Leading philosophical accounts presume that Thomas H. Morgan’s transmission theory can be understood independently of experimental practices. Experimentation is taken to be relevant to confirming, rather than interpreting, the transmission theory. But the construction of Morgan’s theory went hand in hand with the reconstruction of the chief experimental object, the model organism Drosophila melanogaster . This raises an important question: when a theory is constructed to account for phenomena in carefully controlled laboratory settings, what knowledge, if any, indicates the theory’s (...) relevance to phenomena outside highly controlled settings? The answer, I argue, is found within the procedural knowledge embedded within laboratory practice. †To contact the author, please write to: Minnesota Center for Philosophy of Science, University of Minnesota, Department of Philosophy, 831 Heller Hall, 271 19th Ave., University of Minnesota, Minneapolis, MN 55455‐0310; e‐mail: [email protected]. (shrink)

A computer simulation runs a model generating a phenomenon under investigation. For the simulation to be explanatory, the model has to be explanatory. The model must be isomorphic to the natural system that realizes the phenomenon. This paper elaborates the method of assessing a simulation's explanatory power. Then it illustrates the method by applying it to two simulations in game theory. The first is Brian Skyrms's (1990) simulation of interactive deliberations. It is intended to explain the emergence of a Nash (...) equilibrium in a noncooperative game. The second is Skyrms's (2004) simulation of the evolution of cooperation. It is intended to explain cooperation in assurance games. The final section suggests ways of enhancing the explanatory power of these simulations. (shrink)

In this paper I propose an account of representation for scientific models based on Kendall Walton’s ‘make-believe’ theory of representation in art. I first set out the problem of scientific representation and respond to a recent argument due to Craig Callender and Jonathan Cohen, which aims to show that the problem may be easily dismissed. I then introduce my account of models as props in games of make-believe and show how it offers a solution to the problem. Finally, I demonstrate (...) an important advantage my account has over other theories of scientific representation. All existing theories analyse scientific representation in terms of relations, such as similarity or denotation. By contrast, my account does not take representation in modelling to be essentially relational. For this reason, it can accommodate a group of models often ignored in discussions of scientific representation, namely models which are representational but which represent no actual object. (shrink)

Philosophical interpretations of theories generally presuppose that a theory can be presented as a consistent mathematical formulation that is interpreted through models. Algebraic quantum field theory (AQFT) can fit this interpretative model. However, standard Lagrangian quantum field theory (LQFT), as well as quantum electrodynamics and nuclear physics, resists recasting along such formal lines. The difference has a distinct bearing on ontological issues. AQFT does not treat particle interactions or the standard model. This paper develops a framework and methodology for interpreting (...) such informal theories as LQFT and the standard model. We begin by summarizing two minimal epistemological interpretation of non-relativistic quantum mechanics (NRQM): Bohrian semantics, which focuses on communicables; and quantum information theory, which focuses on the algebra of local observables. Schwinger's development of quantum field theory supplies a unique path from NRQM to QFT, where each step is conceptually anchored in local measurements. LQFT and the standard model rely on postulates that go beyond the limits set by AQFT and Schwinger's anabatic methodology. The particle ontology of the standard model is clarified by regarding the standard model as an informal modular theory with a limited range of validity. (shrink)

In this paper, I propose a new way to integrate historical accounts of social interaction in scientific practice with philosophical examination of scientific knowledge. The relation between descriptive accounts of scientific practice, on the one hand, and normative accounts of scientific knowledge, on the other, is a vexed one. This vexatiousness is one instance of the gap between normative and descriptive domains. The general problem of the normative/descriptive divide takes striking and problematic form in the case of social aspects of (...) scientific knowledge. With respect to this issue, history and philosophy of science appear starkly incompatible. I show how this dualism can be overcome, drawing on social action theory and the recent history of cellular immunology. (shrink)

