Scientific Representation

This review essay of two edited volumes sketches how STS scholars have analyzed scientific representation and visualization in recent work. Several key foci have emerged, among them attending closely to materiality, engaging the digital through embodied action, turning to ontology, as well as benefitting from artistic practice and critique. In diverse ways these choices are informed by a discontentment with the Cartesian split of mind and body as well as the picture theory of language. Yet, naturalism endures as a template, an expectation, and sometimes a specter with and against which much representational work in science is done. What STS scholars have learnt about representation in laboratory and expert settings still awaits being employed more comprehensively for making sense of practices beyond the lab, especially in contested political, social and ecological environments. In setting out to do so, they ought to reflect on the kinds of logic that their practices of representing representation enact.

Today, we are in the midst of a rapid development of digital technologies. Following this development in our communicative infrastructure, many far-reaching claims about the promises of multimedia learning have been, and are still, made. For instance,in research on multimedia and interactive learning environments one will typically find claims to the effect that modern technologies offer radically new and innovative forms of presenting and communicating information. These instructional technologies are sometimes claimed to be interactive, to have real-time features, to offer rich animations in a multimodal environment and so forth. Such descriptions, however, risk oversimplifying and concealing much of the variation that characterise the use of technologies.
  Accordingly, one aim of this thesis is to go beyond the employment of general categories and abstract analytical concepts when discussing the relation between technologies and learning.Through four separate studies,practical actions and practical reasoning performed in technology-mediated learning environments are scrutinized.The outcomes of the empirical investigations are illustrations of some of the aspects that can go unnoticed if handling these matters in the abstract.
  As a theoretical contribution in the longstanding debate on human knowing, the research further illustrates how human reasoning is dependent on tools. One general observation is that when people are familiar with a particular tool (e.g., maps), they can accomplish sophisticated modes of reasoning that they seem unable to perform without such support in external devices. At a methodological level, the results point to the gains of investigating the interactions between people, and between people and technologies. Some concrete aspects of the interaction with explicit pedagogical consequences are attended to. In one analysis, it is shown how the use of a visually driven learning environment can become an interactive puzzle that keeps the students in a local and non-conceptual world. The results suggest that the mastery of conceptual knowledge that the students develop is tied to local features of the situation that they operate in. A different analysis shows how two instructional technologies – which have been described in similar terms – afforded different courses of action. It is argued that this difference is of crucial importance for what experiences the students had and, hence, for what they learned.

In this essay, I reflect on the significance of 'the turn to practice' for contemporary philosophy of science. After briefly characterizing the practice turn and its inherent challenges, I discuss chemistry's periodic law, drawing on its establishment in the nineteenth century to illustrate how attention to practice is relevant for understanding scientific representation, and considering the subsequent entrenchment of the periodic table within chemistry to argue for the inter-relation between representation and explanation. I suggest this example's significance is best appreciated by taking a functional perspective on scientific explanation and conclude by highlighting philosophical gains enabled by attention to practice.

Representationalism—the view that scientific modeling is best understood in representational terms—is the received view in contemporary philosophy of science. Contributions to this literature have focused on a number of puzzles concerning the nature of representation and the epistemic role of misrepresentation, without considering whether these puzzles are the product of an inadequate analytical framework. The goal of this paper is to suggest that this possibility should be taken seriously. The argument has two parts, employing the “can’t have” and “don’t need” tactics drawn from philosophy of mind. On the one hand, I propose that representationalism doesn’t work: different ways to flesh out representationalism create a tension between its ontological and epistemological components and thereby undermine the view. On the other hand, I propose that representationalism is not needed in the first place—a position I articulate based on a pragmatic stance on the success of scientific research and on the feasibility of alternative philosophical frameworks. I conclude that representationalism is untenable and unnecessary, a philosophical dead end. A new way of thinking is called for if we are to make progress in our understanding of scientific modeling.

