Scientific consensus is widely deferred to in public debates as a social indicator of the existence of knowledge. However, it is far from clear that such deference to consensus is always justified. The existence of agreement in a community of researchers is a contingent fact, and researchers may reach a consensus for all kinds of reasons, such as fighting a common foe or sharing a common bias. Scientific consensus, by itself, does not necessarily indicate the existence of shared knowledge among (...) the members of the consensus community. I address the question of under what conditions it is likely that a consensus is in fact knowledge based. I argue that a consensus is likely to be knowledge based when knowledge is the best explanation of the consensus, and I identify three conditions—social calibration, apparent consilience of evidence, and social diversity, for knowledge being the best explanation of a consensus. (shrink)

Meynell’s contention is that feminists should attend to pictures in science as distinctive bearers of epistemic content that cannot be reduced to propositions. Remarks on the practice and function of medical illustration—specifically, images Nancy Tuana used in her discussion of the construction of ignorance of women’s sexual function (2004)—show pictures to be complex and powerful epistemic devices. Their affinity with perennial feminist concerns, the relation between epistemic subject and object, and the nature of social knowledge, are of particular interest.

Résumé Dans cet article, nous discuterons de l’intégration du numérique à la sémiotique et proposerons qu’une modélisation conceptuelle puisse offrir un pont de dialogue entre ces deux domaines classiquement cloisonnés. Plus précisément, nous avancerons l’hypothèse que tout projet de recherche qui en appellera à l’informatique soit une démarche scientifique que s’il construit une théorie qui contient, en plus des modèles classiques que sont les modèles formel, computationnel et physique, un modèle conceptuel. Ce lieu, où les chercheur-es conceptualisent les multiples dimensions (...) de leur objet de recherche, sera alors défini en tant que socle d’une relation solide entre la sémiotique et l’informatique. Nous verrons que les différentes définitions du modèle conceptuel convergent vers la thèse soutenant que la connaissance scientifique met en œuvre une instance de conceptualisation qui doit identifier les diverses dimensions du problème en plus de devoir s’exprimer de manière à ce qu’elle soit communicable entre les membres des communautés épistémiques. Nous verrons, enfin, qu’un projet de recherché sémiotique exige la construction d’un tel modèle afin de décrire, généraliser et sélectionner des problèmes et que ce même modèle, conceptuel, sera aussi nécessaire si le ou la sémioticien-ne utilise l’informatique dans le cadre de sa recherche.fr. (shrink)

We suggest that human culture exhibits key Darwinian evolutionary properties, and argue that the structure of a science of cultural evolution should share fundamental features with the structure of the science of biological evolution. This latter claim is tested by outlining the methods and approaches employed by the principal subdisciplines of evolutionary biology and assessing whether there is an existing or potential corresponding approach to the study of cultural evolution. Existing approaches within anthropology and archaeology demonstrate a good match with (...) the macroevolutionary methods of systematics, paleobiology, and biogeography, whereas mathematical models derived from population genetics have been successfully developed to study cultural microevolution. Much potential exists for experimental simulations and field studies of cultural microevolution, where there are opportunities to borrow further methods and hypotheses from biology. Potential also exists for the cultural equivalent of molecular genetics in “social cognitive neuroscience,” although many fundamental issues have yet to be resolved. It is argued that studying culture within a unifying evolutionary framework has the potential to integrate a number of separate disciplines within the social sciences. (shrink)

Though the concept of ‘stylized fact’ plays an important role in the economic literature, there is little analysis of the definition and evaluative use of the term. A permissive account of stylized facts is developed which focuses on their mediating role between models and empirical evidence. The mediation relationship restricts stylized facts by requiring concrete empirical targets. On the other hand, there is much legitimate diversity within the permissive account; key dimensions of diversity are argued to be the part of (...) the model targeted (explanans vs. explanandum) and degree of partiality of correspondence. The use of stylized fact in model evaluation points to the downside of stylization: decreased ability to support strong claims about particular targets. In the final analysis, the role of stylized facts in model-based explanation depends on the view taken of the relative importance of generality and empirical adequacy. (shrink)