I extract some philosophical morals from some aspects of Lagrangian mechanics. One main moral concerns methodology: Lagrangian mechanics provides a level of description of phenomena which has been largely ignored by philosophers, since it falls between their accustomed levels---``laws of nature'' and ``models''. Another main moral concerns ontology: the ontology of Lagrangian mechanics is both more subtle and more problematic than philosophers often realize. The treatment of Lagrangian mechanics provides an introduction to the subject for philosophers, and is technically elementary. (...) In particular, it is confined to systems with a finite number of degrees of freedom, and for the most part eschews modern geometry. (shrink)

This paper describes an alternative to the common view that explanation in the special sciences involves subsumption under laws. According to this alternative, whether or not a generalization can be used to explain has to do with whether it is invariant rather than with whether it is lawful. A generalization is invariant if it is stable or robust in the sense that it would continue to hold under a relevant if it is stable or robust in the sense that it (...) would continue to hold under a relevant class of changes. Unlike lawfulness, invariance comes in degrees and has other features that are well suited to capture the characteristics of explanatory generalizations in the special sciences. For example, a generalization can be invariant even if it has exceptions or holds only over a limited spatio-temporal interval. The notion of invariance can be used to resolve a number of dilemmas that arise in standard treatments of explanatory generalizations in the special sciences. (shrink)

This paper gives a critical evaluation of the philosophical presuppositions and implications of two current schools in the sociology of knowledge: the Strong Programme of Bloor and Barnes; and the Constructivism of Latour and Knorr-Cetina. Bloor's arguments for his externalist symmetry thesis (i.e., scientific beliefs must always be explained by social factors) are found to be incoherent or inconclusive. At best, they suggest a Weak Programme of the sociology of science: when theoretical preferences in a scientific community, SC, are first (...) internally explained by appealing to the evidence, e, and the standards or values, V, accepted in SC, then a sociologist may sometimes step in to explain why e and V were accepted in SC. Latour's story about the social construction of facts in scientific laboratories is found to be misleading or incredible. The idea that scientific reality is an artifact turns out to have some interesting affinities with classical pragmatism, instrumentalism, phenomenology, and internal realism. However, the constructivist account of theoretical entities in terms of negotiation and social consensus is less plausible than the alternative realist story which explains consensus by the preexistence of mind-independent real entities. The author concludes that critical scientific realism, developed with the concept of truthlikeness, is compatible with the thesis that scientific beliefs or knowledge claims may be relative to various types of cognitive and practical interests. However, the realist denies, with good reasons, the stronger type of relativism which takes reality and truth to be relative to persons, groups, or social interests. (shrink)

In this paper, I explore the relationship between epistemic rationality and instrumental rationality, and I attempt to delineate their respective roles in typical instances of theoretical reasoning. My primary concern is with the instrumentalist conception of epistemic rationality: the view that epistemic rationality is simply a species of instrumental rationality, viz. instrumental rationality in the service of one's cognitive or epistemic goals. After sketching the relevance of the instrumentalist conception to debates over naturalism and 'the ethics of belief', I argue (...) that, despite enjoying considerable popularity among both epistemologists and philosophers of science, it is ultimately indefensible. Having thus argued for the distinctness of epistemic and instrumental rationality, I attempt to clarify the role played by each in typical instances of theoretical reasoning. I suggest that being theoretically rational--that is, being proficient with respect to theoretical reasoning--is best construed as a hybrid virtue, inasmuch as it involves manifesting sensitivity to two very different kinds of reasons. (shrink)

Accounts of the relation between theories and models in biology concentrate on mathematical models. In this paper I consider the dual role of models as representations of natural systems and as a material basis for theorizing. In order to explicate the dual role, I develop the concept of a remnant model, a material entity made from parts of the natural system(s) under study. I present a case study of an important but neglected naturalist, Joseph Grinnell, to illustrate the extent to (...) which mundane practices in a museum setting constitute theorizing. I speculate that historical and sociological analyses of institutions can play a specific role in the philosophical analysis of model-building strategies. (shrink)