Representational views of the mind traditionally face a skeptical challenge on perceptual knowledge: if our experience of the world is mediated by representations built upon perceptual inputs, how can we be certain that our representations are accurate and our perceptual apparatus reliable? J. J. Gibson's ecological approach provides an alternative framework, according to which direct perception of affordances does away with the need to posit internal mental representations as intermediary steps between perceptual input and behavioral output. Gibson accordingly spoke of his framework as providing " reasons for realism. " In this paper I suggest that, granting Gibson his reasons for perceptual realism, the Gibsonian framework motivates anti-realism when it comes to scientific theorizing and modeling. If scientists are Gibsonian perceivers, then it makes sense to take their use of models in indirect investigations of real-world phenomena not as representations of the phenomena, but rather as autonomous tools with their own affordances.

In this text I develop the thesis that geometrical diagrams are depictions, not symbols; they depict geometrical objects, concepts or states of affairs. Besides developing this claim, I will defend it against three recent challenges from (Sherry 2009), Macbeth (2009, 2010, 2014) and (Panza 2012). First, according to Sherry, diagrams are not depictions, because no single depict can depict more than one thing, yet a single geometrical diagram can represent different geometrical figures in different contexts. I will argue that, once we recognize that resemblance underdetermines depiction, we can see that pictures can indeed depict different thing in different contexts and, consequently, there is nothing surprising about a single diagram depicting different geometrical figures. Next, I will defend it against a similar argument by Macbeth, according to which diagrams can represent different geometrical figures, even within the context of a single geometrical proof. Finally, I will defend it against Panza’s argument that there are essentially spatial features that geometrical objects have only insofar as they inherit them from the diagrams that represent them, and this is incompatible with the hypothesis that geometrical diagrams are depictions for depictions inherit their visual and spatial properties from the objects they represent, and not the other way around. In response, I will argue that once we understand the sense in which subjects are metaphysically prior to their depiction, we will see that my claim that Euclidean diagrams are depictions is not incompatible with Panza’s thesis.

In his Scientific Representation. Paradoxes of Perspective (2008), Bas van Fraassen offers a pragmatic account of scientific representation and representation tout court. In this paper I examine the three conditions for a user to succeed in representing a target in some context: identification of the target of the representational action, representing the target as such and such and correctly representing it in some respects. I argue that success on these three counts relies on the supposed truth of some predicative assertions, and thus that truth is more fundamental than representation. I do this in the framework of a version of the so-called " structural " account of representation according to which the establishment of a homomorphism by the user between a structure abstracted from the intended target and some relevant structure of the representing artefact is a necessary (although certainly not sufficient) condition of success for representing the target in some respects. Finally, on the basis of a correspondence view (not theory) of truth, I show that it is possible to address what van Fraassen calls " the loss of reality objection ". In his book Scientific Representation. Paradoxes of Perspective (2008) Bas van Fraassen offers a philosophical analysis of representation which is both empiricist and pragmatic. To represent is to perform some kind of action, and actions are evaluated with respect to their success or failure in attaining specific goals. Moreover, in science success or failure in representing a target must be assessed on the basis of observable phenomena. As is well known, according to van Fraassen, science aims at empirical adequacy, that is, at saving the phenomena. Thus, a scientific theory is successful if we have good reasons to believe that it saves the phenomena within its domain. Since for van Fraassen scientific theories are models in the first place, a theory is successful if its empirical parts, called " empirical substructures " , adequately represent the phenomena within its domain. A satisfactory account of representation is thus central to van Fraassen's philosophy of science. The success of a representational action can be evaluated on three counts. First, the user of a representing artefact must succeed in identifying its target or referent. Second, the target is always represented from a certain perspective as having such and such properties. Third, we may ask if our representing activity conveys some reliable information about its target or, in other words, if our representing artefact (a scientific model for example) is adequate or accurate to its target in some respects.

What do the following social practices have in common: children playing with dolls houses or Lego bricks and scientists building and using models to examine how the world works? More than one might think, according to a fascinating new book by Adam Toon. Scientists spend a lot of time building, using and revising models of di erent parts of the world, from subatomic particles to the solar system, world history or the international system (if you count social scientists such as this reviewer). So what models are, and how they represent the world, is in many ways an important question. Adam Toon in Models as Make-Believe o ers a lucid and stimulating argument that deserves to be read widely, inside as well as outside philosophy. Although he concentrates on models in the natural sciences, his argument potentially pertains to knowledge production aimed at global challenges such as climate change and managing the world economy, where modelling is central. The following presents this reviewers' understanding of the key argument and suggests some implications for how we should view and treat models.