We introduce a novel point of view on the “models as mediators” framework in order to emphasize certain important epistemological questions about models in science which have so far been little investigated. To illustrate how this perspective can help answer these kinds of questions, we explore the use of simplified models in high energy physics research beyond the Standard Model. We show in detail how the construction of simplified models is grounded in the need to mitigate pressing epistemic problems concerning (...) the uncertainty inherent in the present theoretical and experimental contexts. (shrink)

: The main contribution of this paper to current philosophical and sociological studies on modeling is to analyze modeling as an object-oriented interdisciplinary activity and thus to bring new insights into the wide, heterogeneous discourse on tools, forms and organization of interdisciplinary research. A detailed analysis of interdisciplinarity in the making of models is presented, focusing on long-standing interdisciplinary collaboration between specialists in infectious diseases, mathematicians and computer scientists. The analysis introduces a novel way of studying the elements of the (...) models as carriers of interdisciplinarity. These elements, being functionally interdependent building blocks, evolve during the modeling work and carry the disciplinary tensions in the process. This shows how the long and challenging process of defining and reformulating the object of research is crucial for understanding the dynamics of interdisciplinarity in the making. (shrink)

In this paper I analyze the process by which modelers in systems biology arrive at an adequate representation of the biological structures thought to underlie data gathered from high-throughput experiments. Contrary to views that causal claims and explanations are rare in systems biology, I argue that in many studies of gene regulatory networks modelers aim at a representation of causal structure. In addressing modeling challenges, they draw on assumptions informed by theory and pragmatic considerations in a manner that is guided (...) by an interventionist conception of causal structure. While doubts have been raised about the applicability of this notion of causality to complex biological systems, it is here seen to be an adequate guide to inquiry. (shrink)

In the seventeenth century, Newton published his famous experimentum crucis, in which he claimed that light is heterogeneous and is composed of rays with different refrangibilities. Experiments, especially the crucial experiment, were important for justifying Newton’s theory of light, and eventually his theory of color. A century later, Goethe conducted a series of experiments on the nature of color, especially in contradistinction to Newton, and he defended his research with a methodological principle formulated in “Der Versuch als Vermittler.” Goethe’s principle (...) included two elements: a series of experiments and resultant higher empirical evidence, which functioned as mediator between the objective and the subjective . Although the notion of experimentum crucis became popular among scientists for reconstructing experimental research and for justifying theories, especially for rhetorical purposes, Newton’s justification of his theory of light and color is best reconstructed in terms of Goethe’s methodological principle. Finally, Goethe’s principle has important consequences for the contemporary philosophical underdetermination thesis. (shrink)

At least since Kuhn’s Structure, philosophers have studied the influence of social factors in science’s pursuit of truth and knowledge. More recently, formal models and computer simulations have allowed philosophers of science and social epistemologists to dig deeper into the detailed dynamics of scientific research and experimentation, and to develop very seemingly realistic models of the social organization of science. These models purport to be predictive of the optimal allocations of factors, such as diversity of methods used in science, size (...) of groups, and communication channels among researchers. In this paper we argue that the current research faces an empirical challenge. The challenge is to connect simulation models with data. We present possible scenarios about how the challenge may unfold. (shrink)

Read argues that modeling cultural idea systems serves to make explicit the cultural rules through which "cultural idea systems" frame behaviors that are culturally meaningful. Because cultural rules are typically "invisible" to us, one of the anthropologists' tasks is to elicit these rules, make them explicit and then use them to build explanations for patterns in cultural phenomena. The main example of Read's approach to cultural idea systems is the formal modeling of kinship terminologies. I reconstruct Read's modeling strategy as (...) comprising the following steps:From the way in which culture-bearers compute kin relations a data model is construed that makes explicit the cultural theory embedded in a kinship .. (shrink)

Is knowledge in the natural sciences discovered or constructed? For objectivists, scientific knowledge is discovered through investigations into a mind-independent, natural world. For constructivists, such knowledge is produced through negotiations among members of a professional guild. I examine the clash between the two positions and propose that scientific knowledge is the concurrent outcome from investigations into a natural world and from consensus reached through negotiations of a professional guild. Specifically, I introduce the general methodological notion, instituting science, which incorporates both (...) the discovery and the construction processes in the generation of scientific knowledge. To that end, I use a case study from the biomedical sciences to illustrate the notion. I conclude with a discussion of how this methodological notion helps to address the debate between objectivists and constructivists over the generation of scientific knowledge, and of how it compares with others who have also attempted to address the debate. (shrink)