Paul Thompson, John Beatty, and Elisabeth Lloyd argue that attempts to resolve certain conceptual issues within evolutionary biology have failed because of a general adherence to the received view of scientific theories. They maintain that such issues can be clarified and resolved when one adopts a semantic approach to theories. In this paper, I argue that such conceptual issues are just as problematic on a semantic approach. Such issues arise from the complexity involved in providing formal accounts of theoretical laws (...) and scientific explanations. That complexity is due to empirical and pragmatic considerations, not one's adherence to a particular formal approach to theories. This analysis raises a broader question. How can any formal account properly represent the complex nature of empirical phenomena? (shrink)

Though many agree that we need to account for the role that social factors play in inquiry, developing a viable social epistemology has proved to be difficult. According to Longino, it is the processes that make inquiry possible that are aptly described as "social," for they require a number of people to sustain them. These processes, she claims, not only facilitate inquiry, but also ensure that the results of inquiry are more than mere subjective opinions, and thus deserve to be (...) called "knowledge." In this paper, I (a) explain Longino's epistemology, and (b) defend it against charges that have recently been raised by Kitcher, Schmitt, and Solomon. Longino rightly recognizes that not all social factors have the same (adverse) affect on inquiry. She also recommends that we distinguish knowledge from mere opinion by reference to a social standard. (shrink)

Philosophers agree that scientific explanations aim to produce understanding, and that good ones succeed in this aim. But few seriously consider what understanding is, or what the cues are when we have it. If it is a psychological state or process, describing its specific nature is the job of psychological theorizing. This article examines the role of understanding in scientific explanation. It warns that the seductive, phenomenological sense of understanding is often, but mistakenly, viewed as a cue of genuine understanding. (...) The article closes with a discussion of several new paths of research that tie the psychology of scientific explanation to cognate notions of learning, testimony, and understanding. (shrink)

Arguably, there is no substantial, general answer to the question of what makes for the approximate truth of theories. But in one class of cases, the issue seems simply resolved. A wide class of applied dynamical theories can be treated as two-component theories—one component specifying a certain kind of abstract geometrical structure, the other giving empirical application to this structure by claiming that it replicates, subject to arbitrary scaling for units etc., the geometric structure to be found in some real-world (...) dynamical phenomenon. In such a case, a theory is approximately true just if the one geometric structure approximately replicates the other (and if problems remain here, they are problems in geometry, of specifying suitable metric approximation relations, not conceptual problems). This article amplifies and defends this simple approach to approximate truth for dynamical theories. (shrink)

In this paper, a criticism of the traditional theories of approximation and idealization is given as a summary of previous works. After identifying the real purpose and measure of idealization in the practice of science, it is argued that the best way to characterize idealization is not to formulate a logical model – something analogous to Hempel's D-N model for explanation – but to study its different guises in the praxis of science. A case study of it is then made (...) in thermostatistical physics. After a brief sketch of the theories for phase transitions and critical phenomena, I examine the various idealizations that go into the making of models at three difference levels. The intended result is to induce a deeper appreciation of the complexity and fruitfulness of idealization in the praxis of model-building, not to give an abstract theory of it. (shrink)

I present a justification for the intution that more-varied data are more valuable than the same number of less-varied data by showing that the more-varied data help to improve the accuracy of our predictions.

This paper starts with an intuitive notion of representational spaces, which is intended to provide an improved version of Kuhn's concept of paradigms. It then proceeds to study the following topics in terms of this new notion: incommensurability, paradigm change, explanation of anomalies, explanation of regularities, explanation of irregularities, and physical necessity. In the course of the investigation, "representational space" gets clarified and defined. It is envisaged that this new concept should throw light on many issues in the philosophy of (...) science. (shrink)

Most recent philosophical thought about the scientific representation of the world has focused on dyadic relationships between language-like entities and the world, particularly the semantic relationships of reference and truth. Drawing inspiration from diverse sources, I argue that we should focus on the pragmatic activity of representing, so that the basic representational relationship has the form: Scientists use models to represent aspects of the world for specific purposes. Leaving aside the terms "law" and "theory," I distinguish principles, specific conditions, models, (...) hypotheses, and generalizations. I argue that scientists use designated similarities between models and aspects of the world to form both hypotheses and generalizations. (shrink)

