Modelling and representing: An artefactual approach to model-based representation

The recent discussion on scientific representation has focused on models and their relationship to the real world. It has been assumed that models give us knowledge because they represent their supposed real target systems. However, here agreement among philosophers of science has tended to end as they have presented widely different views on how representation should be understood. I will argue that the traditional representational approach is too limiting as regards the epistemic value of modelling given the focus on the relationship between a single model and its supposed target system, and the neglect of the actual representational means with which scientists construct models. I therefore suggest an alternative account of models as epistemic tools. This amounts to regarding them as concrete artefacts that are built by specific representational means and are constrained by their design in such a way that they facilitate the study of certain scientific questions, and learning from them by means of construction and manipulation.     

The benefits of acquiring interactional expertise: Why (some) philosophers of science should engage scientific communities

Philosophers of science are increasingly arguing for and addressing the need to do work that is socially and scientifically engaged. However, we currently lack well-developed frameworks for thinking about how we should engage other expert communities and what the epistemic benefits are of doing so. In this paper, I draw on Collins and Evans' concept of ‘interactional expertise’ – the ability to speak the language of a discipline in the absence of an ability to practice – to consider the epistemic benefits that can arise when philosophers engage scientific communities. As Collins and Evans argue, becoming an interactional expert requires that one ‘hang out’ with members of the relevant expert community in order to learn crucial tacit knowledge needed to speak the language. Building on this work, I argue that acquiring interactional expertise not only leads to linguistic fluency, but it also confers several ‘socio-epistemic’ benefits such as the opportunity to cultivate trust with scientific communities. These benefits can improve philosophical work and facilitate the broader uptake of philosophers' ideas, enabling philosophers to meet a variety of epistemic goals. As a result, having at least some philosophers of science acquire interactional expertise via engagement will likely enhance the diversity of epistemic capacities for philosophy of science as a whole. For some philosophers of science, moreover, the socio-epistemic benefits identified here may be more important than the ability to speak the language of a discipline, suggesting the need for a broader analysis of interactional expertise, which this paper also advances.     

(Mis)Understanding scientific disagreement: Success versus pursuit-worthiness in theory choice

Scientists often diverge widely when choosing between research programs. This can seem to be rooted in disagreements about which of several theories, competing to address shared questions or phenomena, is currently the most epistemically or explanatorily valuable—i.e. most successful. But many such cases are actually more directly rooted in differing judgments of pursuit-worthiness, concerning which theory will be best down the line, or which addresses the most significant data or questions. Using case studies from 16^th-century astronomy and 20^th-century geology and biology, I argue that divergent theory choice is thus often driven by considerations of scientific process, even where direct epistemic or explanatory evaluation of its final products appears more relevant. Broadly following Kuhn's analysis of theoretical virtues, I suggest that widely shared criteria for pursuit-worthiness function as imprecise, mutually-conflicting values. However, even Kuhn and others sensitive to pragmatic dimensions of theory ‘acceptance’, including the virtue of fruitfulness, still commonly understate the role of pursuit-worthiness—especially by exaggerating the impact of more present-oriented virtues, or failing to stress how ‘competing’ theories excel at addressing different questions or data. This framework clarifies the nature of the choice and competition involved in theory choice, and the role of alternative theoretical virtues.     

Integrating mechanistic explanations through epistemic perspectives

Talk of levels is ubiquitous in philosophy, especially in the context of mechanistic explanations spanning multiple levels. The mechanistic conception of levels, however, does not allow for the kind of integration needed to construct such multi-level mechanistic explanations integrating observations from different scientific domains. To address the issues arising in this context, I build on a certain perspectival aspect inherent in the mechanistic view. Rather than focusing on compositionally related levels of mechanisms, I suggest analyzing the situation in terms of epistemic perspectives researchers take when making scientific observations. Characterizing epistemic perspectives along five dimensions allows for a systematic analysis of the relations the scientific observations made from these different epistemic perspectives. This, in turn, provides a solid foundation for integrating the mechanistic explanations that are based on the scientific observations in question.     

Generative models: Human embryonic stem cells and multiple modeling relations

Model organisms are at once scientific models and concrete living things. It is widely assumed by philosophers of science that (1) model organisms function much like other kinds of models, and (2) that insofar as their scientific role is distinctive, it is in virtue of representing a wide range of biological species and providing a basis for generalizations about those targets. This paper uses the case of human embryonic stem cells (hESC) to challenge both assumptions. I first argue that hESC can be considered model organisms, analogous to classic examples such as Escherichia coli and Drosophila melanogaster. I then discuss four contrasts between the epistemic role of hESC in practice, and the assumptions about model organisms noted above. These contrasts motivate an alternative view of model organisms as a network of systems related constructively and developmentally to one another. I conclude by relating this result to other accounts of model organisms in recent philosophy of science.     

