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)

Controversies in science have a tendency to be long-lasting. Moreover, they tend to wither rather than be solved by sorting out the arguments pro and con. Barring the sociological dimension, an important factor in the perpetuation of scientific controversies seems to be the contestants' passion for broad philosophical theses when it comes to defending their respective positions. In this paper one such controversy is analysed. It involves the alleged use of Popperian falsificationism to defend a position in (community) ecology some (...) years ago. The upshot of the analysis is that falsificationism is altogether irrelevant to the controversy's solution; philosophy, though, is utterly relevant if one limits it to elementary, uncontroversial, normative methodological principles. (shrink)

Positivism has been used to establish a standard that Information Systems (IS) research must meet to be scientific. According to such positivistic beliefs in IS, scientific research should: 1) be generalizable, 2) focus on stable independent variables, 3) have certain ontological assumptions, and 4) use statistical or quantitative methods rather than qualitative methods. We argue that logical positivist philosophers required none of these. On the contrary, logical positivist philosophers regarded philosophizing in general and ontological considerations in particular as nonsense. Moreover, (...) the positivists’ preferred empirical research method was not a survey, but rather a qualitative observation recorded by field notes. In addition, positivist philosophers required neither statistical nor nonstatistical generalizability. At least some positivist philosophers also acknowledged the study of singular cases as being scientific. Many research orientations (e.g., single-setting research, examination of change, qualitative research) that are deemed “unscientific” by positivism in IS seem to be “scientific” (in principle) according to logical positivism. In turn, generally speaking, what has been justified as scientific by positivism in IS (e.g., requirements of statistical or nonstatistical generalizability, surveys, independent variables, ontological views) were either not required by logical positivists or were regarded as nonsensical by logical positivists. Furthermore, given that positivism is sometimes associated (or confused) with logical empiricism in IS, we also briefly discuss logical empiricism. Finally, realizing that certain influential, taken-forgranted assumptions that underlie IS research are unwarranted could have ground-breaking implications for future IS research. (shrink)

Rationale One's understanding of medical progress – what it is, how it is pursued and how it is assessed – may be deeply dependent on one's understanding of the metaphysics of medicine, and of diseases in particular. -/- Aims and Objectives In this paper I present a new account of the nature of diseases, neither realist nor constructivist, and describe what progress in medicine looks like if we understand diseases in this way. -/- Conclusions This new account, Constructive Realism, may (...) provide a better account of medicine than either realism or constructivism. (shrink)

Scientific models occupy centre stage in scientific practice. Correspondingly, in recent literature in the philosophy of science, scientific models have been a focus of research. However, little attention has been paid so far to the ontology of scientific models. In this essay, I attempt to clarify the issues involved in formulating an informatively rich ontology of scientific models. Although no full-blown theory—containing all ontological issues involved—is provided, I make several distinctions and point to several characteristic properties exhibited by scientific models (...) that are relevant for individuating scientific models. (shrink)

In this article I argue that a methodological challenge to an integrated history and philosophy of science approach put forth by Ronald Giere almost forty years ago can be met by what I call the Kuhnian mode of History and Philosophy of Science (HPS). Although in the Kuhnian mode of HPS norms about science are motivated by historical facts about scientific practice, the justifiers of the constructed norms are not historical facts. The Kuhnian mode of HPS therefore evades the naturalistic (...) fallacy which Giere’s challenge is a version of. Against the backdrop of a discussion of Laudan’s normative naturalism I argue that the Kuhnian mode of HPS is a superior form of naturalism: it establishes contact to the practice of science without making itself dependent on its contingencies. (shrink)

I explore a type of computational social simulation known as artificial societies. Artificial society simulations are dynamic models of real-world social phenomena. I explore the role that these simulations play in social explanation, by situating these simulations within contemporary philosophical work on explanation and on models. Many contemporary philosophers have argued that models provide causal explanations in science, and that models are necessary mediators between theory and data. I argue that artificial society simulations provide causal mechanistic explanations. I conclude that (...) in their current form, these simulations are based on methodologically individualist assumptions that could limit their potential scope of social explanation. (shrink)