"Scientific representation is a currently booming topic, both in analytical philosophy and in history and philosophy of science. The analytical inquiry attempts to come to terms with the relation
between theory and world; while historians and philosophers of science aim to develop an account of the practice of model building in the sciences. This article provides a review of recent work within both traditions, and ultimately argues for a practice-based account of the means employed by scientists to effectively achieve representation in the modelling sciences."

This paper advances three related arguments showing that the ontic conception of explanation (OC), which is often adverted to in the mechanistic literature, is inferentially and conceptually incapacitated, and in ways that square poorly with scientific practice. Firstly, the main argument that would speak in favor of OC is invalid, and faces several objections. Secondly, OC's superimposition of ontic explanation and singular causation leaves it unable to accommodate scientifically important explanations. Finally, attempts to salvage OC by reframing it in terms of 'ontic constraints' just concedes the debate to the epistemic conception of explanation. Together, these arguments indicate that the epistemic conception is more or less the only game in town.

In this paper we study Language, Εmbodied Learning and other semiotic systems as an integral means through which students express emotions, reasoning and scientific meanings when they realize scientific theatrical performances. Four characteristics of Embodied Learning examined, those of gestures, whole body movements, emotional involvement and facial expressions combined with two semiotic systems, verbal communication and Art, as well as Analogical Reasoning. Our research question focuses on how students represent scientific contexts and if there is any connection between different semiotic systems, so as students can hold cognitive fields of each notion. Analyzing students' representations both by quantitative and qualitative methods and grounded theory as well as they performed the scientific theatrical performances, we focused on their scientific representations expressed a) verbally, b) through Embodied Learning, c) through Art and d) through Analogical Reasoning in order t...

In this essay the introduction of quantum mechanics into chemistry serves as a case study of representational innovation in science.  Because the basic complexity of quantum-mechanical representations of molecular systems eliminates the possibility of analytic solutions to the corresponding equations, approximation techniques and issues of computational tractability take center stage.  Largely abstract mathematical techniques must work hand in hand with significant pieces of pre-existing knowledge, both conceptual and empirical, to generate results of chemical significance.  An important consequence of this specific integration of mathematical techniques with pre-existing knowledge is the development of new, amalgamated chemical concepts that are not derived directly from quantum theory and yet are direct descendants of it.  This new conceptual repertoire is accompanied by a dramatic development in alternative representational resources, diagrammatic schemes, that allow the incorporation of the new chemical concepts into disciplinary contexts within chemistry that were essentially isolated from the original mathematical resources of quantum theory.

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.

This article provides a state of the art review of the philosophical literature on scientific representation. It first argues that the topic emerges historically mainly out of what may be called the modelling tradition. It then introduces a number of helpful analytical distinctions, and goes on to divide contemporary approaches to scientific representation into two distinct kinds, substantive and deflationary. Analogies with related discussions of artistic representation in aesthetics, and of the nature of truth in metaphysics are pursued. It is finally urged that the most promising approaches - and the ones most likely to feature prominently in future developments - are deflationary. In particular, a defence is provided of a genuinely inferential conception of representation.

En este trabajo me ocupo de un viejo tema: el de la carga valorativa del conocimiento científico. A lo largo de la historia diversos autores, como Max Weber y el Wittgenstein del Tractatus, han defendido un ideal, el de la “neutralidad valorativa” de la ciencia, que muchos han considerado un mito. Una estrategia reciente para poner en cuestión este mito, en lo tocante a las teorías científicas, lo proporciona el “realismo constructivo” de Ronald Giere y su original concepción de los modelos de la ciencia. Pues, partiendo de esa concepción de los modelos, Giere reconoce el papel que muy diversos valores e intereses, entre ellos valores e intereses no epistémicos, juegan en la construcción de la ciencia. Sin embargo, voy a defender (utilizando la analogía, que el propio Giere establece, entre los modelos científicos y los mapas) que el planteamiento de este autor acarrea algunas consecuencias indeseables, como una excesiva descarga normativa de la filosofía de la ciencia y una peligrosa desprotección frente al relativismo. Finalmente, propondré una corrección de la propuesta de Giere que evite dichos problemas.