What I call theoretical abduction (sentential and model-based)certainly illustrates much of what is important in abductive reasoning, especially the objective of selecting and creating a set of hypotheses that are able to dispense good (preferred) explanations of data, but fails to account for many cases of explanation occurring in science or in everyday reasoning when the exploitation of the environment is crucial. The concept of manipulative abduction is devoted to capture the role of action in many interesting situations: action provides (...) otherwise unavailable information that enables the agent to solve problems by starting and performing a suitable abductive process of generation or selection of hypotheses. Many external things, usually inert from the epistemological point of view, can be transformed into what I call epistemic mediators, which are illustrated in the last part of the paper, together with an analysis of the related notions of ``perceptual and inceptual rehearsal'' and of ``external representation''. (shrink)

More than a hundred years ago, the American philosopher C. S. Peirce suggested the idea of pragmatism as a logical criterion to analyze what words and concepts express through their practical meaning. Many words have been spent on creative processes and reasoning, especially in the case of scientific practices. In fact, philosophers have usually offered a number of ways of construing hypotheses generation, but all aim at demonstrating that the activity of generating hypotheses is paradoxical, illusory or obscure, and thus (...) not analyzable. The “computational turn” gave us a new way to understand creative processes in a strictly pragmatic sense. Artificial Intelligence and Cognitive Science tools allow us to test concepts and ideas previously conceived in abstract terms. It is in the perspective of these actual models that we find the central role of abduction in the explanation of creative reasoning in science. What I call theoretical abduction certainly illustrates much of what is important in abductive reasoning, especially the objective of selecting and creating a set of hypotheses that are able to dispense good explanations of data, but fails to account for many cases of explanation occurring in science or in everyday reasoning when the exploitation of the environment is crucial. The concept of manipulative abduction is devoted to capture the role of action in many interesting situations: action provides otherwise unavailable information that enables the agent to solve problems by starting and performing a suitable abductive process of generation or selection of hypotheses. Many external things, usually inert from the epistemological point of view, can be transformed into what I call epistemic mediators, which are illustrated in the last part of the paper. (shrink)

Many philosophers of science think scientific practice can benefit from philosophical concepts, and as such philosophy of science should play a direct role in science and engineering education. In this paper we consider a highly integrative course design strategy for integrating philosophy of science in specific disciplinary educational programmes through adaptation, operationalization and embedding of philosophy of science material to fit both the scientific and educational structure of a programme. The goal of the strategy is to help encourage students to (...) recognize the value of philosophical concepts to scientific decision making and to apply them in their own scientific practice. We use the example of a 7.5 ECTS civil engineering course which implements this design at a European technical university, to elaborate these concepts, and present some evidence on how students receive the course. We discuss some of challenges and limitations of implementing this kind of strategy for teaching philosophy of science. (shrink)

A characterization of the modelling process in science is proposed for science education, based on Mario Bunge’s ideas about the construction of models in science. Galileo’s Dialogues are analysed as a potentially fruitful starting point to implement strategies aimed at modelling in the classroom in the light of that proposal. It is argued that a modelling process for science education can be conceived as the evolution from phenomenological approaches towards more representational ones, emphasizing the role of abstraction and idealization in (...) model construction. The shift of reference of theories—from sensible objects to conceptual objects—and the black-box models construction process, which are both explicitly presented features in Galileo’s Dialogues, are indicated as highly relevant aspects for modelling in science education. (shrink)

In this article, we provide a case study examining how integrative systems biologists build simulation models in the absence of a theoretical base. Lacking theoretical starting points, integrative systems biology researchers rely cognitively on the model-building process to disentangle and understand complex biochemical systems. They build simulations from the ground up in a nest-like fashion, by pulling together information and techniques from a variety of possible sources and experimenting with different structures in order to discover a stable, robust result. Finally, (...) we analyze the alternative role and meaning theory has in systems biology expressed as canonical template theories like Biochemical Systems Theory. (shrink)

