability, which arises in discussions of realism and anti-realism within the philosophy of science and the philosophy of mathematics. I formulate a version of the phase transition paradox based on the idea that infinite idealizations are explanatorily indispensable to our best science, and (...) so ought to attract a realist attitude. I go on to offer a solution to the paradox by drawing a distinction between two types of indispensability: constructive and substantive indispensability. I argue that infinite idealizations are constructively indispensable to explanations of phase transitions, but not substantively indispensable. This helps to resolve the paradox, I maintain, since realist commitment tracks substantive, and not constructive, indispensability. (shrink)

Bogen and Woodward’s distinction between data and phenomena raises the need to understand the structure of the data-to-phenomena and theory-to-phenomena inferences. I suggest that one way to study the structure of these inferences is to analyze the role of the assumptions involved in the inferences: What kind of assumptions are they? How do these assumptions contribute to the practice of identifying phenomena? In this paper, using examples from atmospheric dynamics, I develop an account of the practice of identifying the target (...) in the data-to-phenomena and theory-to-phenomena inferences in which assumptions about spatiotemporal scales play a central role in the identification of parameters that describe the target system. I also argue that these assumptions are not only empirical but they are also idealizing and abstracting. I conclude the paper with a reflection on the role of idealizations in modeling. (shrink)

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

This paper examines the process of modelling a complex empirical phenomenon in modern astrophysics: extended extragalactic radio sources. I show that modelling is done piecemeal, addressing selected striking or puzzling features of that phenomenon separately and individually. The result is various independent and separate sub-models concerned only with limited aspects of the same phenomenon. Because the sub-models represent features of the same physical phenomenon, they need to be reasonably consistent with each other - a criterion not always fully adhered to (...) - and there needs to be a way to conceptually `re-unite' the sub-models to form an overall-model. Visualisation, that is, supplying a concrete interpretation of abstract, theoretical sub-models, aids this modelling process. My case study further endorses the view that modelling is `work in progress', i.e. a form of developing knowledge whereby models represent, not replicate, a phenomenon. (shrink)

Although Bayesian methods are widely used in phylogenetic systematics today, the foundations of this methodology are still debated among both biologists and philosophers. The Bayesian approach to phylogenetic inference requires the assignment of prior probabilities to phylogenetic trees. As in other applications of Bayesian epistemology, the question of whether there is an objective way to assign these prior probabilities is a contested issue. This paper discusses the strategy of constraining the prior probabilities of phylogenetic trees by means of the Principal (...) Principle. In particular, I discuss a proposal due to Velasco (Biol Philos 23:455–473, 2008) of assigning prior probabilities to tree topologies based on the Yule process. By invoking the Principal Principle I argue that prior probabilities of tree topologies should rather be assigned a weighted mixture of probability distributions based on Pinelis’ (P Roy Soc Lond B Bio 270:1425–1431, 2003) multi-rate branching process including both the Yule distribution and the uniform distribution. However, I argue that this solves the problem of the priors of phylogenetic trees only in a weak form. (shrink)

This paper addresses the methodological problem of analysing what it is to explain observed behaviours of engineered computing systems, focusing on the crucial role that abstraction and idealization play in explanations of both correct and incorrect BECS. First, it is argued that an understanding of explanatory requests about observed miscomputations crucially involves reference to the rich background afforded by hierarchies of functional specifications. Second, many explanations concerning incorrect BECS are found to abstract away from descriptions of physical components and processes (...) of computing systems that one finds below the logic circuit and gate layer of functional specification hierarchies. Third, model-based explanations of both correct and incorrect BECS that are provided in the framework of formal verification methods often involve idealizations. Moreover, a distinction between restrictive and permissive idealizations is introduced and their roles in BECS explanations are analysed. (shrink)