ABSTRACT: The ontic conception of scientific explanation has been constructed and motivated on the basis of a putative lexical ambiguity in the term explanation. I raise a puzzle for this ambiguity claim, and then give a deflationary solution under which all ontically-rendered talk of explanation is merely elliptical; what it is elliptical for is a view of scientific explanation that altogether avoids the ontic conception. This result has revisionary consequences for New Mechanists and other philosophers of science, many of whom have assimilated their conception of explanation to the ontic conception.

Models in action – realising abstractions

This thesis is about mathematical modelling and technology development. While mathematical modelling has become widely deployed within a broad range of scientific practices, it has also gained a central position within technology development. The intersection of mathematical modelling and technology development is especially interesting because of its increasing role in applying scientific theoretical knowledge to concrete societal problems, and even more so, because it is a relatively little studied practice. Based on a multi-sited ethnographic study of an industrial energy-efficiency project, this thesis presents an analysis of the central practices that materialised representative physical modelling and implemented operational regulation models. In order to show how the project’s representative modelling and technology development connected physical theory with concrete problems through different material mediations, the thesis draws on the notion of re-presentation as used within science and technology studies to trace how the project translated between the various states of re-presentative mediations.
The first four chapters introduce the scope of the study and its wider theoretical outset, the existing literature on simulation models, and the study’s methodological and empirical approach. The purpose of this thesis is to describe the central practices that developed regulation technology for industrial production processes and to analyse how mathematical modelling contributed to this development. Because the variation between these practices spanned from work with physical theory to practical hands-on work with machines at operational production sites, the thesis aims to capture how these diverse practices operated and connected by closely following how they transformed and distributed knowledge artefacts.
Chapter 5 to 7 unfolds the empirical study structured as an investigation of two opposite processes that occurred simultaneously; one that “abstracted” the production machinery into theoretical physics (Chapter 5 and 6), and one that “concretised” theories onto the production machinery (Chapter 7). Mathematical models are especially interesting in this technology developing setup since they formed a significant part of both the processes that abstracted machinery and the processes that concretised theory and filled an important role in the coordination between these two opposite processes. By following each stage in both opposite processes, I seek to extend the existing comprehension of models’ technological and epistemological dimensions by describing the different material states the models went through from machine to theory and back again to the machine. 
Chapter 8 analyses and discusses the different effects that were generated by implementing the regulation model technology onto their target environments. The thesis results in a discussion of what kinds of displacement effects these novel technological solutions can be recognised to have generated. Structured around the intersections of certainty, agency, and dependences, the thesis’ findings are in chapter 9 extended to a discussion of the theoretical fundament through which we interpret the regulation project and its use of modelling. I demonstrate a novel framework that I term prescriptive application. Chapter 10 summarises and concludes on the recognitions that are drawn from the study.

Idealization is commonly understood as distortion: representing things differently than how they actually are. In this paper, we outline an alternative artifactual approach that does not make misrepresentation central for the analysis of idealization. We examine the contrast between the Hodgkin-Huxley (1952a, b, c) and the Heimburg-Jackson (2005, 2006) models of the nerve impulse from the artifactual perspective, and argue that, since the two models draw upon different epistemic resources and research programs, it is often difficult to tell which features of a system the central assumptions involved are supposed to distort. Many idealizations are holistic in nature. They cannot be locally undone without dismantling the model, as they occupy a central position in the entire research program. Nor is their holistic character mainly related to the use of mathematical and statistical modeling techniques as portrayed by Rice (2018, 2019). We suggest that holistic idealizations are implicit theoretical and representational assumptions that can only be understood in relation to the conceptual and representational tools exploited in modeling and experimental practices. Such holistic idealizations play a pivotal role not just in individual models, but also in defining research programs.

The goal of this chapter is to lay some foundational groundwork in the study of epistemic representations in general, and visual epistemic representations in particular. To this goal, I introduce three helpful and closely related distinctions: The first one is a distinction between the constraints imposed on a tool by the task it is intended to help perform, and the constraints imposed by its intended user. The second is a distinction between a representation’s proximate function (to represent something), and its remote function, which could be epistemic, aesthetic, etc. Finally, the third one is a distinction between interpreting and applying a representation, that is, between determining how things are according to the representation, and determining whether things actually are as they are represented to be. I illustrate the usefulness of these distinctions by applying them to a couple of examples: a case of photo finish and a diagram of Euclidean Geometry.

