Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization that was developed to address just this sort of epistemic opacity. The (...) visualization is unusual in that it depicts the dynamics and structure of a computer model instead of that model’s target system, and because it is generated algorithmically. Using considerations from epistemology and aesthetics, we explore how this new kind of visualization increases scientific understanding of the content and function of computer models in systems biology to reduce epistemic opacity. (shrink)

The evaluation of universities from different perspectives is important for their scientific development. Analyzing the scientific papers of a university under the bibliometric approach is one main evaluative approach. The aim of this study was to conduct a bibliometric analysis and visualization of papers published by Hamadan University of Medical Science (HUMS), Iran, during 1992-2018. This study used bibliometric and visualization techniques. Scopus database was used for data collection. 3753 papers were retrieved by applying Affiliation Search (...) in Scopus advanced search section. Excel and VOSviewer software packages were used for data analysis and bibliometric indicator extraction. An increasing trend was seen in the numbers of HUMS's published papers and received citations. The highest rate of collaboration in national level was with Tehran University of Medical Sciences. Internationally, HUMS's researchers had the highest collaboration with the authors from the United States, the United Kingdom and Switzerland, respectively. All highly-cited papers were published in high level Q1 journals. Term clustering demonstrated four main clusters: epidemiological studies, laboratory studies, pharmacological studies, and microbiological studies. The results of this study can be beneficial to the policy-makers of this university. In addition, researchers and bibliometricians can use this study as a pattern for studying and visualizing the bibliometric indicators of other universities and research institutions. (shrink)

Just before the Scientific Revolution, there was a "Mathematical Revolution", heavily based on geometrical and machine diagrams. The "faculty of imagination" (now called scientific visualization) was developed to allow 3D understanding of planetary motion, human anatomy and the workings of machines. 1543 saw the publication of the heavily geometrical work of Copernicus and Vesalius, as well as the first Italian translation of Euclid.

Bioinformatics scientists often describe their own scientific activities as the practice of working with large amounts of data using computing devices. An essential part of their self-identification is also the development of ways to visually represent the results of this work. Some of these methods are aimed at building convenient representations of data and demonstrating patterns present in them (graphics, diagrams, graphs). Others are ways of visualizing objects that are not directly accessible to human perception (microphotography, X-ray). Both the (...) construction of visualizations and (especially) the creation of new computer visualization methods are considered in bioinformatics as significant scientific achievements. Representations of the three-dimensional structure of protein molecules play a special role in the inquiries of bioinformatics scientists. 3D-visualization of a macromolecule, on the one hand, is, like a graph, a representation of the results of computer processing of data arrays obtained by material methods – spatiotemporal coordinates of structural elements of the molecule. On the other hand, like microphotography, these 3D structures should serve as accurate representations of specific scientific objects. This leads to the parallel existence of two contradictory epistemic regimes: creative arbitrariness in making convenient, communicatively successful models, is combined with commitment to the object “as it really is”. The paradox is reinforced by the fact that the scientific study of objects in question (determining the properties of the structure, its functions, comparison with other structures) by means of computers does not require visualization at all. Its obviously high value for bioinformatics does not look justified if we take into account the prominent artificiality and artistry of the resulting images. However, the status of these images becomes clearer if we relate them to earlier notions of the role of the visual in scientific discovery. The highest estimation of visualization as the final result of scientific research was characteristic of Renaissance science. The artistic representation of ideal essential properties, instead of a strict correspondence to a particular biological object, is an epistemic virtue typical of the naturalists of the 17th and 18th centuries. Both suggested a close collaboration between the scientist and the artist; and standards for visualizing macromolecules in bioinformatics grow out of a similar collaboration (Geis’ drawings). The desire for maximum accuracy and detail inherits the regulation of “mechanical objectivity” (as Daston and Galison put it into words), for which it is also important to eliminate humans from the image production process (in bioinformatics, to transfer these functions to computer programs). Thus, 3D-visualization of protein structures bears traces of historically different value orientations, but the scientific practice of the 20th and 21st centuries, supplemented by computer technologies, allows them to be intertwined in particular disciplinary units. (shrink)

This paper explores the extent to which a scientific framework for visualization might be possible. It presents several potential parts of a framework, illustrated by application to the visualization of correlation in scatterplots. The first is an extended-vision thesis, which posits that a viewer and visualization system can be usefully considered as a single system that perceives structure in a dataset, much like "basic" vision perceives structure in the world. This characterization is then used to suggest (...) approaches to evaluation that take advantage of techniques used in vision science. Next, an optimal-reduction thesis is presented, which posits that an optimal visualization enables the given task to be reduced to the most suitable operations in the extended system. A systematic comparison of alternative designs is then proposed, guided by what is known about perceptual mechanisms. It is shown that these elements can be extended in various ways—some even overlapping with parts of vision science. As such, a science of some kind appears possible for at least some parts of visualization. It would remain distinct from design practice, but could nevertheless assist with the design of visualizations that better engage human perception and cognition. (shrink)

The essay advocates for diverse approaches in presenting a researcher's scientific contributions in a project. Taking inspiration from sports journalism and its visualization of football players' data, the essay suggests that a radar plot, incorporating CRediT contributor role data, enables multiple authors of a scientific paper to illustrate their contributions in a more specific manner. The suggested method, though subject to bias reporting, pays credit to different aspects of a research project, from conceptualization, analysis, administration, to writing (...) and revising. It not only enables both academics and lay readers to better understand the considerable amount of work required in every project but also calls for the need to employ diverse viewpoints in science. (shrink)