A review of the chemical education research literature suggests that the term constructivism is used in two ways: experience-based constructivism and discipline-based constructivism. These two perspectives are examined as an epistemology in relation to the teaching and learning of the concept of idealization in chemistry. It is claimed that experience-based constructivism is powerless to inform the origin of such concepts in chemistry and while discipline-based constructivism can admit such theoretical concepts as idealization it does not offer any unique perspectives that (...) cannot be obtained from other models. Chemical education researchers do not consistently appeal to constructivism as an epistemology or as a teaching/learning perspective and it is shown that, while it draws attention to worthwhile teaching/learning strategies, it cannot be considered as foundational to chemical education research and tends to be used more as an educational label than as an undergirding theory. (shrink)

In this paper, I develop Mauricio Suárez’s distinction between denotation, epistemic representation, and faithful epistemic representation. I then outline an interpretational account of epistemic representation, according to which a vehicle represents a target for a certain user if and only if the user adopts an interpretation of the vehicle in terms of the target, which would allow them to perform valid (but not necessarily sound) surrogative inferences from the model to the system. The main difference between the interpretational conception I (...) defend here and Suárez’s inferential conception is that the interpretational account is a substantial account—interpretation is not just a “symptom” of representation; it is what makes something an epistemic representation of a something else. (shrink)

In this paper the claim that laws of nature are to be understood as claims about what necessarily or reliably happens is disputed. Laws can characterize what happens in a reliable way, but they do not do this easily. We do not have laws for everything occurring in the world, but only for those situations where what happens in nature is represented by a model: models are blueprints for nomological machines, which in turn give rise to laws. An example from (...) economics shows, in particular, how we use--and how we need to use--models to get probabilistic laws. (shrink)

: As a response to the critics of feminist science studies I argue that it is possible to formulate empirical hypotheses about gender ideology in the practice of the physical sciences without (1) reinforcing stereotypes about women and mathematical sciences or (2) assuming at the outset that the area of physics under investigation is methodologically suspect. I will then critically evaluate two case studies of gender ideology in the practice of the physical sciences. The case studies fail to show that (...) gender ideologies have influenced the practice of the physical sciences in a profound way--not because it is impossible to conceive how gender ideologies could influence the practice of the physical sciences even in a profound way--but because they do not provide the right kind of evidence. This, however, leaves open the possibility that future studies might provide such evidence. (shrink)

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

Among theory theorists, it is commonly thought that folk psychological theory is tacitly known. However, folk psychological knowledge has none of the central features of tacit knowledge. But if it is ordinary knowledge, why is it that we have difficulties expressing anything but a handful of folk psychological generalisations? The reason is that our knowledge is of theoretical models and hypotheses, not of universal generalisations. Adopting this alternative view of (scientific) theories, we come to see that, given time and reflection, (...) we can say what we know. (shrink)

I argue against theories that attempt to reduce scientific representation to similarity or isomorphism. These reductive theories aim to radically naturalize the notion of representation, since they treat scientist's purposes and intentions as non-essential to representation. I distinguish between the means and the constituents of representation, and I argue that similarity and isomorphism are common but not universal means of representation. I then present four other arguments to show that similarity and isomorphism are not the constituents of scientific representation. I (...) finish by looking at the prospects for weakened versions of these theories, and I argue that only those that abandon the aim to radically naturalize scientific representation are likely to be successful. (shrink)

Perspectival realism combines two apparently contradictory aspects: the epistemic relativity of perspectives and the mind-independence of realism. This paper examines the prospects for a coherent perspectival realism, taking the literature on scientific representation as a starting point. It is argued that representation involves two types of norms, referred to as norms of relevance and norms of accuracy. Norms of relevance fix the domain of application of a theory and the way it categorises the world, and norms of accuracy give the (...) conditions for the theory to be true. Perspectival realism could be made coherent by taking a realist stance towards one type of norm, and a perspectival stance towards the other, by assuming they are relative to a community. This provides two versions of perspectival realism, called relevance perspectivism and accuracy perspectivism. How each option fares with respect to the challenge of incompatible models is examined. Finally, the prospects of full perspectivism are evaluated. (shrink)