The paper studies the nature of understanding in condensed matter physics (CMP), mediated by the successful employment of its models. I first consider two obvious candidates for the criteria of model-based understanding, Van Fraassen's sense of empirical adequacy and Hacking's instrumental utility , and conclude that both are unsatisfactory. Inspired by Hasok Chang's recent proposal to reformulate realism as the pursuit of ontological plausibility in our system of knowledge, we may require the model under consideration to be understood (or intelligible) (...) before claiming model-based understanding. Here the understanding of a model typically consists of the following: figuring out at least one plausible (preferably realistic) physical mechanism for the model, determining the theoretical consequences of the model by mathematically probing it and developing our physical intuitions about the model. I consider the q-state Potts model to illustrate. After having understood a model, we may employ the model to understand its target phenomena in the world. This is done by matching one of the interpretative models of the model with the central features of the phenomena. The matching should be motivated (ideally both theoretically and empirically) in the sense that we have good reason to believe that the central features of the phenomena can be thought of as having more or less the same structure as postulated by the interpretative model. In conclusion, I propose a two-stage account of model-based understanding in CMP: (1) understanding of a model and (2) matching a target phenomenon with a well-motivated interpretative model of the model. Empirical success and instrumental utility both play their roles in the evaluation of how successful the model is, but are not the essential part of model-based understanding. (shrink)

This paper examines the question of whether scientific realism is committed to the inevitability of science or is consistent with claims of the contingency of science. In order to address this question, a general characterization of the position of scientific realism is presented. It is then argued that scientific realism has no evident implications with regard to the inevitability of science. A historical case study is presented in which contingency plays a significant role, and the appropriate realist response to this (...) case study is indicated. Finally, it is argued that, when conjoined with a reliabilist theory of method, realism does have implications for the inevitability of science.Keywords: Inevitability; Contingency; Scientific realism; Reliabilism; Ian Hacking. (shrink)

The aim of this paper is to explore the possibility that, at least, some metaphysical debates are ‘metalinguistic negotiations’. I will take the dispute between the dominant approaches of realism and the anti-realism ones about the ontological status of scientific models as a case-study. I will argue that such a debate may be better understood as a disagreement, at bottom normatively, motivated, insofar as a normative and non-factual question may be involved in it: how the relevant piece of language ought (...) to be used. Even though I will generally assess the prospects for a broadly deflationist approach, I shall outline a sense in which the dispute can be recast as ‘minimally substantive’. (shrink)

Review essay of How to do science with models. A philosophical primer. Springer briefs in philosophy, Axel Gelfert., 129, Price € 49,99 softcover, ISBN: 978-3-319-27954-1.

The epistemic conception of scientific progress equates progress with accumulation of scientific knowledge. I argue that the epistemic conception fails to fully capture scientific progress: theoretical progress, in particular, can transcend scientific knowledge in important ways. Sometimes theoretical progress can be a matter of new theories ‘latching better onto unobservable reality’ in a way that need not be a matter of new knowledge. Recognising this further dimension of theoretical progress is particularly significant for understanding scientific realism, since realism is naturally (...) construed as the claim that science makes theoretical progress. Some prominent realist positions are best understood in terms of commitment to theoretical progress that cannot be equated with accumulation of scientific knowledge. (shrink)

I erect a framework within the semantic view of theories for explaining the empirical success of internally inconsistent models and theories, with scientific realism in mind. The framework is an instance of the ‘content-driven’ approach to inconsistency, advocated by both Norton (Philos Sci 54:327–350, 1987) and Smith (Stud Hist Philos Sci 19:429–445, 1988a, In: Fine A, Leplin J (eds) PSA1988, 1988b), whose ideas my analysis aims to clarify and substantiate.