The literature on values in science struggles with questions about how to describe and manage the role of values in scientific research. We argue that progress can be made by shifting this literature’s current emphasis. Rather than arguing about how non-epistemic values can or should figure into scientific assessment, we suggest analyzing how scientific assessment can accommodate non-epistemic values. For scientific assessment to do so, it arguably needs to incorporate goals that have been traditionally characterized as non-epistemic. Building on this (...) insight, we show how the adequacy-for-purpose framework recently developed for assessing scientific models can provide a general framework for describing scientific assessment so that it goes beyond purely epistemic considerations. Adopting this framework has significant advantages and opens the possibility of effecting a partial rapprochement between critics and proponents of the value-free ideal. (shrink)

Philosophers have usually offered a number of ways of describing hypotheses generation, but all aim at demonstrating that the activity of generating hypotheses is paradoxical, illusory or obscure, and then not analysable. Those descriptions are often so far from Peircian pragmatic prescription and so abstract to result completely unknowable and obscure. The “computational turn” gives us a new way to understand creative processes in a strictly pragmatic sense. In fact, by exploiting artificial intelligence and cognitive science tools, computational philosophy allows (...) us to test concepts and ideas previously conceived only in abstract terms. It is in the perspective of these actual computational models that I find the central role of abduction in the explanation of creative reasoning in science. Creativity and discovery are no more seen as a mysterious irrational process, but, thanks to constructive accounts, as a complex relationship among different inferential steps that can be clearly analysed and identified. I maintain that the computational philosophy analysis of model-based and manipulative abduction and of external and epistemic mediators is important not only to delineate the actual practice of abduction, but also to further enhance the development of programs computationally adequate in rediscovering, or discovering for the first time, for example, scientific hypotheses or mathematical theorems. (shrink)

What I call theoretical abduction (sentential and model-based) certainly illustrates much of what is important in abductive reasoning, especially the objective of selecting and creating a set of hypotheses that are able to dispense good (preferred) explanations of data, but fails to account for many cases of explanations occurring in science or in everyday reasoning when the exploitation of the environment is crucial. The concept of manipulative abduction is devoted to capture the role of action in many interesting situations: action (...) provides otherwise unavailable information that enables the agent to solve problems by starting and performing a suitable abductive process of generation or selection of hypotheses. Many external things, usually inert from the epistemological point of view, can be transformed into what I call epistemic mediators, which are illustrated in the last part of the paper, together with an analysis of the related notion of external representation . Finally, some examples of computational programs that simulate geometrical reasoning are illustrated. The computational embodiment generates a kind of squared epistemic mediator: geometrical construction, as an example of epistemic mediator, is further mediated. (shrink)

In the last few years, biologists and computer scientists have claimed that the introduction of data science techniques in molecular biology has changed the characteristics and the aims of typical outputs (i.e. models) of such a discipline. In this paper we will critically examine this claim. First, we identify the received view on models and their aims in molecular biology. Models in molecular biology are mechanistic and explanatory. Next, we identify the scope and aims of data science (machine learning in (...) particular). These lie mainly in the creation of predictive models which performances increase as data set increases. Next, we will identify a tradeoff between predictive and explanatory performances by comparing the features of mechanistic and predictive models. Finally, we show how this a priori analysis of machine learning and mechanistic research applies to actual biological practice. This will be done by analyzing the publications of a consortium—The Cancer Genome Atlas—which stands at the forefront in integrating data science and molecular biology. The result will be that biologists have to deal with the tradeoff between explaining and predicting that we have identified, and hence the explanatory force of the ‘new’ biology is substantially diminished if compared to the ‘old’ biology. However, this aspect also emphasizes the existence of other research goals which make predictive force independent from explanation. (shrink)

El propósito del presente trabajo consiste en abordar la pregunta por la ontología de la química cuántica. Para ello nos concentraremos en el concepto de enlace químico desde la perspectiva de los dos enfoques a través de los cuales la ecuación de Schrödinger se aplica a los sistemas químicos moleculares: la teoría del enlace de valencia (EV) y la teoría del orbital molecular (OM). Sobre la base de la presentación de ambos enfoques y su comparación, señalaremos que, a pesar de (...) su denominación tradicional, no pueden considerarse estrictamente como teorías científicas, sino que se ajustan mejor a la noción de modelo; en particular, son modelos que incorporan conceptos y leyes tanto del ámbito de la mecánica cuántica como del de la química estructural. Estas consideraciones nos permitirán argumentar que la química cuántica no posee un referente ontológico autónomo, sino que se trata de un ámbito científico cuya vigencia descansa sobre su éxito práctico en el cálculo y la predicción. Finalmente, indicaremos de qué modo los enfoques EV y OM del enlace químico abren una nueva perspectiva respecto de la noción misma de modelo en ciencias empíricas. (shrink)