There is a vast literature within philosophy of mind that focuses on artificial intelligence, but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between models and (...) targets are picked out, how modeling inferences are justified, and the metaphysical status of models. (shrink)

The libertarian attribute of Thaler and Sunstein’s nudge theory (Nudge: improving decisions about health, wealth, and happiness. Yale University Press, New Haven, 2008) is one of the most important features for its candidature as a new model for public policy-making. It relies on the reversibility of choices made under the influence of nudging. Since the mind is articulated into two systems, the choice taken by System 1 is always reversible because it can be overridden by the deliberative and corrective role (...) of System 2. This article does not aim to criticise the whole theory of nudge and neither to assess its practical efficacy as a policy-making tool. Rather it intends to show that there are doubts that the specific claim of reversibility is correct for a subset of nudges called “System 1 nudges” (Sunstein in The ethics of influence, Cambridge University Press, Cambridge, 2016). And that therefore, in this case, the libertarian claim seems little justified. The thrust of my argument contests the truth of the main pillar of the libertarian claim, namely the dual-process theory of mind. I will show that even the minimal version of dual reasoning, namely the Type 1 and Type 2 processes proposed by Evans and Stanovich (Perspect Psychol Sci 8(3):223–241, 2013), is weakened by psychological and neural data. (shrink)

The concept of linguistic infinity has had a central role to play in foundational debates within theoretical linguistics since its more formal inception in the mid-twentieth century. The conceptualist tradition, marshalled in by Chomsky and others, holds that infinity is a core explanandum and a link to the formal sciences. Realism/Platonism takes this further to argue that linguistics is in fact a formal science with an abstract ontology. In this paper, I argue that a central misconstrual of formal apparatus of (...) recursive operations such as the set-theoretic operation merge has led to a mathematisation of the object of inquiry, producing a strong analogy with discrete mathematics and especially arithmetic. The main product of this error has been the assumption that natural, like some formal, languages are discretely infinite. I will offer an alternative means of capturing the insights and observations related to this posit in terms of scientific modelling. My chief aim will be to draw from the larger philosophy of science literature in order to offer a position of grammars as models compatible with various foundational interpretations of linguistics while being informed by contemporary ideas on scientific modelling for the natural and social sciences. (shrink)

Numerous articles in top IS journals note as a limitation and lack of generalizability that their findings are specific to a certain type of technology, culture, and so on. We argue that this generalizability concern is about limited scope. The IS literature notes this preference for generalizability as a characteristic of good science and it is sometimes confused with statistical generalizability. We argue that such generalizability can be in conflict with explanation or prediction accuracy. An increase in scope can decrease (...) explanation or prediction accuracy. Thus, in sciences such as cancer research, where explanation and prediction accuracy are highly valued, the cancer accounts have become increasingly narrower. IS thinking has not yet benefitted from these considerations. Whether generalizability is valued should be linked with the research aims. If the aim is practical applicability through explanation or prediction accuracy, then “limited” generalizability could be a strength rather than a weakness. (shrink)

Microbial model systems have a long history of fruitful use in fields that include evolution and ecology. In order to develop further insight into modelling practice, we examine how the competitive exclusion and coexistence of competing species have been modelled mathematically and materially over the course of a long research history. In particular, we investigate how microbial models of these dynamics interact with mathematical or computational models of the same phenomena. Our cases illuminate the ways in which microbial systems and (...) equations work as models, and what happens when they generate inconsistent findings about shared targets. We reveal an iterative strategy of comparative modelling in different media, and suggest reasons why microbial models have a special degree of epistemic tractability in multimodel inquiry. (shrink)

After a brief presentation of Feynman diagrams, we criticizise the idea that Feynman diagrams can be considered to be pictures or depictions of actual physical processes. We then show that the best interpretation of the role they play in quantum field theory and quantum electrodynamics is captured by Hughes' Denotation, Deduction and Interpretation theory of models, where “models” are to be interpreted as inferential, non-representational devices constructed in given social contexts by the community of physicists.