‘Visualisations play an important role in science’, this seems to be an uncontroversial statement today. Scientists not only use visual representations as means to communicate their research results in publications or talks, but also often as surrogates for their objects of interest during the process of research. Thus, we can make a distinction between two contexts of usage here, namely the explanatory and the exploratory context. The focus of this paper is on the latter one. Obviously, using visualisations as surrogates (...) for their objects of depiction presupposes the assumption that the former can tell us something relevant about the latter. Thus, a particular referential relation between object and image has to be assumed that can transfer the relevant information. Furthermore, as science is a collaborative enterprise – a social activity – this information has to be intersubjectively accessible and stable. Nonetheless, philosophers of science still quarrel about the epistemic and ontological status of such visualisations. After all, they are means to visualise theoretical entities, such as the Higgs Boson, i.e. entities that are principally not observable with the unaided eye. Especially the significant reliance on information technology devices to access this world of the unobservable provokes a lot of suspicion with regard to the referential status of such visualisations. In this sense, quite a few philosophers adopt social constructivism as an explanatory hypothesis. A particular image is constructed with the aid of instruments and theoretical assumptions; hence it does not refer to an entity outside this system. In this paper, I will critically analyse this assumption and try to argue for an alternative point of view. (shrink)

The main purpose of this dissertation is to examine critically and discuss the role of imagination in science and religion, with particular emphasis on its possible epistemic, creative, and meaning-making functions. In order to answer my research questions, I apply theories and concepts from contemporary philosophy of mind on scientific and religious practices. This framework allows me to explore the mental state of imagination, not as an isolated phenomenon but, rather, as one of many mental states that co-exist and (...) interplay in our cogntive architecture. Based on the philosophical discourse of philosophy of mind, four types of imagination are indentified and conceptualized: sensory, propositional, experiential, and creative imagination. These categories are then employed on five phenomena that can be found in scientific and religious environments: metaphors, models, thought experiments, aspect perception, and - in the religious case - rituals. In relation to the concept of religious "seeing" I consider how imaginings may influence visionary experiences and visualization, and compare these phenomena with cases of scientific visualization and eureka experiences. In regard to scientific and religious models, a distinction is made between, on the one hand, two notions of truth and, on the other hand, truth-independent meaning-making. In light of these categories, I differentiate between, and critically discuss, the use of imagination in doxastic, non-doxastic and fictionalist accounts. In light of this investigation, I formulate and defend the position of interactivism, which acknowledges a constant interplay between different attitudes and mental states. In my examination of rituals and scientific and religious thought experiments, special attention is given to the mental capacity to recreate the experiences that are entailed in an imagined scenario. At the end of the investigation, I consider the possible impact that my study might have on how we view science and religion as well as the dialogue bewteen these two fields. (shrink)

List of Illustrations Introduction 1 The Didactic and the Elegant: Some Thoughts on Scientific and Technological Illustrations in the Middle Ages and Renaissance 3 2 Temples of the Body and Temples of the Cosmos: Vision and Visualization in the Vesalian and Copernican Revolutions 40 3 Descartes’s Scientific Illustrations and ’la grande mecanique de la nature’ 86 4 Illustrating Chemistry 135 5 Representations of the Natural System in the Nineteenth Century 164 6 Visual Representation in Archaeology: Depicting the (...) Missing-Link in Human Origins 184 7 Towards an Epistemology of Scientific Illustration 215 8 Illustration and Inference 250 9 Visual Models and Scientific Judgment 269 10 Are Pictures Really Necessary? The Case of Sewall Wright’s ’Adaptive Landscapes’ 303 Bibliography 339 Notes on Contributors 373 Index 377. (shrink)

Statistics play a critical role in biological and clinical research. However, most reports of scientific results in the published literature make it difficult for the reader to reproduce the statistical analyses performed in achieving those results because they provide inadequate documentation of the statistical tests and algorithms applied. The Ontology of Biological and Clinical Statistics (OBCS) is put forward here as a step towards solving this problem. Terms in OBCS, including ‘data collection’, ‘data transformation in statistics’, ‘data visualization’, (...) ‘statistical data analysis’, and ‘drawing a conclusion based on data’, cover the major types of statistical processes used in basic biological research and clinical outcome studies. OBCS is aligned with the Basic Formal Ontology (BFO) and extends the Ontology of Biomedical Investigations (OBI), an OBO (Open Biological and Biomedical Ontologies) Foundry ontology supported by over 20 research communities. We discuss two examples illustrating how the ontology is being applied. In the first (biological) use case, we describe how OBCS was applied to represent the high throughput microarray data analysis of immunological transcriptional profiles in human subjects vaccinated with an influenza vaccine. In the second (clinical outcomes) use case, we applied OBCS to represent the processing of electronic health care data to determine the associations between hospital staffing levels and patient mortality. Our case studies were designed to show how OBCS can be used for the consistent representation of statistical analysis pipelines under two different research paradigms. By representing statistics-related terms and their relations in a rigorous fashion, OBCS facilitates standard data analysis and integration, and supports reproducible biological and clinical research. (shrink)