In this paper, I argue that recent sociological theory has become increasingly bifurcated into two mutually incompatible styles of theorizing that I label formalist and behavioral-realist. Formalism favors mathematization and proposes an instrumentalist ontology of abstract processes while behavioral-realist theory takes at its basis the "real" physical individual endowed with concrete biological, cognitive and neurophysiological capacities and constraints and attempts to derive the proper conceptualization of social behavior from that basis. Formalism tends to lead toward a conceptually independent sociology that (...) in principle requires only minimal reference to the empirical and ontological storehouse of other disciplines, while behavioral-realist theory leads to an interdisciplinary sociology that can be located within a hierarchy of behavioral sciences, leading to questions regarding the relationship between sociology and other disciplines as well as issues of transdisciplinary unification and possible interdisciplinary reduction. I explore the consequences of this split for the project of explanatory sociological theory within the context of how it has manifested itself in sociological network theory and social psychology. I close with a critique and assessment of formalist tendencies in sociological theorizing. (shrink)

This article argues for an anti-deflationist view of scientific representation. Our discussion begins with an analysis of the recent Callender–Cohen deflationary view on scientific representation. We then argue that there are at least two radically different ways in which a thing can be represented: one is purely symbolic, and therefore conventional, and the other is epistemic. The failure to recognize that scientific models are epistemic vehicles rather than symbolic ones has led to the mistaken view that whatever distinguishes scientific models (...) from other representational vehicles must merely be a matter of pragmatics. It is then argued that even though epistemic vehicles also contain conventional elements, they do their job of demonstration in spite of such elements. (shrink)

This article develops an approach to modelling and models in science—the hybrid view—that is against model fictionalism of a recent stripe. It further argues that there is a version of fictionalism about models to which my approach is neutral and which makes sense only if one adopts a special sort of antirealism. Otherwise, my approach strongly suggests that one stay away from fictionalism and embrace realism directly.

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)

Scientific models are often said to be more or less general depending on how many cases they cover. In this paper we argue that the cardinality of cases is insufficient as a metric of generality, and we present a novel account based on measure theory. This account overcomes several problems with the cardinality approach, and additionally provides some insight into the nature of assessments of generality. Specifically, measure theory affords a natural and quantitative way of describing local spaces of possibility. (...) The generality of models can be understood as the measure of possibilities to which the models apply. In order to illustrate our view, we consider the example of structural genomics, the ongoing project of building three-dimensional models of biological macromolecules like proteins. Using measure theory, we interpret the practice of homology modeling, where such models are understood to apply widely but imperfectly to the space of possible proteins. (shrink)

Many biological investigations are organized around a small group of species, often referred to as ‘model organisms’, such as the fruit fly Drosophila melanogaster. The terms ‘model’ and ‘modelling’ also occur in biology in association with mathematical and mechanistic theorizing, as in the Lotka–Volterra model of predator-prey dynamics. What is the relation between theoretical models and model organisms? Are these models in the same sense? We offer an account on which the two practices are shown to have different epistemic characters. (...) Theoretical modelling is grounded in explicit and known analogies between model and target. By contrast, inferences from model organisms are empirical extrapolations. Often such extrapolation is based on shared ancestry, sometimes in conjunction with other empirical information. One implication is that such inferences are unique to biology, whereas theoretical models are common across many disciplines. We close by discussing the diversity of uses to which model organisms are put, suggesting how these relate to our overall account. 1 Introduction2 Volterra and Theoretical Modelling3 Drosophila as a Model Organism4 Generalizing from Work on Model Organisms5 Phylogenetic Inference and Model Organisms6 Further Roles of Model Organisms6.1 Preparative experimentation6.2 Model organisms as paradigms6.3 Model organisms as theoretical models6.4 Inspiration for engineers6.5 Anchoring a research community7 Conclusion. (shrink)