The abundant world: Paul Feyerabend's metaphysics of science

The goal of this paper is to provide an interpretation of Feyerabend's metaphysics of science as found in late works like Conquest of Abundance and Tyranny of Science. Feyerabend's late metaphysics consists of an attempt to criticize and provide a systematic alternative to traditional scientific realism, a package of views he sometimes referred to as “scientific materialism.” Scientific materialism is objectionable not only on metaphysical grounds, nor because it provides a poor ground for understanding science, but because it implies problematic claims about the epistemic and cultural authority of science, claims incompatible with situating science properly in democratic societies. I show how Feyerabend's metaphysical view, which I call “the abundant world” or “abundant realism,” constitute a sophisticated and challenging form of ontological pluralism that makes interesting connections with contemporary philosophy of science and issues of the political and policy role of science in a democratic society.     

The rise of western rationalism: Paul Feyerabend's story

I summarize certain aspects of Paul Feyerabend's account of the development of Western rationalism, show the ways in which that account is supposed to run up against an alternative, that of Karl Popper, and then try to give a preliminary comparison of the two. My interest is primarily in whether what Feyerabend called his ‘story’ constitutes a possible history of our epistemic concepts and their trajectory. I express some grave reservations about that story, and about Feyerabend's framework, finding Popper's views less problematic here. However, I also suggest that one important aspect of Feyerabend's material, his treatment of religious belief, can be given an interpretation which makes it tenable, and perhaps preferable to a Popperian approach.     

Knowing what would happen: The epistemic strategies in Galileo's thought experiments

While philosophers have subjected Galileo's classic thought experiments to critical analysis, they have tended to largely ignored the historical and intellectual context in which they were deployed, and the specific role they played in Galileo's overall vision of science. In this paper I investigate Galileo's use of thought experiments, by focusing on the epistemic and rhetorical strategies that he employed in attempting to answer the question of how one can know what would happen in an imaginary scenario. Here I argue we can find three different answers to this question in Galileo later dialogues, which reflect the changing meanings of ‘experience’ and ‘knowledge’ (scientia) in the early modern period. Once we recognise that Galileo's thought experiments sometimes drew on the power of memory and the explicit appeal to ‘common experience’, while at other times, they took the form of demonstrative arguments intended to have the status of necessary truths; and on still other occasions, they were extrapolations, or probable guesses, drawn from a carefully planned series of controlled experiments, it becomes evident that no single account of the epistemological relationship between thought experiment, experience and experiment can adequately capture the epistemic variety we find Galileo's use of imaginary scenarios. To this extent, we cannot neatly classify Galileo's use of thought experiments as either ‘medieval’ or ‘early modern’, but we should see them as indicative of the complex epistemological transformations of the early seventeenth century.     

Incredulity towards Lyotard: a critique of a postmodernist account of science and knowledge

Philosophers of science have paid little attention, positive or negative, to Lyotard’s book The postmodern condition, even though it has been popular in other fields. We set out some of the reasons for this neglect. Lyotard thought that sciences could be justified by non-scientific narratives (a position he later abandoned). We show why this is unacceptable, and why many of Lyotard’s characterisations of science are either implausible or are narrowly positivist. One of Lyotard’s themes is that the nature of knowledge has changed and thereby so has society itself. However much of what Lyotard says muddles epistemological matters about the definition of ‘knowledge’ with sociological claims about how information circulates in modern society. We distinguish two kinds of legitimation of science: epistemic and socio-political. In proclaiming ‘incredulity towards metanarratives’ Lyotard has nothing to say about how epistemic and methodological principles are to be justified (legitimated). He also gives a bad argument as to why there can be no epistemic legitimation, which is based on an act/content confusion, and a confusion between making an agreement and the content of what is agreed to. As for socio-political legitimation, Lyotard’s discussion remains at the abstract level of science as a whole rather than at the level of the particular applications of sciences. Moreover his positive points can be accepted without taking on board any of his postmodernist account of science. Finally we argue that Lyotard’s account of paralogy, which is meant to provide a ‘postmodern’ style of justification, is a failure.     