I review prominent historical arguments against scientific realism to indicate how they display a systematic overshooting in the conclusions drawn from the historical evidence. The root of the overshooting can be located in some critical, undue presuppositions regarding realism. I will highlight these presuppositions in connection with both Laudan’s ‘Old induction’ and Stanford’s New induction, and then delineate a minimal realist view that does without the problematic presuppositions.

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)

The interpretive plasticity of Kuhn’s philosophical work has been reinforced by readings informed by other philosophical, historiographic or sociological projects. This paper highlights several aspects of Kuhn’s work that have been neglected by such readings. First, Kuhn’s early contribution to several subsequent philosophical developments has been unduly neglected. Kuhn’s postscript discussion of “exemplars” should be recognized as one of the earliest versions of a conception of theories as “mediating models.” Kuhn’s account of experimental practice has also been obscured by readings (...) that assimilate his views to Quinean holism. Second, three distinctive Kuhnian themes have been insufficiently recognized. Kuhn’s challenge to received philosophical views has been domesticated by reading him as offering an alternative conception of scientific knowledge. Kuhn is better understood as rejecting knowledge-centric accounts altogether, in favor of understanding the practice of research. Kuhn’s conception of that activity, as conceptual “articulation,” has accordingly also not been given its due. Finally, Kuhn’s career-long insistence on the mutual accountability of philosophy of science and the philosophy of mind and language calls attention to the extent to which these fields have now drifted apart. (shrink)

Attention to scientific practice offers a novel response to philosophical queries about how conceptual understanding is empirically accountable. The locus of the issue is thereby shifted, from perceptual experience to experimental and fieldwork interactions. More important, conceptual articulation is shown to be not merely ?spontaneous? and intralinguistic, but instead involves a establishing a systematic domain of experimental operations. The importance of experimental practice for conceptual understanding is especially clearly illustrated by cases in which entire domains of scientific investigation were first (...) made accessible to articulated conceptual understanding. We thereby see more clearly how experimental systems themselves, and not merely the theories and models they make possible, have an intentional directedness and ?representational? import. (shrink)

This paper sketches an alternative answer to James Jones's recent attempt to explore the implications of cognitive social learning theories of personality for issues in epistemology, philosophy of science, and religious studies. Since the 1960s, two cognitive revolutions have taken place in scientific psychology: the first made cognition central to theories of perception, memory, problem solving, and so on; the second made cognition central to theories of learning and behavior, among others. Cognitive social learning theories find their place in the (...) latter revolution. Because of an ongoing naturalistic revolution in philosophy, these cognitive revolutions in psychology are having a profound effect on both descriptive and normative issues in epistemology and philosophy of science. From the naturalistic perspective, philosophy cannot adequately pursue its goals without the contributions of the empirical sciences, including psychology. The author concludes that the cognitive revolutions in psychology and the naturalistic revolution in philosophy have similar descriptive and normative import for the study of religion. (shrink)

There is a long-standing debate in the philosophy of action and the philosophy of science over folk psychological explanations of human action: do the (perhaps implicit) generalizations that underwrite such explanations purport to state contingent, empirically established connections between beliefs, desires, and actions, or do such generalizations serve rather to define, at least in part, what it is to have a belief or desire, or perform an action? This question has proven important because of certain traditional assumptions made about the (...) role of law-statements in scientific explanations. According to this tradition, law-statements take the form of generalizations, and the laws we find in well-established sciences are contingent and empirical; as such, if the kinds of generalizations at work in folk psychological explanations of human action act like definitions, or state conceptual connections, then such generalizations could not play the kind of explanatory role we find in mature sciences. This paper argues that the aforementioned way of framing the debate reflects a still powerful but impoverished conception of the role laws play in scientific explanations, a conception that, moreover, cannot be reconciled with a good deal of actual scientific practice. When we update the philosophy of science, we find the concerns that are raised for folk psychological explanations largely evaporate or are found not to be specific to such explanations. (shrink)