I argue that the best interpretation of the general theory of relativity has need of a causal entity, and causal structure that is not reducible to light cone structure. I suggest that this causal interpretation of GTR helps defeat a key premise in one of the most popular arguments for causal reductionism, viz., the argument from physics.

This Ph.D. thesis provides a pilosophical account of the structure of the evolutionary synthesis of the 1930s and 40s. The first, more historical part analyses how classical genetics came to be integrated into evolutionary thinking, highlighting in particular the importance of chromosomal mapping of Drosophila strains collected in the wild by Dobzansky, but also the work of Goldschmidt, Sumners, Timofeeff-Ressovsky and others. The second, more philosophical part attempts to answer the question wherein the unity of the synthesis consisted. I argue (...) that it exemplifies a weak of form of explanatory unification. (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)

Idealization and abstraction are central concepts in the philosophy of science and in science itself. My goal in this paper is suggest an account of these concepts, building on and refining an existing view due to Jones Idealization XII: correcting the model. Idealization and abstraction in the sciences, vol 86. Rodopi, Amsterdam, pp 173–217, 2005) and Godfrey-Smith Mapping the future of biology: evolving concepts and theories. Springer, Berlin, 2009). On this line of thought, abstraction—which I call, for reasons to be (...) explained, abstractness—involves the omission of detail, whereas idealization consists in a deliberate mismatch between a description and the world. I will suggest that while the core idea underlying these authors’ view is correct, they make several assumptions and stipulations that are best avoided. For one thing, they tie abstractness too close to truth. For another, they do not allow sufficient room to the difference between idealization and error. Taking these points into account leads to a refined account of the distinction, in which abstractness is seen in terms of relative richness of detail, and idealization is seen as closely connected with the knowledge and intentions of idealizers. I lay out these accounts in turn, and then discuss the relationship between the two concepts, and several other upshots of the present way of construing the distinction. (shrink)

The inclusion of the practice of “developing and using models” in the Framework for K-12 Science Education and in the Next Generation Science Standards provides an opportunity for educators to examine the role this practice plays in science and how it can be leveraged in a science classroom. Drawing on conceptions of models in the philosophy of science, we bring forward an agent-based account of models and discuss the implications of this view for enacting modeling in science classrooms. Models, according (...) to this account, can only be understood with respect to the aims and intentions of a cognitive agent, not solely in terms of how they represent phenomena in the world. We present this contrast as a heuristic—models of versus models for—that can be used to help educators notice and interpret how models are positioned in standards, curriculum, and classrooms. (shrink)

Model-based learning has an established position within science education. It has been found to enhance conceptual understanding and provide a way for engaging students in authentic scientific activity. Despite ample research, few studies have examined the cognitive processes regarding learning scientific concepts within MBL. On the other hand, recent research within cognitive science has examined the learning of so-called relational categories. Relational categories are categories whose membership is determined on the basis of the common relational structure. In this theoretical paper, (...) I argue that viewing models as relational categories provides a well-motivated cognitive basis for MBL. I discuss the different roles of models and modeling within MBL and discern the related cognitive aspects brought forward by the reinterpretation of models as relational categories. I will argue that relational knowledge is vital in learning novel models and in the transfer of learning. Moreover, relational knowledge underlies the coherent, hierarchical knowledge of experts. Lastly, I will examine how the format of external representations may affect the learning of models and the relevant relations. The nature of the learning mechanisms underlying students’ mental representations of models is an interesting open question to be examined. Furthermore, the ways in which the expert-like knowledge develops and how to best support it is in need of more research. The discussion and conceptualization of models as relational categories allows discerning students’ mental representations of models in terms of evolving relational structures in greater detail than previously done. (shrink)

Difficulties in learning Ohm’s Law suggest a need to refocus it from the law for a part of the circuit to the law for the whole circuit. Such a revision may improve understanding of Ohm’s Law and its practical applications. This suggestion comes from analysis of the history of the law’s discovery and its teaching. The historical materials this paper provides can also help teacher to improve students’ insights into the nature of science.