String theory,Einstein, and the identity of physics: Theory assessment in absence of the empirical

String theorists are certain that they are practicing physicists. Yet, some of their recent critics deny this. This paper argues that this conflict is really about who holds authority in making rational judgment in theoretical physics. At bottom, the conflict centers on the question: who is a proper physicist? To illustrate and understand the differing opinions about proper practice and identity, we discuss different appreciations of epistemic virtues and explanation among string theorists and their critics, and how these have been sourced in accounts of Einstein's biography. Just as Einstein is claimed by both sides, historiography offers examples of both successful and unsuccessful non-empirical science. History of science also teaches that times of conflict are often times of innovation, in which novel scholarly identities may come into being. At the same time, since the contributions of Thomas Kuhn historians have developed a critical attitude towards formal attempts and methodological recipes for epistemic demarcation and justification of scientific practice. These are now, however, being considered in the debate on non-empirical physics.     

A second look at the colors of the dinosaurs

In earlier work, I predicted that we would probably not be able to determine the colors of the dinosaurs. I lost this epistemic bet against science in dramatic fashion when scientists discovered that it is possible to draw inferences about dinosaur coloration based on the microstructure of fossil feathers (Vinther et al., 2008). This paper is an exercise in philosophical error analysis. I examine this episode with two questions in mind. First, does this case lend any support to epistemic optimism about historical science? Second, under what conditions is it rational to make predictions about what questions scientists will or will not be able answer? In reply to the first question, I argue that the recent work on the colors of the dinosaurs matters less to the debate about the epistemology of historical science than it might seem. In reply to the second question, I argue that it is difficult to specify a policy that would rule out the failed bet without also being too conservative.     

The diverse aims of science

There is increasing attention to the centrality of idealization in science. One common view is that models and other idealized representations are important to science, but that they fall short in one or more ways. On this view, there must be an intermediary step between idealized representation and the traditional aims of science, including truth, explanation, and prediction. Here I develop an alternative interpretation of the relationship between idealized representation and the aims of science. I suggest that continuing, widespread idealization calls into question the idea that science aims for truth. If instead science aims to produce understanding, this would enable idealizations to directly contribute to science's epistemic success. I also use the fact of widespread idealization to motivate the idea that science's wide variety aims, epistemic and non-epistemic, are best served by different kinds of scientific products. Finally, I show how these diverse aims—most rather distant from truth—result in the expanded influence of social values on science.     

What is mechanistic evidence,and why do we need it for evidence-based policy?

It has recently been argued that successful evidence-based policy should rely on two kinds of evidence: statistical and mechanistic. The former is held to be evidence that a policy brings about the desired outcome, and the latter concerns how it does so. Although agreeing with the spirit of this proposal, we argue that the underlying conception of mechanistic evidence as evidence that is different in kind from correlational, difference-making or statistical evidence, does not correctly capture the role that information about mechanisms should play in evidence-based policy. We offer an alternative account of mechanistic evidence as information concerning the causal pathway connecting the policy intervention to its outcome. Not only can this be analyzed as evidence of difference-making, it is also to be found at any level and is obtainable by a broad range of methods, both experimental and observational. Using behavioral policy as an illustration, we draw the implications of this revised understanding of mechanistic evidence for debates concerning policy extrapolation, evidence hierarchies, and evidence integration.     

Naturalized epistemology, or what the Strong Programme can’t explain

In this paper I argue that the Strong Programme’s aim to provide robust explanations of belief acquisition is limited by its commitment to the symmetry principle. For Bloor and Barnes, the symmetry principle is intended to drive home the fact that epistemic norms are socially constituted. My argument here is that even if our epistemic standards are fully naturalized—even relativized—they nevertheless can play a pivotal role in why individuals adopt the beliefs that they do. Indeed, sometimes the fact that a belief is locally endorsed as rational is the only reason why an individual holds it. In this way, norms of rationality have a powerful and unique role in belief formation. But if this is true then the symmetry principle’s emphasis on ‘sameness of type’ is misguided. It has the undesirable effect of not just naturalizing our cognitive commitments, but trivializing them. Indeed, if the notion of ‘similarity’ is to have any content, then we are not going to classify as ‘the same’ beliefs that are formed in accordance with deeply entrenched epistemic norms as ones formed without reflection on these norms, or ones formed in spite of these norms. My suggestion here is that we give up the symmetry principle in favor of a more sophisticated principle, one that allows for a taxonomy of causes rich enough to allow us to delineate the unique impact epistemic norms have on those individuals who subscribe to them.     