I begin by arguing that a consistent general naturalism must be understood in terms of methodological maxims rather than metaphysical doctrines. Some specific maxims are proposed. I then defend a generalized naturalism from the common objection that it is incapable of accounting for the normative aspects of human life, including those of scientific practice itself. Evolutionary naturalism, however, is criticized as being incapable of providing a sufficient explanation of categorical moral norms. Turning to the epistemological norms of science itself, particularly (...) those governing the empirical testing of specific models, I argue that these should be regarded as conditional rather than categorical and that, as such, can be given a naturalistic justification. The justification, however, is more cognitive than evolutionary. The historical development of science is found to be a better place for applying evolutionary ideas. After briefly considering the possibility of a naturalistic understanding of mathematics and logic, I turn to the problem of reconciling scientific realism with an evolutionary picture of scientific development. The solution, I suggest, is to understand scientific knowledge as being “perspectival” rather than absolutely objective. I first argue that scientific observation, whether by humans or instruments, is perspectival. This argument is extended to scientific theorizing which is regarded not as the formulation of universal laws of nature but as the construction of principles to be used in the construction of models to be applied to specific natural systems. The application of models, however, is argued to be not merely opportunistic but constrained by the methodological presumption that we live in a world with a definite causal structure even though we can understand it only from various perspectives. (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)

Within the modeling literature, there is often an implicit assumption about the relationship between a given model and a scientific explanation. The goal of this article is to provide a unified framework with which to analyze the myriad relationships between a model and an explanation. Our framework distinguishes two fundamental kinds of relationships. The first is metaphysical, where the model is identified as an explanation or as a partial explanation. The second is epistemological, where the model produces understanding that is (...) related to the explanation of interest. Our analysis reveals that the epistemological relationships are not always dependent on the metaphysical relationships, contrary to what has been assumed by many philosophers of science. Moreover, we identify several importantly different ways that scientific models instantiate these relationships. We argue that our framework provides novel insights concerning the nature of models, explanation, idealization, and understanding. (shrink)

Scientific communities as social groupings and the role that such communities play in scientific change and the production of scientific knowledge is currently under debate. I examine theory change as a complex social interaction among individual scientists and the scientific community, and argue that individuals will be motivated to adopt a more radical or innovative attitude when confronted with striking similarities between model systems and a more robust understanding of specialised vocabulary. Two case studies from the biological sciences, Barbara McClintock (...) and Stanley Prusiner, help motivate the idea that sharing of models and specialised vocabulary fill the gap between discovery and scientific change by promoting the dispersal of important information throughout the scientific community. (shrink)

Recently, a number of philosophers of biology have endorsed views about random drift that, we will argue, rest on an implicit assumption that the meaning of concepts such as drift can be understood through an examination of the mathematical models in which drift appears. They also seem to implicitly assume that ontological questions about the causality of terms appearing in the models can be gleaned from the models alone. We will question these general assumptions by showing how the same equation (...) — the simple 2 = p2 + 2pq + q2 — can be given radically different interpretations, one of which is a physical, causal process and one of which is not. This shows that mathematical models on their own yield neither interpretations nor ontological conclusions. Instead, we argue that these issues can only be resolved by considering the phenomena that the models were originally designed to represent and the phenomena to which the models are currently applied. When one does take those factors into account, starting with the motivation for Sewall Wright’s and R.A. Fisher’s early drift models and ending with contemporary applications, a very different picture of the concept of drift emerges. On this view, drift is a term for a set of physical processes, namely, indiscriminate sampling processes. (shrink)