What is the best way to analyse abstraction in scientific modelling? I propose to focus on abstracting as an epistemic activity, which is achieved in different ways and for different purposes depending on the actual circumstances of modelling and the features of the models in question. This is in contrast to a more conventional use of the term ‘abstract’ as an attribute of models, which I characterise as black-boxing the ways in which abstraction is performed and to which epistemological advantage. (...) I exemplify my claims through a detailed reconstruction of the practices involved in creating two types of models of the flowering plant Arabidopsisthaliana, currently the best-known model organism in plant biology. This leads me to distinguish between two types of abstraction processes: the ‘material abstracting’ required in the production of Arabidopsis specimens and the ‘intellectual abstracting’ characterising the elaboration of visual models of Arabidopsis genomics. Reflecting on the differences between these types of abstracting helps to pin down the epistemic skills and research commitments used by researchers to produce each model, thus clarifying how models are handled by researchers and with which epistemological implications. (shrink)

Knowledge-making practices in biology are being strongly affected by the availability of data on an unprecedented scale, the insistence on systemic approaches and growing reliance on bioinformatics and digital infrastructures. What role does theory play within data-intensive science, and what does that tell us about scientific theories in general? To answer these questions, I focus on Open Biomedical Ontologies, digital classification tools that have become crucial to sharing results across research contexts in the biological and biomedical sciences, and argue that (...) they constitute an example of classificatory theory. This form of theorizing emerges from classification practices in conjunction with experimental know-how and expresses the knowledge underpinning the analysis and interpretation of data disseminated online. (shrink)

Scientific classification has long been recognized as involving a specific style of reasoning and doing research, and as occasionally affecting the development of scientific theories. However, the role played by classificatory activities in generating theories has not been closely investigated within the philosophy of science. I argue that classificatory systems can themselves become a form of theory, which I call classificatory theory, when they come to formalize and express the scientific significance of the elements being classified. This is particularly evident (...) in some of the classification practices used in contemporary experimental biology, such as bio-ontologies used to classify genomic data and typologies used to classify “normal” stages of development in developmental biology. In this paper, I explore some characteristics of classificatory theories and ways in which they differ from other types of scientific theories and other components of scientific epistemology, such as models and background assumptions. (shrink)

In this paper, a modest version of the Semantic View is motivated as both tenable and potentially fruitful for philosophy of science. An analysis is proposed in which the Semantic View is characterized by three main claims. For each of these claims, a distinction is made between stronger and more modest interpretations. It is argued that the criticisms recently leveled against the Semantic View hold only under the stronger interpretations of these claims. However, if one only commits to the modest (...) interpretation for all the claims, then the view obtained, the Modest Semantic View, is tenable and fruitful for the philosophy of science. (shrink)

Science is replete with falsehoods that epistemically facilitate understanding by virtue of being the very falsehoods they are. In view of this puzzling fact, some have relaxed the truth requirement on understanding. I offer a factive view of understanding that fully accommodates the puzzling fact in four steps: (i) I argue that the question how these falsehoods are related to the phenomenon to be understood and the question how they figure into the content of understanding it are independent. (ii) I (...) argue that the falsehoods do not figure into the understanding’s content by being elements of its periphery or core. (iii) Drawing lessons from case studies, I argue that the falsehoods merely enable understanding. When working with such falsehoods, only the truths we extract from them are elements of the content of our understanding. (iv) I argue that the extraction view is compatible with the thesis that falsehoods can have an epistemic value by virtue of being the very falsehoods they are. (shrink)

Robert Sugden argues that robustness analysis cannot play an epistemic role in grounding model-world relationships because the procedure is only a matter of comparing models with each other. We posit that this argument is based on a view of models as being surrogate systems in too literal a sense. In contrast, the epistemic importance of robustness analysis is easy to explicate if modelling is viewed as extended cognition, as inference from assumptions to conclusions. Robustness analysis is about assessing the reliability (...) of our extended inferences, and when our confidence in these inferences changes, so does our confidence in the results. Furthermore, we argue that Sugden’s inductive account relies tacitly on robustness considerations. (shrink)