In 1890, in Paris, a text entitled « Des formes extérieures du Cachalot » was published, signed by G. Pouchet and F.-A. Chaves and illustrated with three drawings and three photographs. These are advertised as “the first scientific photographs of the whale.” Through them it is finally possible to “fix the exterior features of this animal, as famous as poorly known” and therefore, as stated in the opening, ending a long era of inaccurate representations. The authors of the article are two reputed naturalists : Charles Henri Georges Pouchet (1833-1894), and the Azorean Francisco Afonso Chaves (1857-1926). Afonso Chaves is also a remarkable photographer whose work, mostly stereoscopic, remained unknown until recently. The aim of this paper is to analyse the photographs of Francisco Afonso Chaves and realize why they play a central role in the publication of 1890. As emphatically stressed by Georges Pouchet, they constitute the first scientific representations of a species hitherto poorly understood and poorly visually represented. But ultimately, what makes these photographs scientific? And how does the visual and the visible mingle in these images?

DSGE models (Introduction) have recently been criticized by P. Romer (2016) as pseudoscientific (Section 1). Their dominance is attributed to the uncritical " deference to authority " that has dominated macroeconomics " for the last 30 years ". In contrast, the paper aims to support the widespread view that – their problems notwithstanding – DSGE models meet the epistemic standards of scientific research. The argument turns on the recent advancements in theories of scientific representation (Section 1) and of empirical grounding (Section 2). The latter is illustrated with a historical case, which also substantiates Romer's constructive point on the role of theory in design of measurements.

Scientific models share one central characteristic with fiction: their relation to the physical world is ambiguous. It is often unclear whether an element in a model represents something in the world or presents an artifact of model building. Fiction, too, can resemble our world to varying degrees. However, we assign a different epistemic function to scientific representations. As artifacts of human activity, how are scientific representations allowing us to make inferences about real phenomena? In reply to this concern, philosophers of science have started analyzing scientific representations in terms of fictionalization strategies. Many arguments center on a dyadic relation between the model and its target system, focusing on structural resemblances and “as if” scenarios. This chapter provides a different approach. It looks more closely at model-building to analyze the interpretative strategies dealing with the representational limits of models. How do we interpret ambiguous elements in models? Moreover, how do we determine the validity of model-based inferences to information that is not an explicit part of a representational structure? I argue that the problem of ambiguous inference emerges from two features of representations, namely their hybridity and incompleteness. To distinguish between fictional and non-fictional elements in scientific models my suggestion is to look at the integrative strategies that link a particular model to other methods in an ongoing research context. To exemplify this idea, I examine protein modeling through X-ray crystallography as a pivotal method in biochemistry.

This is the story of a material translation between architecture and science in postwar Britain in which specific materials were imported from architecture to virus structure research, mediating narratives related to building that resonated beyond laboratory walls.

In postwar decades, scientists using the technique of X-ray crystallography were examining matter at its smallest scale yet: the sub-visible arrangements of atoms in molecules. This process involved three-dimensional models as an integral research tool. In the early 1960s Birkbeck crystallographer Aaron Klug’s research on the structure of viruses was altered by the introduction of two new modelling materials to his work: architect R. Buckminster Fuller’s geodesic domes and his plastic Geo-D-Stix construction toy. Their specific components - plastic straws and steel rods - became models for the submicroscopic units of virus shells. The affordances of domes and Geo-D-Stix were associated with both children and an infantalised vision of ‘unskilled’ Afghani builders who assembled Fuller’s airlifted dome components at the 1956 International Trade Fair in Kabul, a site the perceived foreignness of which mirrored the mysterious realm of the virus. In their translation into X-ray crystallography, Fuller’s materials became embedded in scientific narratives of the virus’s capacity for ‘self–assembly’. Here, concerns about ‘efficient’ production methods and design converge, speaking not only to new scientific notions of life but also to concerns about postwar housing.