Scientific models are used to predict and understand the target phenomena in the reality. The kind of epistemic relationship between the model and the reality is always regarded by most of the philosophers as a representational one. I argue that, complementary to this representational role, some of the scientific models have a constructive role to play in altering and reconstructing the reality in a physical way. I hold that the idealized model assumptions and elements bestow the constructive force of a (...) model on the reality. By recognizing the physical constructive force of some scientific models, the merit of these models could be judged by how successful they are in the reality construction, rather than by the traditional criterion of model-world representation. (shrink)

Callender and Cohen argue that there is no need for a special account of the constitution of scientific representation. I argue that scientific representation is communal and therefore deeply tied to the practice in which it is embedded. The communal nature is accounted for by licensing, the activities of scientific practice by which scientists establish a representation. A case study of the Lotka-Volterra model reveals how licensure is a constitutive element of the representational relationship. Thus, any account of the constitution (...) of scientific representation must account for licensing, meaning that there is a special problem of scientific representation. (shrink)

Indispensablists contend that accepting scientific realism while rejecting mathematical realism involves a double standard. I refute this contention by developing an enhanced version of scientific realism, which I call interactive realism. It holds that interactively successful theories are typically approximately true, and that the interactive unobservable entities posited by them are likely to exist. It is immune to the pessimistic induction while mathematical realism is susceptible to it.

This paper presents an artifactual approach to models that also addresses their fictional features. It discusses first the imaginary accounts of models and fiction that set model descriptions apart from imagined-objects, concentrating on the latter :251–268, 2010; Frigg and Nguyen in The Monist 99:225–242, 2016; Godfrey-Smith in Biol Philos 21:725–740, 2006; Philos Stud 143:101–116, 2009). While the imaginary approaches accommodate surrogative reasoning as an important characteristic of scientific modeling, they simultaneously raise difficult questions concerning how the imagined entities are related (...) to actual representational tools, and coordinated among different scientists, and with real-world phenomena. The artifactual account focuses, in contrast, on the culturally established external representational tools that enable, embody, and extend scientific imagination and reasoning. While there are commonalities between models and fictions, it is argued that the focus should be on the fictional uses of models rather than considering models as fictions. (shrink)

A central component to scientific practice is the construction and use of scientific models. Scientists believe that the success of a model justifies making claims that go beyond the model itself. However, philosophical analysis of models suggests that drawing inferences about the world from successful models is more complex. In this dissertation I develop a framework that can help disentangle the related strands of evaluation of model success, model extendibility, and the ability to draw ampliative inferences about the world from (...) models. I present and critically assess two leading accounts of model assessment, arguing that neither is sufficient to provide a complete understanding of model evaluation. I introduce a more powerful framework incorporating elements of the two views, which can help answer these three questions: What is the target of evaluation in model assessment? How does that evaluation proceed? What licenses us in making inferences about the real world, based on the evaluation of our models as successful? The framework identifies two distinct targets of model evaluation: representational similarity between the model and target system, and the adequacy of the model as a tool to answer questions. Both assessments must be relativized to a purpose, of which there are three general kinds: descriptive, predictive, and explanatory. These purposes differ in the way they inform the similarity relation, which is relevant for the similarity assessment, and the output they produce, which is relevant for the adequacy assessment. Any model can be assessed relative to any purpose, however a model encodes certain decisions made during the model’s construction, which impact its ability to be applied to a new purpose or new domain. My framework shows that extending a model, and drawing inferences from it, depends on its representational similarity. I apply this framework to several examples taken from astrophysics showing in detail how it can help illuminate the structure of the models, as well as make the justification for inferences made from them clear. The final chapter is a detailed analysis of a contemporary debate surrounding the use of models in astrophysics, between proponents of MOND and the standard ΛCDM model. (shrink)

This volume argues for a new image of science that understands both natural and social phenomena to be the product of mechanisms, casting the work of science as an effort to understand those mechanisms. Glennan offers an account of the nature of mechanisms and of the models used to represent them in physical, life, and social sciences.