When considering the question of possible transformation and disappearance of scientific objects, it is useful to distinguish between epistemic and technical objects. This paper presents preliminary observations and offers a typology of obsolescence. It is based on several case studies drawn from the history of life sciences. The paper proceeds as follows: first, the dynamics of epistemic objects is considered through the examples of Carl Correns’ study of “xenia”, Alfred Kühn’s work on physiological developmental genetics, and Paul Zamecnik’s research (...) on the protein biosynthesis. Second, the phasing out of technical objects is then separately discussed and illustrated by the example of radioactive tracing in biology – until recently, an established technique of visualization. (shrink)

This article analyzes the value of geometric models to understand matter with the examples of the Platonic model for the primary four elements (fire, air, water, and earth) and the models of carbon atomic structures in the new science of crystallography. How the geometry of these models is built in order to discover the properties of matter is explained: movement and stability for the primary elements, and hardness, softness and elasticity for the carbon atoms. These geometric models appear to have (...) a double quality: firstly, they exhibit visually the scientific properties of matter, and secondly they give us the possibility to visualize its whole nature. Geometrical models appear to be the expression of the mind in the understanding of physical matter. (shrink)

Philosophers have relied on visual metaphors to analyse ideas and explain their theories at least since Plato. Descartes is famous for his system of axes, and Wittgenstein for his first design of truth table diagrams. Today, visualisation is a form of ‘computer-aided seeing’ information in data. Hence, information is the fundamental ‘currency’ exchanged through a visualisation pipeline. In this article, we examine the types of information that may occur at different stages of a general visualization pipeline. We do so (...) from a quantitative and a qualitative perspective. The quantitative analysis is developed on the basis of Shannon’s information theory. The qualitative analysis is developed on the basis of Floridi’s taxonomy in the philosophy of information. We then discuss in detail how the condition of the ‘data processing inequality’ can be broken in a visualisation pipeline. This theoretic finding underlines the usefulness and importance of visualisation in dealing with the increasing problem of data deluge. We show that the subject of visualisation should be studied using both qualitative and quantitative approaches, preferably in an interdisciplinary synergy between information theory and the philosophy of information. (shrink)

The article proposes systematisation and development of the discourse of the East European methodological traditions regarding application of the systematic approach as a way of subject localisation in psychological research. In particular, the author’s version of systematic localisation of psychological research subjects by means of structural and ontological visualisations has been developed. The procedure proposed for systematic localisation of the researched subject includes four subsequent stages: 1) fixation of the borders and structure of the ontological field which is being studied; (...) 2) segment analysis of the obtained structure; 3) study of specifics and contents of structural and functional ties; 4) visual mapping of genesis of the core processes. The article describes specifics of application of systematic localisation of the subject of research at the example of such researched object as personal socialisation. (shrink)

Traditionally, vision science and information/data visualization have interacted by using knowledge of human vision to help design effective displays. It is argued here, however, that this interaction can also go in the opposite direction: the investigation of successful visualizations can lead to the discovery of interesting new issues and phenomena in visual perception. Various studies are reviewed showing how this has been done for two areas of visualization, namely, graphical representations and interaction, which lend themselves to work on (...) visual processing and the control of visual operations, respectively. The results of these studies have provided new insights into aspects of vision such as grouping, attentional selection and the sequencing of visual operations. More generally yet, such results support the view that the perception of visualizations can be a useful domain for exploring the nature of visual cognition, inspiring new kinds of questions as well as casting new light on the limits to which information can be conveyed visually. (shrink)

Visual imagination (or visualization) is peculiar in being both free, in that what we imagine is up to us, and useful to a wide variety of practical reasoning tasks. How can we rely upon our visualizations in practical reasoning if what we imagine is subject to our whims? The key to answering this puzzle, I argue, is to provide an account of what constrains the sequence in which the representations featured in visualization unfold—an account that is consistent with (...) its freedom. Three different proposals are outlined, building on theories that link visualization to sensorimotor predictive mechanisms (e.g., efference copies, forward models ). Each sees visualization as a kind of reasoning, where its freedom consists in our ability to choose the topic of the reasoning. Of the three options, I argue that the approach many will find most attractive—that visualization is a kind of off-line perception, and is therefore in some sense misrepresentational—should be rejected. The two remaining proposals both conceive of visualization as a form of sensorimotor reasoning that is constitutive of one’s commitments concerning the way certain kinds of visuomotor scenarios unfold. According to the first, these commitments impinge on one’s web of belief from without, in the manner of normal perceptual experience; according to the second, these commitments just are one’s (occurrent) beliefs about such generalizations. I conclude that, despite being initially counterintuitive, the view of visualization as a kind of occurrent belief is the most promising. (shrink)

This article explores how readers recognize their personal identities represented through data visualizations. The recognition is investigated starting from three definitions captured by the philosopher Paul Ricoeur: the identification with the visualization, the recognition of someone in the visualization, and the mutual recognition that happens between readers. Whereas these notions were initially applied to study the role of the book reader, two further concepts complete the shift to data visualization: the digital identity stays for the present-day passport (...) of human actions and the promise is the intimate reflection that projects readers towards their own future. This article reflects on the delicate meaning of digital identity and the way of representing it according to this structure: From Personal Identity to Media is a historical introduction to self-recognition, Data Visualization for Representing Identities moves the focus to visual representation, and The Course of Recognition breaks the self-recognition in through the five concepts above just before the Conclusion. (shrink)