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 concerns what the epistemic goal of toy modelling 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 article 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. _1_ Introduction _2_ Embedded and Autonomous Toy Models _2.1_ Embedded toy models _2.2_ Autonomous toy models _2.3_ Qualification _3_ A Theory of Understanding for Toy Models _3.1_ Preliminaries and requirements _3.2_ The refined simple view _4_ Two Kinds of Understanding with Toy Models _4.1_ Embedded toy models and how-actually understanding _4.2_ Against a how-actually interpretation of all autonomous toy models _4.3_ The how-possibly interpretation of some autonomous toy models _5_ Conclusion. (shrink)

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)

InExplaining Science: A Cognitive Approach, Ronald Giere (1988), proposes what he calls a cognitive theory of science (p. 2). Giere intends his view to be a broadly scientific account employing the resources of the cognitive sciences (Giere, 1988, p. 2). This paper argues that Giere does not secure a firm foundation for a cognitive theory of science because he leaves the door wide open for social constructivist interpretations of his views. In order to avoid social constructivism, Giere needs to adopt (...) or develop an objective (i.e. non-conventionalist) concept of similarity. (shrink)

Understanding Nature of Science is a central component of scientific literacy, which is agreed upon internationally, and consequently has been a major educational goal for many years all over the globe. In order to justify the promotion of an adequate understanding of NOS, educators have developed several arguments, among them the cultural argument. But what is behind this argument? In order to answer this question, C. P. Snow’s vision of two cultures was used as a starting point. In his famous (...) Rede Lecture from 1959, he complained about a wide gap between the arts and humanities on the one hand and sciences on the other hand. While the representatives of the humanities refer to themselves as real intellectuals, the scientists felt rather ignored as a culture, despite the fact that their achievements had been so important for Western society. Thus, Snow argued that as these intellectual cultures were completely different from each other, a mutual understanding was impossible. The first European Regional IHPST Conference took up the cultural view on science again. Thus, the topic of the conference “Science as Culture in the European Context” encouraged us to look at the two cultures and to figure out possibilities to bridge the gap between them in chemistry teacher education. For this reason, we put together three studies—one theoretical and two independent research projects which contribute to our main research field —in order to address the cultural argument for understanding science from an educational point of view. Among the consented tenets of what understanding NOS implies in an educational context, there are aspects which are associated mainly with the humanities, like the tentativeness of knowledge, creativity, and social tradition, whereas others seem to have a domain-specific meaning, like empirical evidence, theories and laws, and the role of technology. Thus, the cultural argument for understanding science invites us not only to consider domain-specific concepts but also to reflect on similarities between science and the humanities by way of examples. (shrink)

This paper aims (a) to provide characterizations of realism and instrumentalism that are philosophically interesting and applicable to economics; and (b) to defend instrumentalism against realism as a methodological stance in economics. Starting point is the observation that ‘all models are false’, which, or so I argue, is difficult to square with the realist's aim of truth, even if the latter is understood as ‘partial’ or ‘approximate’. The three cheers in favour of instrumentalism are: (1) Once we have usefulness, truth (...) is redundant. (2) There is something disturbing about causal structure. (3) It's better to do what one can than to chase rainbows. (shrink)

Abstract Philosophers have paid little attention to the kind of reduction involved in transforming an analytically intractable equation into solvable form. I argue that this practice is important because it involves the design of a basic level theory for use in a specific domain. The design process can lead to the construction of a new theory. As a result of my analysis, theory design emerges as an important category of analysis for scientific methodology. Similarities between design in technology and science (...) are explored to illuminate the heuristic function of such reductions. (shrink)