The recognition that models and simulations play a central role in the epistemology of science is about fifteen years old. Although models had long been discussed as possible foundational units in the logical analysis of scientific knowledge, the philosophical study of modelling as a distinct epistemic practice really got going in the wake of the Models as Mediators anthology edited by Margaret Morrison and Mary Morgan. In spite of the broad agreement that in fact much of science is model-based, however, (...) there is still little agreement on pretty much anything else. What are models? Are they representations or fictions, abstract entities or concrete artifacts? Which functions do they play? Can they explain.. (shrink)

Scientists of many disciplines use theoretical models to explain and predict the dynamics of the world. They often have to rely on digital computer simulations to draw predictions fromthe model. But to deliver phenomenologically adequate results, simulations deviate from the assumptions of the theoretical model. Therefore the role of simulations in scientific explanation demands itself an explanation. This paper analyzes the relation between real-world system, theoretical model, and simulation. It is argued that simulations do not explain processes in the real (...) world directly. The way in which simulations help explaining real-world processes is conceived as indirect, mediated by the theoretical model. Simulacra are characterized further, and turn out to be a priori measurable. This gives a clue to a better understanding of the epistemic role of computer simulations in scientific research. (shrink)

This two-part article presents the research program for a theory and empirical analysis of religious evolution. It is assumed that religion isprimarilya co-evolution to societal evolution, which in turn is a co-evolution to mental, organic, and physical evolution. The theory of evolution is triangulated with the systems theory and the semiotically informed theory of communication, so that knowledge can be gained that would not be acquired by only one of the three theories: The differentiation between religion and its environment can (...) be reconstructed based on the theory of evolution. The elements of the theory of evolution can be understood as the formation of systems. The semiotically informed theory of communication clarifies the conditions of the combination of both the systems theory and the theory of evolution as well as its objects. In turn, the combination of the systems theory and the theory of evolution can describe how communication—including religion and science—evolves and is structured. (shrink)

Es soll ein Beitrag zur epistemischen Charakterisierung von Computersimulationen als jenseits von Experiment und Theorie geleistet werden. Es wird argumentiert, dass die in der Simulationstechnik eingesetzten Verfahren nicht numerische Lösungen liefern, sondern deren Dynamik mittels generativer Mechanismen imitieren. Die Computersimulationen in der Klimatologie werden als systematisches wie historisches Fallbeispiel behandelt. Erst "Simulationsexperimente" gestatten es, mittels Modellen eine Dynamik zu imitieren, ohne deren Grundgleichungen zu "lösen". /// Computer simulations will be characterized in epistemic respect as a method between experiment and theory. (...) It will be argued that simulations do not provide numerical solutions, rather they use generative mechanisms to imitate a dynamics. Climate science will be considered as a case both systematically and historically. Only simulation experiments allow to build models that imitate a dynamics without solving the relevant equations. (shrink)

Es soll ein Beitrag zur epistemischen Charakterisierung von Computersimulationen als jenseits von Experiment und Theorie geleistet werden. Es wird argumentiert, dass die in der Simulationstechnik eingesetzten Verfahren nicht numerische Lösungen liefern, sondern deren Dynamik mittels generativer Mechanismen imitieren. Die Computersimulationen in der Klimatologie werden als systematisches wie historisches Fallbeispiel behandelt. Erst "Simulationsexperimente" gestatten es, mittels Modellen eine Dynamik zu imitieren, ohne deren Grundgleichungen zu "lösen". /// Computer simulations will be characterized in epistemic respect as a method between experiment and theory. (...) It will be argued that simulations do not provide numerical solutions, rather they use generative mechanisms to imitate a dynamics. Climate science will be considered as a case both systematically and historically. Only simulation experiments allow to build models that imitate a dynamics without solving the relevant equations. (shrink)

Our concern is in explaining how and why models give us useful knowledge. We argue that if we are to understand how models function in the actual scientific practice the representational approach to models proves either misleading or too minimal. We propose turning from the representational approach to the artefactual, which implies also a new unit of analysis: the activity of modelling. Modelling, we suggest, could be approached as a specific practice in which concrete artefacts, i.e., models, are constructed with (...) the help of specific representational means and used in various ways, for example, for the purposes of scientific reasoning, theory construction and design of experiments and other artefacts. Furthermore, in this activity of modelling the model construction is intertwined with the construction of new phenomena, theoretical principles and new scientific concepts. We will illustrate these claims by studying the construction of the ideal heat engine by Sadi Carnot. (shrink)