Questions concerning the epistemological status of computer science are, in this paper, answered from the point of view of the formal verification framework. State space reduction techniques adopted to simplify computational models in model checking are analysed in terms of Aristotelian abstractions and Galilean idealizations characterizing the inquiry of empirical systems. Methodological considerations drawn here are employed to argue in favour of the scientific understanding of computer science as a discipline. Specifically, reduced models gained by Dataion are acknowledged as Aristotelian (...) abstractions that include only data which are sufficient to examine the interested executions. The present study highlights how the need to maximize incompatible properties is at the basis of both Abstraction Refinement, the process of generating a cascade of computational models to achieve a balance between simplicity and informativeness, and the Multiple Model Idealization approach in biology. Finally, fairness constraints, imposed to computational models to allow fair behaviours only, are defined as ceteris paribus conditions under which temporal formulas, formalizing software requirements, acquire the status of law-like statements about the software systems executions. (shrink)

The Galilean explanatory style is characterized by the search for the underlying structure of phenomena, the positing of "deep" explanatory principles, and a view of the relation between theory and data, on which the search for "crucial data" is of primary importance. In this paper, I trace the dynamics of adopting the Galilean style, focusing on the science of episodic memory. I argue that memory systems, such as episodic and semantic memory, were posited as underlying competences producing the observable phenomena (...) of memory. Considered in idealized isolation from other systems, episodic memory was taken to underlay the ability of individuals to remember events from their personal past. Yet, in reality, memory systems regularly interact, standing in many-to-many relations to actual memory tasks and experiences. Upon this backdrop, I explore a puzzle about the increasing prominence of the notion of autonoetic consciousness in Tulving's theory of episodic memory. I argue that, contrary to widespread belief, the prominence is not best explained by the purported essential link between autonoetic consciousness and episodic memory. Rather, it is explained by the fact that autonoetic consciousness, hypothesized to uniquely accompany episodic retrieval, was considered a source of crucial data, predictable only from theories positing a functionally distinct episodic memory system. However, with the emergence of a new generation of theories, positing wider memory systems for remembering and imagination, the question of the relation between episodic memory and autonoetic consciousness has been reopened. This creates a pressing need for de-idealization, triggering a new search for crucial data. (shrink)

This paper calls into question one fundamental claim at the basis of an alleged puzzle for veritistic accounts of the value of idealized models: the claim that idealized models cannot be veridical representations of the world. Catherine Elgin has argued that the value of idealized models can only be explained if we construe them as exemplars, which do not represent the world. I argue that Elgin’s proposal is problematic and cannot accommodate central cases of idealization. Nevertheless, there is value in (...) Elgin’s proposal. I rescue her notion of selectiveness in exemplification and incorporate it within a revised account of representation. I provide independent motivation in favour of a form of veritism, which motivates a revision of Elgin’s case against it. I argue that an account based on selective representation has the resources to rescue veritism from the problems raised by Elgin. In the proposal I advance, idealized models are literally veridical representations of the world. (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)

Can social phenomena be understood by analyzing their parts? Contemporary economic theory often assumes that they can. The methodology of constructing models which trace the behavior of perfectly rational agents in idealized environments rests on the premise that such models, while restricted, help us isolate tendencies, that is, the stable separate effects of economic causes that can be used to explain and predict economic phenomena. In this paper, I question both the claim that models in economics supply claims about tendencies (...) and also the view that economics, when successful, necessarily follows this method. When economics licenses successful policy interventions, as it did in the case of the Federal Communications Commission spectrum auctions, its method is not to study tendencies but rather to study the phenomenon as a whole. Key Words: economic models • tendencies • economic experiments • policy making • John Stuart Mill. (shrink)

In the recent literature on causal and non-causal scientific explanations, there is an intuitive assumption according to which an explanation is non-causal by virtue of being abstract. In this context, to be ‘abstract’ means that the explanans in question leaves out many or almost all causal microphysical details of the target system. After motivating this assumption, we argue that the abstractness assumption, in placing the abstract and the causal character of an explanation in tension, is misguided in ways that are (...) independent of which view of causation or causal explanation one takes to be most accurate. On major accounts of causation, as well as on major accounts of causal explanation, the abstractness of an explanation is not sufficient for it being non-causal. That is, explanations are not non-causal by dint of being abstract. (shrink)