This paper aims to address the relevance of the natural sciences for transcendental phenomenology, that is, the issue of naturalism. The first section distinguishes three varieties of naturalism and corresponding forms of naturalization: an ontological one, a methodological one, and an epistemological one. In light of these distinctions, in the second section, I examine the main projects aiming to “naturalize phenomenology”: neurophenomenology, front-loaded phenomenology, and formalized approaches to phenomenology. The third section then considers the commitments of Husserl’s transcendental phenomenology with (...) respect to the three varieties of naturalism previously discussed. I argue that Husserl rejected strong and weak forms of epistemological naturalism, strong methodological naturalism, and ontological naturalism. The fourth section presents the argument that Husserl endorsed a weak, conditional form of methodological naturalism. This point is illustrated with Husserl’s proposal of “somatology,” a natural science apt to study the corporeality of the lived body. The final section addresses the complementarity and respective limits of the transcendental phenomenological and the natural scientific frameworks. I argue that, on Husserl’s account, the function of transcendental phenomenology with respect to the natural sciences is to provide them with an epistemological foundation and an ontological clarification. I suggest that certain natural sciences can be understood, within the transcendental phenomenological framework, as “sciences of constitution,” that is, as sciences investigating the contribution of real structures acting as conditions of possibility for the occurrence of certain kinds of comprehensive unities in lived experience. (shrink)

A natural way to think of models is as abstract entities. If theories employ models to represent the world, theories traffic in abstract entities much more widely than is often assumed. This kind of thought seems to create a problem for a scientific realist approach to theories. Scientific realists claim theories should be understood literally. Do they then imply the reality of abstract entities? Or are theories simply—and incurably—false? Or has the very idea of literal understanding to be abandoned? Is (...) then fictionalism towards scientific theories inevitable? This paper argues that scientific realism can happily co-exist with models qua abstracta. (shrink)

This paper proposes a novel distinction between accounts of scientific representation: it distinguishes thin accounts from thick accounts. Thin accounts focus on the descriptive aspect of representation whereas thick accounts acknowledge the evaluative aspect of representation. Thin accounts focus on the question of what a representation as such is. Thick accounts start from the question of what an adequate representation is. In this paper, I give two arguments in favor of a thick account, the Argument of the Epistemic Aims of (...) Modeling and the Argument of the Normativity of the Practice of Modeling. I also discuss possible objections to a thick account: the Argument from Misrepresentation and the Objections from Model Testing. The conclusion will be that the arguments on balance support a thick account of representation. (shrink)

On the basis of a case study in bioengineering, this paper proposes a novel perspective on models in science and engineering. This is done with the help of two notions: representation and design. These two notions are interpreted as referring to modeling relations between vehicles and targets that differ in their respective directions of fit. The representation relation has a vehicle-to-target direction of fit and the design relation has a target-to-vehicle direction of fit. The case study of an organ on (...) chip model illustrates that the technical device can participate in both design and representation relations. The two relations share the same relatum of the organ on chip, but they have different directions of fit. In the design relation, the chip is adjusted to a design plan, in which case we are dealing with a target-to-vehicle direction of fit. In the representation relation, the chip is adjusted to a human organ, in which case we are dealing with a vehicle-to-target direction of fit. The example shows that a conception of modeling as involving only relations with a vehicle-to-target direction of fit is too narrow to account for models in science and engineering. (shrink)

The process of abstraction and concretisation is a label used for an explicative theory of scientific model-construction. In scientific theorising this process enters at various levels. We could identify two principal levels of abstraction that are useful to our understanding of theory-application. The first level is that of selecting a small number of variables and parameters abstracted from the universe of discourse and used to characterise the general laws of a theory. In classical mechanics, for example, we select position and (...) momentum and establish a relation amongst the two variables, which we call Newton’s 2nd law. The specification of the unspecified elements of scientific laws, e.g. the force function in Newton’s 2nd law, is what would establish the link between the assertions of the theory and physical systems. In order to unravel how and with what conceptual resources scientific models are constructed, how they function and how they relate to theory, we need a view of theory-application that can accommodate our constructions of representation models. For this we need to expand our understanding of the process of abstraction to also explicate the process of specifying force functions etc. This is the second principal level at which abstraction enters in our theorising and in which I focus. In this paper, I attempt to elaborate a general analysis of the process of abstraction and concretisation involved in scientific- model construction, and argue why it provides an explication of the construction of models of the nuclear structure. (shrink)