This paper examines two recent approaches to the nature and functioning of economic models: models as isolating representations and models as credible constructions. The isolationist view conceives of economic models as surrogate systems that isolate some of the causal mechanisms or tendencies of their respective target systems, while the constructionist approach treats them rather like pure constructions or fictional entities that nevertheless license different kinds of inferences. I will argue that whereas the isolationist view is still tied to the representationalist (...) understanding of models that takes the model-target dyad as the basic unit of analysis, the constructionist perspective can better accommodate the way we actually acquire knowledge through them. Using the example of Tobin’s ultra-Keynesian model I will show how many of the epistemic characteristics of modelling tend to go unrecognised if too much focus is placed on the model-target dyad. (shrink)

Rather than assume a unitary cybernetics, I ask how its disunity mattered to the history of the human sciences in the United States from about 1940 to 1980. I compare the work of four prominent social scientists – Herbert Simon, George Miller, Karl Deutsch, and Talcott Parsons – who created cybernetic models in psychology, economics, political science, and sociology with the work of anthropologist Gregory Bateson, and relate their interpretations of cybernetics to those of such well-known cyberneticians as Norbert Wiener, (...) Warren McCulloch, W. Ross Ashby, and Heinz von Foerster. I argue that viewing cybernetics through the lens of disunity – asking what was at stake in choosing a specific cybernetic model – shows the complexity of the relationship between first-order cybernetics and the postwar human sciences, and helps us rethink the history of second-order cybernetics. (shrink)

This paper studies the semiotic,epistemological and historical aspects of Berzelianformulas in early nineteenth-century organicchemistry. I argue that Berzelian formulas wereenormously productive `paper tools' for representingchemical reactions of organic substances, and forcreating different pathways of reactions. Moreover, myanalysis of Jean Dumas's application of Berzelianformulas to model the creation of chloral from alcoholand chlorine exemplifies the role played by chemicalformulas in conceptual development (the concept ofsubstitution). Studying the dialectic of chemists'collectively shared goals and tools, I argue thatpaper tools, like laboratory instruments, areresources (...) whose possibilities are not exhausted byscientists' attempts to achieve existing goals, butrather whose applications generate new goals. The term`paper tools' is introduced to emphasize that thepragmatic and syntactic aspects of symbol systems arefully comparable to physical laboratory tools. (shrink)

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

Agent-based models are increasingly important in social science research. They have two obvious apparent virtues: they can model complex macrosociological phenomena without strong assumptions about agents and without analytic solutions for models, and they seem to instantiate the methodological individualist program in a concrete way. We argue that the latter claim is false. After providing schematic accounts of ABM models and a first introduction to ways in which to characterize individualist explanations, we work through six conceptions of individualist explanations that (...) are decreasingly "less individualist" and argue that ABM-based explanations in the social sciences are not inevitably individualist in any of these senses. ABMs allow for explanatory relations among social entities and properties in the model environment and they are silent on what basic agents are, allowing social entities and properties to play basic explanatory roles. (shrink)

In the quest for a new social turn in philosophy of science, exploring the prospects of a Vygotskian perspective could be of significant interest, especially due to his emphasis on the role of culture and socialisation in the development of cognitive functions. However, a philosophical reassessment of Vygotsky's ideas in general has yet to be done. As a step towards this direction, I attempt to elaborate an approach on scientific representations by drawing inspirations from Vygotsky. Specifically, I work upon Vygotsky’s (...) understanding on the nature and function of concepts, mediation and zone of proximal development. -/- I maintain that scientific representations mediate scientific cognition in a tool-like fashion (like Vygotsky’s signs). Scientific representations are consciously acquired through deliberate inquiry in a specific context, where it turns to be part of a whole system, reflecting the social practices related to scientific inquiry, just scientific concepts do in Vygotsky’s understanding. They surrogate the real processes or effects under study, by conveying some of the features of the represented systems. Vygotsky’s solution to the problem of the ontological status of concepts points to an analogous understanding for abstract models, which should be regarded neither as fictions nor as abstract objects. -/- I elucidate these views by using the examples of the double-helix model of DNA structure and the development of our understanding of the photoelectric effect. (shrink)