With the rapidly growing amounts of information, visualization is becoming increasingly important, as it allows users to easily explore and understand large amounts of information. However the field of information visualiza- tion currently lacks sufficient theoretical foundations. This article addresses foundational questions connecting information visualization with computing and philosophy studies. The idea of multiscale information granula- tion is described based on two fundamental concepts: information (structure) and computation (process). A new information processing paradigm of Granular Computing enables stepwise (...) increase of granulation/aggregation of information on different levels of resolution, which makes possible dynamical viewing of data. Information produced by Google Earth is an illustration of visualization based on clustering (granulation) of information on a succession of layers. Depending on level, specific emergent properties become visible as a result of different ways of aggregation of data/information. As information visualization ultimately aims at amplifying cognition, we discuss the process of simulation and emulation in relation to cognition, and in particular visual cognition. (shrink)

Progress in philosophy is difficult to achieve because our methods are evidentially and rhetorically weak. In the last two decades, experimental philosophers have begun to employ the methods of the social sciences to address philosophical questions. However, the adequacy of these methods has been called into question by repeated failures of replication. Experimental philosophers need to incorporate more robust methods to achieve a multi-modal perspective. In this chapter, we describe and showcase cutting-edge methods for data-mining and visualization. Big data (...) is a useful investigatory tool for moral psychology, and it fits well with the Ramsification method the first author advances in a series of recent papers. The guiding insight of these papers is that we can infer the meaning and structure of concepts from patterns of assertions and inferential associations in natural language. (shrink)

In this position paper, we describe a number of methodological and philosophical challenges that arose within our interdisciplinary Digital Humanities project CatVis, which is a collaboration between applied geometric algorithms and visualization researchers, data scientists working at OCLC, and philosophers who have a strong interest in the methodological foundations of visualization research. The challenges we describe concern aspects of one single epistemic need: that of methodologically securing (an increase in) trust in visualizations. We discuss the lack of ground (...) truths in the (digital) humanities and argue that trust in visualizations requires that we evaluate visualizations on the basis of ground truths that humanities scholars themselves create. We further argue that trust in visualizations requires that a visualization provides provable guarantees on the faithfulness of the visual representation and that we must clearly communicate to the users which part of the visualization can be trusted and how much. Finally, we discuss transparency and accessibility in visualization research and provide measures for securing transparency and accessibility. (shrink)

Scientific realism is the view that our best scientific theories can be regarded as (approximately) true. This is connected with the view that science, physics in particular, and metaphysics could (and should) inform one another: on the one hand, science tells us what the world is like, and on the other hand, metaphysical principles allow us to select between the various possible theories which are underdetermined by the data. Nonetheless, quantum mechanics has always been regarded as, at best, (...) puzzling, if not contradictory. As such, it has been considered for a long time at odds with scientific realism, and thus a naturalized quantum metaphysics was deemed impossible. Luckily, now we have many quantum theories compatible with a realist interpretation. However, scientific realists assumed that the wave-function, regarded as the principal ingredient of quantum theories, had to represent a physical entity, and because of this they struggled with quantum superpositions. In this paper I discuss a particular approach which makes quantum mechanics compatible with scientific realism without doing that. In this approach, the wave-function does not represent matter which is instead represented by some spatio-temporal entity dubbed the primitive ontology: point-particles, continuous matter fields, space-time events. I argue how within this framework one develops a distinctive theory-construction schema, which allows to perform a more informed theory evaluation by analyzing the various ingredients of the approach and their inter-relations. (shrink)

Claude P. Bruter (editor), Mathematics in Art: Mathematical Visualization in Art and Education, Springer-Verlag, New York, 2002, pp. X + 337, ISBN 3-540-43422-4.

Stegenga (forthcoming) formulates and defends a novel account of scientific progress, according to which science makes progress just in case there is a change in scientific justification. Here we present several problems for Stegenga’s account, concerning respectively (i) obtaining misleading evidence, (ii) losses or destruction of evidence, (iii) oscillations in scientific justification, and (iv) the possibility of scientific regress. We conclude by sketching a substantially different justification-based account of scientific progress that avoids these problems.

Scientific realism is the position that the aim of science is to advance on truth and increase knowledge about observable and unobservable aspects of the mind-independent world which we inhabit. This book articulates and defends that position. In presenting a clear formulation and addressing the major arguments for scientific realism Sankey appeals to philosophers beyond the community of, typically Anglo-American, analytic philosophers of science to appreciate and understand the doctrine. The book emphasizes the epistemological aspects of scientific (...) realism and contains an original solution to the problem of induction that rests on an appeal to the principle of uniformity of nature. (shrink)

Scientific realism driven by inference to the best explanation (IBE) takes empirically confirmed objects to exist, independent, pace empiricism, of whether those objects are observable or not. This kind of realism, it has been claimed, does not need probabilistic reasoning to justify the claim that these objects exist. But I show that there are scientific contexts in which a non-probabilistic IBE-driven realism leads to a puzzle. Since IBE can be applied in scientific contexts in which empirical confirmation (...) has not yet been reached, realists will in these contexts be committed to the existence of empirically unconfirmed objects. As a consequence of such commitments, because they lack probabilistic features, the possible empirical confirmation of those objects is epistemically redundant with respect to realism. (shrink)