The experimenters' regress reconsidered: Replication,tacit knowledge,and the dynamics of knowledge generation

This paper revisits the debate between Harry Collins and Allan Franklin, concerning the experimenters' regress. Focusing my attention on a case study from recent psychology (regarding experimental evidence for the existence of a Mozart Effect), I argue that Franklin is right to highlight the role of epistemological strategies in scientific practice, but that his account does not sufficiently appreciate Collins's point about the importance of tacit knowledge in experimental practice. In turn, Collins rightly highlights the epistemic uncertainty (and skepticism) surrounding much experimental research. However, I will argue that his analysis of tacit knowledge fails to elucidate the reasons why scientists often are (and should be) skeptical of other researchers' experimental results. I will present an analysis of tacit knowledge in experimental research that not only answers to this desideratum, but also shows how such skepticism can in fact be a vital enabling factor for the dynamic processes of experimental knowledge generation.     

The epistemic value of good sense

This paper examines competing interpretations of Pierre Duhem’s theory of good sense recently defended by David Stump and Milena Ivanova and defends a hybrid reading that accommodates the intuitions of both readings. At issue between Stump and Ivanova is whether Duhemian good sense is a virtue theoretic concept. I approach the issue from the broader perspective of determining the epistemic value of good sense per se, and argue for a mitigated virtue theoretic reading that identifies an essential role for good sense in theory choice. I also show that many important issues in both philosophy of science and ‘mainstream’ value driven epistemology are illuminated by the debate over the epistemic value of good sense. In particular, philosophical work on the nature of cognitive character, rule governed rationality and the prospects of epistemic value t-monism are illuminated by virtue theoretic readings of Duhemian good sense.     

Conventionalism,structuralism and neo-Kantianism in Poincaré׳s philosophy of science

Poincaré is well known for his conventionalism and structuralism. However, the relationship between these two theses and their place in Poincaré׳s epistemology of science remain puzzling. In this paper I show the scope of Poincaré׳s conventionalism and its position in Poincaré׳s hierarchical approach to scientific theories. I argue that for Poincaré scientific knowledge is relational and made possible by synthetic a priori, empirical and conventional elements, which, however, are not chosen arbitrarily. By examining his geometric conventionalism, his hierarchical account of science and defence of continuity in theory change, I argue that Poincaré defends a complex structuralist position based on synthetic a priori and conventional elements, the mind-dependence of which precludes epistemic access to mind-independent structures.     

Kuhn’s Structure of Scientific Revolutions between sociology and epistemology

The aim of the paper is to clarify Kuhn’s theory of scientific revolutions. We propose to discriminate between a scientific revolution, which is a sociological event of a change of attitude of the scientific community with respect to a particular theory, and an epistemic rupture, which is a linguistic fact consisting of a discontinuity in the linguistic framework in which this theory is formulated. We propose a classification of epistemic ruptures into four types. In the paper, each of these types of epistemic ruptures is illustrated by examples from physics. The classification of epistemic ruptures can be used as a basis for a classification of scientific revolutions and thus for a refinement of our view of the progress of science.     

A mid-level approach to modeling scientific communities

This paper provides an account of mid-level models which calibrate highly theoretical agent-based models of scientific communities by incorporating empirical information from real-world systems. As a result, these models more closely correspond with real-world communities, and are better suited for informing policy decisions than extant how-possibly models. I provide an exemplar of a mid-level model of science funding allocation that incorporates bibliometric data from scientific publications and data generated from empirical studies of peer review into an epistemic landscape model. The results of my model show that on a dynamic epistemic landscape, allocating funding by modified and pure lottery strategies performs comparably to a perfect selection funding allocation strategy. These results support the idea that introducing randomness into a funding allocation process may be a tractable policy worth exploring further through pilot studies. My exemplar shows that agent-based models need not be restricted to the abstract and the apriori; they can also be informed by empirical data.     

Picturing the moon: Hevelius’s and Riccioli’s visual debate

This article investigates the maps of the moon produced in the mid-seventeenth century by Jesuit Giambattista Riccioli (1598-1671) and Johannes Hevelius (1611-1687), whose cartographic projects competed for widespread acceptance. Although Hevelius’s Selenographia (1647) was applauded for its many detailed, self-engraved pictures of the moon, his cartography and proposed nomenclature were supplanted by Riccioli’s as offered in Almagestum novum (1651), in spite of the latter’s simplistic pictures and promotion of geocentric cosmology. Exploring this paradox through pictorial analysis, three types of images common to both Selenographia and Almagestum novum are compared, employing an analytical tool developed by Svetlana Alpers in The art of describing (1983). A focus on this debate exposes the tensions evoked by new technologies of vision and competing cultures of visual epistemology in seventeenth-century astronomy. As both selenographers grappled with questions about the role of representation and what kinds of knowledge could be generated visually, the successes and failures of their competing projects present implications for the course of visual astronomy, as well as for our understanding of the use of ‘visual technologies’ in a period of controversy.