Recent contributions to the philosophical literature on scientific modeling have tended to follow one of two approaches, on the one hand addressing conceptual, metaphysical and epistemological questions about models, or, on the other hand, emphasizing the cognitive aspects of modeling and accordingly focusing on model-based reasoning. In this paper I explore the relationship between these two approaches through a case study of model-based research on the behavior of infant rats, particularly thigmotaxis (movement based on tactile sensation) and temperature regulation in groups. A common assumption in the philosophical literature is that models represent the target phenomena they simulate. In the modeling project under investigation, however, this assumption was not part of the model-based reasoning process, arising only in a theoretical article as, I suggest, a post hoc rhetorical device. I argue that the otherwise nonexistent concern with the model-target relationship as being representational results from a kind of objectification often at play in philosophical analysis, one that can be avoided if an alternative form of objectification is adopted instead.

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 of the development of our understanding of the photoelectric effect.

In this paper we study Language, Embodied Learning and other semiotic systems as an integral means through which students express emotions, reasoning and scientific meanings when they realize scientific theatrical performances. Four characteristics of Embodied Learning examined, those of gestures, whole body movements, emotional involvement and facial expressions combined with two semiotic systems, verbal communication and Art, as well as Analogical Reasoning. Our research question focuses on how students represent scientific contexts and if there is any connection between different semiotic systems, so as students can hold cognitive fields of each notion. Analyzing students’ representations both by quantitative and qualitative methods and grounded theory as well as they performed the scientific theatrical performances, we focused on their scientific representations expressed a) verbally, b) through Embodied Learning, c) through Art and d) through Analogical Reasoning in order to ma...

Each revolution in brain science prompts mechanistic explanations of the mind. These are inevitably followed by a “holistic” reaction that argues against a one-to-one correspondence between a brain organ, region, or pro- cess and a cognition. From the beginning of the 20th century, imaging tech- nologies, behaviorism and, later, computational models have all been met with holistic responses from gestalt theory to cognitive science to embodied, enactive and environmental theories of cognition. Neglected in such debates so far has been the way these research cultures employ different forms of sci- entific representation. Making use of recent debate on the nature of scientific representation, this article uses research from psycholinguistics, classic works of gestalt and related theories, and embodied cognitive science to argue that gestalt-type models represent more rigorous forms of scientific representa- tion that yet have limitations in their relevance. Computational models, on the other hand, are flawed forms of representation that use hybrid forms to impose logical structure or necessity on concrete neural structures. Data in- dicate there is support for both models, so it is hoped that further research will be done to clarify the role of representation as a construct that shapes both theory and research practice.

Callender and Cohen (2006) 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 the 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.

In this essay, I shall show that the so-called inferential and interpretational (Contessa 2007) accounts of scientific representation are respectively unsatisfactory and too weak to account for scientific representation (pars destruens). Along the way, I shall also argue that the pragmatic similarity (Giere 2004 and Giere 2010) and the partial isomorphism (da accounts are unable to single out scientific representation. In the pars construens I spell out a limiting case account which has explanatory surplus vis a`vis the approaches which I have previously reviewed. My account offers an adequate treatment of scientific representation, or so I shall try to argue. Central to my account is the notion of a pragmatic limiting case, which will be characterized in due course.

The thesis proposes an account of the means of scientific representation focused on similarity, or more specifically, on the notion of “creative similarity”. I first distinguish between two different questions regarding the problem of representation: the question about the constituents and the question about the means of representation (following Suárez 2003; van Fraassen 2008). I argue that, although similarity is not a good candidate for constituent of representation, it can satisfactorily answer the question about the means of representation if adequately characterized. To motivate this position, I dispute the main arguments offered against similarity as means of representation, namely the arguments from variety, vagueness, and misrepresentation, and contend that similarity plays a central epistemic role in practices of representing in science. The study of the role of similarity in scientific practice, I argue, requires the analysis of the uses of judgments of similarity in the construction of scientific models. I examine the cases of the Mississippi Basin Model and the San Francisco Bay Model to illustrate how judgments of similarity are directly involved in the production of epistemically fruitful models. Informed by the practical investigation developed throughout the thesis, I finally outline what I call the creative similarity account of the means of representation. The notion of “creative similarity” helps to capture the way in which similarity, as means of representation, intervenes in actual practices of representing, namely, in the form of a productive interplay of judgments of similarity and distortions (i.e. idealizations, abstractions, simplifications), which is employed by resourceful agents with the aim of understanding aspects of the natural world.