What is scientific progress? This paper advances an interpretation of this question, and an account that serves to answer it. Roughly, the question is here understood to concern what type of cognitive change with respect to a topic X constitutes a scientific improvement with respect to X. The answer explored in the paper is that the requisite type of cognitive change occurs when scientific results are made publicly available so as to make it possible for anyone to (...) increase their understanding of X. This account is briefly compared to two rival accounts of scientific progress, based respectively on increasing truthlikeness and accumulating knowledge, and is argued to be preferable to both. (shrink)

Broadly speaking, the contemporary scientific realist is concerned to justify belief in what we might call theoretical truth, which includes truth based on ampliative inference and truth about unobservables. Many, if not most, contemporary realists say scientific realism should be treated as ‘an overarching scientific hypothesis’ (Putnam 1978, p. 18). In its most basic form, the realist hypothesis states that theories enjoying general predictive success are true. This hypothesis becomes a hypothesis to be tested. To justify our (...) belief in the realist hypothesis, realists commonly put forward an argument known as the ‘no-miracles argument’. With respect to the basic hypothesis this argument can be stated as follows: it would be a miracle were our theories as successful as they are, were they not true; the only possible explanation for the general predictive success of our scientific theories is that they are true. (shrink)

"Understanding Scientific Progress constitutes a potentially enormous and revolutionary advancement in philosophy of science. It deserves to be read and studied by everyone with any interest in or connection with physics or the theory of science. Maxwell cites the work of Hume, Kant, J.S. Mill, Ludwig Bolzmann, Pierre Duhem, Einstein, Henri Poincaré, C.S. Peirce, Whitehead, Russell, Carnap, A.J. Ayer, Karl Popper, Thomas Kuhn, Imre Lakatos, Paul Feyerabend, Nelson Goodman, Bas van Fraassen, and numerous others. He lauds Popper for advancing (...) beyond verificationism and Hume’s problem of induction, but faults both Kuhn and Popper for being unable to show that and how their work could lead nearer to the truth." —Dr. LLOYD EBY teaches philosophy at The George Washington University and The Catholic University of America, in Washington, DC "Maxwell's aim-oriented empiricism is in my opinion a very significant contribution to the philosophy of science. I hope that it will be widely discussed and debated." – ALAN SOKAL, Professor of Physics, New York University "Maxwell takes up the philosophical challenge of how natural science makes progress and provides a superb treatment of the problem in terms of the contrast between traditional conceptions and his own scientifically-informed theory—aim-oriented empiricism. This clear and rigorously-argued work deserves the attention of scientists and philosophers alike, especially those who believe that it is the accumulation of knowledge and technology that answers the question."—LEEMON McHENRY, California State University, Northridge "Maxwell has distilled the finest essence of the scientific enterprise. Science is about making the world a better place. Sometimes science loses its way. The future depends on scientists doing the right things for the right reasons. Maxwell's Aim-Oriented Empiricism is a map to put science back on the right track."—TIMOTHY McGETTIGAN, Professor of Sociology, Colorado State University - Pueblo "Maxwell has a great deal to offer with these important ideas, and deserves to be much more widely recognised than he is. Readers with a background in philosophy of science will appreciate the rigour and thoroughness of his argument, while more general readers will find his aim-oriented rationality a promising way forward in terms of a future sustainable and wise social order."—David Lorimer, Paradigm Explorer, 2017/2 "This is a book about the very core problems of the philosophy of science. The idea of replacing Standard Empiricism with Aim-Oriented Empiricism is understood by Maxwell as the key to the solution of these central problems. Maxwell handles his main tool masterfully, producing a fascinating and important reading to his colleagues in the field. However, Nicholas Maxwell is much more than just a philosopher of science. In the closing part of the book he lets the reader know about his deep concern and possible solutions of the biggest problems humanity is facing."—Professor PEETER MŰŰREPP, Tallinn University of Technology, Estonia “For many years, Maxwell has been arguing that fundamental philosophical problems about scientific progress, especially the problem of induction, cannot be solved granted standard empiricism (SE), a doctrine which, he thinks, most scientists and philosophers of science take for granted. A key tenet of SE is that no permanent thesis about the world can be accepted as a part of scientific knowledge independent of evidence. For a number of reasons, Maxwell argues, we need to adopt a rather different conception of science which he calls aim-oriented empiricism (AOE). This holds that we need to construe physics as accepting, as a part of theoretical scientific knowledge, a hierarchy of metaphysical theses about the comprehensibility and knowability of the universe, which become increasingly insubstantial as we go up the hierarchy. In his book “Understanding Scientific Progress: Aim-Oriented Empiricism”, Maxwell gives a concise and excellent illustration of this view and the arguments supporting it… Maxwell’s book is a potentially important contribution to our understanding of scientific progress and philosophy of science more generally. Maybe it is the time for scientists and philosophers to acknowledge that science has to make metaphysical assumptions concerning the knowability and comprehensibility of the universe. Fundamental philosophical problems about scientific progress, which cannot be solved granted SE, may be solved granted AOE.” Professor SHAN GAO, Shanxi University, China . (shrink)

First, I argue that scientific progress is possible in the absence of increasing verisimilitude in science’s theories. Second, I argue that increasing theoretical verisimilitude is not the central, or primary, dimension of scientific progress. Third, I defend my previous argument that unjustified changes in scientific belief may be progressive. Fourth, I illustrate how false beliefs can promote scientific progress in ways that cannot be explicated by appeal to verisimilitude.

When science makes cognitive progress, who or what is it that improves in the requisite way? According to a widespread and unchallenged assumption, it is the cognitive attitudes of scientists themselves, i.e. the agents by whom scientific progress is made, that improve during progressive episodes. This paper argues against this assumption and explores a different approach. Scientific progress should be defined in terms of potential improvements to the cognitive attitudes of those for whom progress is made, i.e. the (...) receivers rather than the producers of scientific information. This includes not only scientists themselves, but also various other individuals who utilize scientific information in different ways for the benefit of society as a whole. (shrink)

Imagination is necessary for scientific practice, yet there are no in vivo sociological studies on the ways that imagination is taught, thought of, or evaluated by scientists. This article begins to remedy this by presenting the results of a qualitative study performed on two systems biology laboratories. I found that the more advanced a participant was in their scientific career, the more they valued imagination. Further, positive attitudes toward imagination were primarily due to the perceived role of imagination (...) in problem-solving. But not all problem-solving episodes involved clear appeals to imagination, only maximally specific problems did. This pattern is explained by the presence of an implicit norm governing imagination use in the two labs: only use imagination on maximally specific problems, and only when all other available methods have failed. This norm was confirmed by the participants, and I argue that it has epistemological reasons in its favour. I also found that its strength varies inversely with career stage, such that more advanced scientists do (and should) occasionally bring their imaginations to bear on more general problems. A story about scientific pedagogy explains the trend away from (and back to) imagination over the course of a scientific career. Finally, some positive recommendations are given for a more imagination-friendly scientific pedagogy. (shrink)

Background and Objectives: In this research article, the researcher addresses the issue of creating public understanding in a democratic society about the progress of science, with an emphasis on pluralism from philosophers of science. The idea that there is only one truth and that there are just natural laws awaiting discovery by scientists has historically made it difficult to explain scientific progress. This belief motivates science to develop theories that explain the unity of science, and it is thought that (...) diversity in the way different ideas presented by scientists is a problem that results in time being wasted in search of the most accurate theory. Some scientists perceive a benefit in having a range of scientific hypotheses, though. One benefit that is frequently cited is that scientific diversity as a whole contributes to the development of a democratic society that permits the expression of a range of viewpoints. The road to accountable scientific pluralism is fraught with difficulties, though. Therefore, it is crucial to take into account both pluralism's advantages and disadvantages. This research aims at: 1. analyzing in an epistemological way the interpretation of scientific theories and the progress of science from the perspectives of scientific pluralists; 2. analyzing the relationship between science and democracy in explaining scientific significance and progress; and 3. synthesizing new knowledge on epistemic dependentism and to argue that it plays a significant role in evaluating research issues related to scientific pluralism. Methodology: The research methodology involves the application of documentary investigation along with philosophical discourse. The method of philosophical argumentation involves analyzing the lines of arguments found in relevant academic publications in order to assess their validity and soundness. Main Results: One key argument of the pluralists is the use of the concept of theoretical pluralism, which suggests that scientific knowledge is created from a variety of perspectives according to the social and cultural context of knowledge creation. It is found that part of Longino's argument is based on the negation of rational/social dichotomy. Moreover, her theory is a departure from philosopher of science Philip Kitcher, who advocates the creation of scientific knowledge and the evaluation of scientific progress through the means of democratic society. He explains that these procedures will lead to "well-ordered science" in democratic society. Discussions: The researcher examines the underlying ideas accepted by these two philosophers of science and finds that although their opinions differ, they have common ground in the acceptance of consensus. However, the views of both philosophers still lack weight in explaining the knowledge itself. The researcher argues that the acceptance of pluralism as a way of understanding scientific progress necessarily lends itself to dependentism, which points to interdependence in comparisons of superiority/inferiority between scientific theories. It is undeniable that the situation has emerged all the time, even though the success of the scientific theories being compared to each other comes from different social and cultural grounds of thought. Conclusions: Some popular models of scientific pluralism in the philosophy of science still lack a compelling justification, particularly on the epistemic grounds. By elucidating the epistemic significance of the interdependence of these things, scientific pluralism can be strengthened by incorporating the notion of epistemic dependentism into the analysis of scientific progress. (shrink)

We report the results of a study that investigated the views of researchers working in seven scientific disciplines and in history and philosophy of science in regard to four hypothesized dimensions of scientific realism. Among other things, we found that natural scientists tended to express more strongly realist views than social scientists, that history and philosophy of science scholars tended to express more antirealist views than natural scientists, that van Fraassen’s characterization of scientific realism failed to cluster (...) with more standard characterizations, and that those who endorsed the pessimistic induction were no more or less likely to endorse antirealism. (shrink)