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 perspective
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.

Las simulaciones computacionales constituyen el principal campo de pruebas virtual en múltiples ciencias, una práctica distintiva con respecto al Representar e Intervenir que Hacking proponía en 1983. Estas no solamente constituyen una herramienta de cálculo, sino que también suponen una metodología de investigación en sí misma. A través de ellas se pueden recrear tecnomundos virtuales que sustituyen como objeto de estudio a sistemas naturales experimentalmente inaccesibles, como el cambio climático o fenómenos astrofísicos. Este artículo analiza la posibilidad de considerar este tipo de simulaciones como objetos de controversia superpuestos al debate del realismo científico. Para ello, se parte de la caracterización de Hacking, adoptando una perspectiva praxeológica y focalizándose en aquellas con potencial explicativo causal. Finalmente, se analiza la aplicabilidad de los argumentos de la intervención y la correspondencia múltiple de representaciones, analizando las diferencias y analogías entre la práctica de observar con microscopios y la práctica de simular con tecnología computacional.

Biologists use tree diagrams to illustrate phylogenetic relationships among species. However, both novices and experts are prone to misinterpret this notational form. A difficulty with reasoning with cladograms is that intuitive narrative conceptions of evolution as a linear progression interfere with perceiving the hierarchical relationships that tree diagrams are intended to convey. We challenge the use of standard cladograms to teach phylogenetic reasoning and attempt to disentangle the effects of content beliefs, conceptual metaphors, and visual structure. We explain how and why students misinterpret cladograms and investigate the effects of alternative, more intuitive representations and approaches. Through clinical interviews with 24 undergraduate students. Study 1 describes students’ invented representations for depicting the concept of relatedness and investigates the impacts of recontextualizing their representational activities within non-evolutionary contexts. Study 2 examines the effects on students’ reasoning with the standard cladogram after they first invent a diagram of their own. Findings from our mixed quantitative and qualitative analyses display the range of representational resources that students bring to the task of reasoning about relatedness. They suggest potential value in building upon such representations when teaching novices to reason about phylogenies. We observed that the quality of students’ reasoning differed depending on whether students invented a representation, what kind they invented, and in what context. While some findings are promising, others reaffirm the powerful influence of Gestalt perceptual processes on students’ misinterpretations of these difficult, but critical scientific diagrams. We end by discussing implications for instructors and designers.

In this paper, I attempt to sketch a dialectical approach on scientific representations and their role in scientific cognition. In my understanding, scientific representations can be construed as ‘tools’ mediating scientific cognition. These ‘tools’ are products of our cognitive activity, by which we signify which features of certain objects or states of affairs should be embodied in abstractive representations of them. In such a context, I explore the merits of bringing some ideas of thinkers whose work is underestimated in the relevant discussion nowadays (such as K. Marx, E.V. Ilyenkov, L.S. Vygotsky, M. Wartofsky) in dialogue with currently discussed approaches.

What does it take for a scientific model to represent? Models, as an integral part of scientific practice, are historically and contextually bound in their application. Practice-oriented debates in recent philosophy of science have emphasised how models can be said to act as representations in practice, e.g., as “mediators” between theory and data. However, the questions that remain open are: what exactly is it that is represented by a scientific model, and in which sense can we speak of a representation? I argue that the proper object of representation in scientific practice is not a model as such but, rather, the entire experimental system in which a model is an active part. The implication of my claim is a strongly historicized perspective on the capacity models to represent: the capacity of a model to represent must be judged against the individual life of an experimental system. In support of my argument, I turn to modelling issues in fragrance chemistry regarding the molecular basis of odors. Explanations of irregularities in the pursuit of so-called structure-odor relations provide an interesting example to analyze the modelling strategies that inform the notion of chemical similarity.