Motivated by a recent trend that advocates a reassessment of the aim of medical science and clinical practice, this paper investigates the epistemic aims of biomedical research. Drawing on contemporary discussions in epistemology and the philosophy of science, along with a recent study on scurvy, this paper (1) explores the concept of understanding as the aim of scientific inquiry and (2) establishes a framework that will guide the examination of its forms in biomedical research. Using the case of Tuberculosis (...) (TB), (3) it is argued that grasping a mechanistic explanation is crucial for reaching a threshold of understanding at which we may speak of an objectual, biomedical understanding of TB. (shrink)

Scientists are constantly making observations, carrying out experiments, and analyzing empirical data. Meanwhile, scientific theories are routinely being adopted, revised, discarded, and replaced. But when are such changes to the content of science improvements on what came before? This is the question of scientific progress. One answer is that progress occurs when scientific theories ‘get closer to the truth’, i.e. increase their degree of truthlikeness. A second answer is that progress consists in increasing theories’ effectiveness for solving (...) scientific problems. A third answer is that progress occurs when the stock of scientific knowledge accumulates. A fourth and final answer is that scientific progress consists in increasing scientific understanding, i.e. the capacity to correctly explain and reliably predict relevant phenomena. This paper compares and contrasts these four accounts of scientific progress, considers some of the most prominent arguments for and against each account, and briefly explores connections to different forms of scientific realism. (shrink)

This book provides philosophers of science with new theoretical resources for making their own contributions to the scientific realism debate. Readers will encounter old and new arguments for and against scientific realism. They will also be given useful tips for how to provide influential formulations of scientific realism and antirealism. Finally, they will see how scientific realism relates to scientific progress, scientific understanding, mathematical realism, and scientific practice.

Bird argues that scientific progress consists in increasing knowledge. Dellsén objects that increasing knowledge is neither necessary nor sufficient for scientific progress, and argues that scientific progress rather consists in increasing understanding. Dellsén also contends that unlike Bird’s view, his view can account for the scientific practices of using idealizations and of choosing simple theories over complex ones. I argue that Dellsén’s criticisms against Bird’s view fail, and that increasing understanding cannot account for scientific progress, (...) if acceptance, as opposed to belief, is required for scientific understanding. (shrink)

Extensional scientific realism is the view that each believable scientific theory is supported by the unique first-order evidence for it and that if we want to believe that it is true, we should rely on its unique first-order evidence. In contrast, intensional scientific realism is the view that all believable scientific theories have a common feature and that we should rely on it to determine whether a theory is believable or not. Fitzpatrick argues that extensional realism (...) is immune, while intensional realism is not, to the pessimistic induction. I reply that if extensional realism overcomes the pessimistic induction at all, that is because it implicitly relies on the theoretical resource of intensional realism. I also argue that extensional realism, by nature, cannot embed a criterion for distinguishing between believable and unbelievable theories. (shrink)

A prominent type of scientific realism holds that some important parts of our best current scientific theories are at least approximately true. According to such realists, radically distinct alternatives to these theories or theory-parts are unlikely to be approximately true. Thus one might be tempted to argue, as the prominent anti-realist Kyle Stanford recently did, that realists of this kind have little or no reason to encourage scientists to attempt to identify and develop theoretical alternatives that are radically (...) distinct from currently accepted theories in the relevant respects. In other words, it may seem that realists should recommend that scientists be relatively conservative in their theoretical endeavors. This paper aims to show that this argument is mistaken. While realists should indeed be less optimistic of finding radically distinct alternatives to replace current theories, realists also have greater reasons to value the outcomes of such searches. Interestingly, this holds both for successful and failed attempts to identify and develop such alternatives. (shrink)

We model scientific theories as Bayesian networks. Nodes carry credences and function as abstract representations of propositions within the structure. Directed links carry conditional probabilities and represent connections between those propositions. Updating is Bayesian across the network as a whole. The impact of evidence at one point within a scientific theory can have a very different impact on the network than does evidence of the same strength at a different point. A Bayesian model allows us to envisage and (...) analyze the differential impact of evidence and credence change at different points within a single network and across different theoretical structures. (shrink)

This article endeavors to identify the strongest versions of the two primary arguments against epistemic scientific realism: the historical argument—generally dubbed “the pessimistic meta-induction”—and the argument from underdetermination. It is shown that, contrary to the literature, both can be understood as historically informed but logically validmodus tollensarguments. After specifying the question relevant to underdetermination and showing why empirical equivalence is unnecessary, two types of competitors to contemporary scientific theories are identified, both of which are informed by science itself. (...) With the content and structure of the two nonrealist arguments clarified, novel relations between them are uncovered, revealing the severity of their collective threat against epistemic realism and its “no-miracles” argument. The final section proposes, however, that the realist’s axiological tenet “science seeks truth” is not blocked. An attempt is made to indicate the promise for a nonepistemic, purely axiological scientific realism—here dubbed “Socratic scientific realism.”. (shrink)

Economists customarily talk about the ‘realism’ of economic models and of their assumptions and make descriptive and prescriptive judgements about them: this model has more realism in it than that, the realism of assumptions does not matter, and so on. This is not the way philosophers mostly use the term ‘realism’ thus there is a major terminological discontinuity between the two disciplines. The following remarks organise and critically elaborate some of the philosophical usages of the term and show some of (...) the ways in which they relate to economists’ concerns. In the philosophy of science, scientific realism is the mainstream position – or rather a heterogeneous collection of positions - that includes ideas about the nature of scientific theories and how they are related to the real world and about the goals and achievements of scientific inquiry. However, most of what philosophers have contributed around these ideas is not designed to deal with the peculiarities of economics, thus some important adjustments are needed to make scientific realism an interesting position for economists. (shrink)

Scientific Realism (SR) has three crucial aspects: 1) the centrality of the concept of truth, 2) the idea that success is a reliable indicator of truth, and 3) the idea that the Inference to the Best Explanation is a reliable inference rule. It will be outlined how some realists try to overcome the difficulties which arise in justifying such crucial aspects relying on an adaptationist view of evolutionism, and why such attempts are inadequate. Finally, we will briefly sketch some (...) of the main difficulties the realist has to face in defending those crucial aspects, and how such difficulties are deeply related: they derive from the inability of SR to satisfyingly avoid the sceptical challenge of the criterion of truth. Indeed, SR seems not to be able to fill the so-called ‘epistemic gap’ (Sankey 2008). In fact, the epistemic gap cannot be filled in no way other than obtaining a criterion of truth, but such a criterion cannot be obtained if the epistemic gap obtains. (shrink)

Epistemic accounts of scientific collaboration usually assume that, one way or another, two heads really are more than twice better than one. We show that this hypothesis is unduly strong. We present a deliberately crude model with unfavorable hypotheses. We show that, even then, when the priority rule is applied, large differences in successfulness can emerge from small differences in efficiency, with sometimes increasing marginal returns. We emphasize that success is sensitive to the structure of competing communities. Our results (...) suggest that purely epistemic explanations of the efficiency of collaborations are less plausible but have much more powerful socioepistemic versions. (shrink)

ABSTRACTThis discussion note aims to contribute to the ongoing debate over the nature of scientific progress. I argue against the semantic view of scientific progress, according to which scientific progress consists in approximation to truth or increasing verisimilitude. If the semantic view of scientific progress were correct, then scientists would make scientific progress simply by arbitrarily adding true disjuncts to their hypotheses or theories. Given that it is not the case that scientists could make (...) class='Hi'>scientific progress simply by arbitrarily adding true disjuncts to their hypotheses or theories, it follows that the semantic view of scientific progress is incorrect. (shrink)

Some scientific categories seem to correspond to genuine features of the world and are indispensable for successful science in some domain; in short, they are natural kinds. This book gives a general account of what it is to be a natural kind and puts the account to work illuminating numerous specific examples.

Ground is all the rage in contemporary metaphysics. But what is its nature? Some metaphysicians defend what we could call, following Skiles and Trogdon (2021), the inheritance view: it is because constitutive forms of metaphysical explanation are such-and-such that we should believe that ground is so-and-so. However, many putative instances of inheritance are not primarily motivated by scientific considerations. This limitation is harmless if one thinks that ground and science are best kept apart. Contrary to this view, we believe (...) that ground is a highly serviceable tool for investigating metaphysical areas of science. In this paper, we defend a naturalistic version of the inheritance view which takes constitutive scientific explanation as a better guide to ground. After illustrating the approach and its merits, we discuss some implications of the emerging scientific conception for the theory of ground at large. (shrink)

Scientific realists believe both what a scientific theory says about observables and unobservables. In contrast, scientific antirealists believe what a scientific theory says about observables, but not about unobservables. I argue that scientific realism is a more useful doctrine than scientific antirealism in science classrooms. If science teachers are antirealists, they are caught in Moore’s paradox when they help their students grasp the content of a scientific theory, and when they explain a phenomenon (...) in terms of a scientific theory. Teachers ask questions to their students to check whether they have grasped the content of a scientific theory. If the students are antirealists, they are also caught in Moore’s paradox when they respond positively to their teachers’ questions, and when they explain a phenomenon in terms of a scientific theory. Finally, neither teachers nor students can understand phenomena in terms of scientific theories, if they are antirealists. (shrink)

What is scientific progress? On Alexander Bird’s epistemic account of scientific progress, an episode in science is progressive precisely when there is more scientific knowledge at the end of the episode than at the beginning. Using Bird’s epistemic account as a foil, this paper develops an alternative understanding-based account on which an episode in science is progressive precisely when scientists grasp how to correctly explain or predict more aspects of the world at the end of the episode (...) than at the beginning. This account is shown to be superior to the epistemic account by examining cases in which knowledge and understanding come apart. In these cases, it is argued that scientific progress matches increases in scientific understanding rather than accumulations of knowledge. In addition, considerations having to do with minimalist idealizations, pragmatic virtues, and epistemic value all favor this understanding-based account over its epistemic counterpart. (shrink)

I examine the epistemological debate on scientific realism in the context of quantum physics, focusing on the empirical underdetermin- ation of different formulations and interpretations of QM. I will argue that much of the interpretational, metaphysical work on QM tran- scends the kinds of realist commitments that are well-motivated in the light of the history of science. I sketch a way of demarcating empirically well-confirmed aspects of QM from speculative quantum metaphysics in a way that coheres with anti-realist evidence (...) from the history of science. The minimal realist attitude sketched withholds realist com- mitment to what quantum state |Ψ⟩ represents. I argue that such commitment is not required for fulfilling the ultimate realist motiva- tion: accounting for the empirical success of quantum mechanics in a way that is in tune with a broader understanding of how theoretical science progresses and latches onto reality. (shrink)