This thesis starts with three challenges to the structuralist accounts of applied mathematics. Structuralism views applied mathematics as a matter of building mapping functions between mathematical and target-ended structures. The first challenge concerns how it is possible for a non-mathematical target to be represented mathematically when the mapping functions per se are mathematical objects. The second challenge arises out of inconsistent early calculus, which suggests that mathematical representation does not require rigorous mathematical structures. The third challenge comes from renormalisation group (RG) explanations of universality. It is argued that the structural mapping between the world and a highly abstract minimal model adds little value to our understanding of how RG obtains its explanatory force. I will address the first and second challenges from the similarity perspective. The similarity account captures representations as similarity relations, providing a more fle...

After a brief presentation of what I  believe to be the main features of the modelling demarche in science, I will focus on the basic following question: how can an abstract entity – a model – possibly represent an existing observable entity, which is phenomenally accessible to us, but which is not abstract? This is what Bas van Fraassen calls “the loss of reality objection.” Instead of proposing a pragmatic dissolution of this objection as van Fraassen does, I will argue that scientific representing necessarily involves a homomorphism between structures and thus that, in a strict technical sense of representation, phenomena are not represented by our models but only as having some specific properties belonging to the domains of our representing structures. Yet, our contact with phenomenal entities is secured by propositions that are true in a correspondence sense. The truth of these – ontic – propositions which state that that phenomenal entities possess some precise properties are the soil on which the informative content of our successful representations rest.

This short paper grew out of an observation—made in the course of a larger research project—of a surprising convergence between, on the one hand, certain themes in the work of Mary Hesse and Nelson Goodman in the 1950/60s and, on the other hand, recent work on the representational resources of science, in particular regarding model-based representation. The convergence between these more recent accounts of representation in science and the earlier proposals by Hesse and Goodman consists in the recognition that, in order to secure successful representation in science, collective representational resources must be available. Such resources may take the form of (amongst others) mathematical formalisms, diagrammatic methods, notational rules, or—in the case of material models—conventions regarding the use and manipulation of the constituent parts. More often than not, an abstract characterization of such resources tells only half the story, as they are constituted equally by the pattern of (practical and theoretical) activities—such as instances of manipulation or inference—of the researchers who deploy them. In other words, representational resources need to be sustained by a social practice; this is what renders them collective representational resources in the first place.

After a brief presentation of what I take to be the representational démarche in science, I stress the fundamental role of true judgements in model construction. The success and correctness of a representation rests on the truth of judgements which attribute properties to real targeted entities, called "ontic judgements". I then present what van Fraassen calls "the Loss of Reality objection". After criticizing his dissolution of the objection, I offer an alternative way of answering the Loss of Reality objection by showing that the contact of our models with reality is grounded on the truth of ontic judgements. I conclude by examining the consequence of this view on the issue of scientific realism.

This article argues in favour of an inferential role for fictions in scientific modelling. The argument proceeds by means of a detailed case study, namely models of the internal structure of stars in stellar astrophysics. The main assumptions in such models are described, and it is argued that they are best understood as useful fictions. The role that conditionals play in these models is explained, and it is argued that fictional assumptions play an important role as either background or antecedent conditions. I then expand on the argument for the compatibility of fictions and scientific realism. I argue that realism and antirealism plausibly offer correspondingly different accounts of the semantics of these fictional conditionals.

within the philosophy of science, with many papers published regularly on the topic every year, and several yearly conferences and workshops on related topics. Historically the topic originates in two different strands in 20 th century philosophy of science. One strand begins in the 1950s with philosophical interest upon the nature of scientific theories. As the received or 'syntactic' view gave way to a "semantic" or "structural" conception, representation progressively gained the centre stage. Yet, there is another, older, strand that links representation to fin de siècle modelling debates, particularly in the emerging 'bildtheorie' of Boltzmann and Hertz, and to the ensuing discussion amongst philosophers

This paper presents an exploratory study of the representations of science and scientists in online debates about Global Warming between non-scientists. We analysed qualitatively and in an comprehensive manner the exchanges held in two websites discussing so-called "skeptic" theses. Results show that debates occur in very small and active communities that develop quite well-structured argumentation. Skeptics claim to produce a true scientific discourse, and develop a representation where science skeptical scientists embody the scientific ideal face of scientific institutions and researchers perceived as corrupted and driven by ideology. Opponents to skeptical positions highlight sêcific mechanisms of the scientific literature to deny to skeptics the status of experts.