Although “theory” has been the prevalent unit of analysis in the meta-study of science throughout most of the twentieth century, the concept remains elusive. I further explore the leitmotiv of several authors in this issue: that we should deal with theorizing (rather than theory) in biology as a cognitive activity that is to be investigated naturalistically. I first contrast how philosophers and biologists have tended to think about theory in the last century or so, and consider recent calls to upgrade (...) the role of theory in the life sciences against the background of the recent “data deluge” in molecular biology, systems biology, etc. I then review thinking about theory in biology in relation to physical theory as a positive or negative exemplar. I conclude by discussing various aspects of a positive program for “naturalizing theorizing.”. (shrink)

Since Nietzsche, the term “perspectivism” has been used as the name for an ill-defined epistemological position. Some have tried to find an adequate meaning for the word “perspectivism,” tacitly investing it with a set of different predicates, such as “the dependence of cognition on position,” “pluralism,” “anti-universalism,” “epistemic humility,” etc. This approach is related to two contestable attitudes: the monolateral linguistic paradigm and the metaepistemological position of multiplicity of incompatible epistemological programs. The monolateral linguistic paradigm proceeds from the assumption that (...) there is no obligatory connection between word and meaning. This makes it possible to denote logical content by any possible sign, and to explicate the sign in any number of ways. The metaepistemological position of multiplicity of incompatible epistemological programs encourages the support of artificial antagonism in the theory of cognition and the creation of “new” positions with different denotations. These attitudes can be contrasted with the method of empirical “originalist” analysis within the bilateral paradigm, as well as the theory of one epistemology and universal epistemic language. The content of the term “perspectivism” can be reconstructed by analyzing the original meanings of its individual constituent morphemes and their combination. The extremely precise and empirically provable definition of the word “perspectivism” is “the tendency to act by seeing through something”. This points to the problem of the impossibility of analytically deducing from it “the dependence of cognition on position,” “pluralism,” and other predicates. The same problem of inconsistency between the name of the epistemological position and its content is also encountered, for example, in the literature on relativism. It freely attributes a set of doctrinal beliefs to the term “relativism” without explicit linguistic signification of the predicates and blurs the difference between perspectivism and relativism. This points to the inexpediency of constructing epistemological positions on the basis of words denoting one of all possible interrelated cognitive actions, and the need to rethink epistemological practice. (shrink)

Epistemic pluralists in the philosophy of science often argue that different epistemic perspectives in science are equally warranted. Sandra Mitchell – with her Integrative Pluralism (IP) – has notably advocated for this kind of epistemic pluralism. A problem arises for Mitchell however because she also wants to be an epistemological pluralist. She claims that, not only are different epistemic perspectives in science equally warranted in different contexts, but different understandings of these epistemic perspectives in science are also equally warranted in (...) different contexts. The problem is that Mitchell argues that her understanding of epistemic perspectives in science (IP) is the correct one, and it is dilemmic to then claim that there is more than one such understanding. As solution, I suggest that we abandon epistemological pluralism and instead follow Feyerabend in being opportunistic pluralists. We can adopt pluralism as a short-term strategy in the pursuit of a long-term unitary goal. This unitary goal is what philosophers of understanding call objectual understanding, the kind of understanding that Integrative Pluralism tacitly aspires to anyway. (shrink)

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2018.

Relying on the notion of “overlapping perspectives,” this paper argues that entity realism and perspectivism are complementary. According to entity realism, it is justified to maintain a positive attitude toward the existence of unobservable entities with which multiple experimental interactions are possible. Perspectivism also explains that our beliefs about these entities are bounded by historically contingent theoretical and instrumental perspectives. The argument of the paper is developed through a discussion of Ronald Giere’s versions of realism: entity realism, constructive realism, and (...) perspectival realism. (shrink)

The purpose of this article is to establish a connection between modelling practices and interpretive approaches in quantum mechanics, taking as a starting point the literature on scientific representation. Different types of modalities play different roles in scientific representation. I postulate that the way theoretical structures are interpreted in this respect affects the way models are constructed. In quantum mechanics, this would be the case in particular of initial conditions and observables. I examine two formulations of quantum mechanics, the standard (...) wave-function formulation and the consistent histories formulation, and show that they correspond to opposite stances, which confirms my approach. Finally, I examine possible strategies for deciding between these stances. (shrink)

There has been much criticism of the idea that Friston's free-energy principle can unite the life and mind sciences. Here, we argue that perhaps the greatest problem for the totalizing ambitions of its proponents is a failure to recognize the importance of evolutionary dynamics and to provide a convincing adaptive story relating free-energy minimization to organismal fitness.

A large part of the controversy surrounding the publication of DSM-5 stems from the possibility of replacing the purely descriptive approach to classification favored by the DSM since 1980. This paper examines the question of how mental disorders should be classified, focusing on the issue of whether the DSM should adopt a purely descriptive or theoretical approach. I argue that the DSM should replace its purely descriptive approach with a theoretical approach that integrates causal information into the DSM’s descriptive diagnostic (...) categories. The paper proceeds in three sections. In the first section, I examine the goals (viz., guiding treatment, facilitating research, and improving communication) associated with the DSM’s purely descriptive approach. In the second section, I suggest that the DSM’s purely descriptive approach is best suited for improving communication among mental health professionals; however, theoretical approaches would be superior for purposes of treatment and research. In the third section, I outline steps required to move the DSM towards a hybrid system of classification that can accommodate the benefits of descriptive and theoretical approaches, and I discuss how the DSM’s descriptive categories could be revised to incorporate theoretical information regarding the causes of disorders. I argue that the DSM should reconceive of its goals more narrowly such that it functions primarily as an epistemic hub that mediates among various contexts of use in which definitions of mental disorders appear. My analysis emphasizes the importance of pluralism as a methodological means for avoiding theoretical dogmatism and ensuring that the DSM is a reflexive and self-correcting manual. (shrink)

Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.

After Wesley Salmon’s causal-mechanical stance on explanation in the 1980s, the ontic-epistemic debate of scientific explanations appeared to be resolved in the philosophy of science. However, since the twenty-first century, this debate has been rekindled among philosophers who focus on mechanistic explanations. Nevertheless, its issues have evolved, necessitating scrutiny of the new trends in this debate and a comparison with the original controversy between Carl Hempel and Salmon. The primary objective of this paper is to elucidate three categorical dimensions in (...) the ontic-epistemic debates, spanning from the original to the recent controversies. Subsequently, it will explore why the conception of explanation is linked to representations, what conditions are necessary for linguistic expressions to be explanatory, and what roles norms play in explanation. Consequently, contrary to the common stereotype, it will be argued that mechanistic explanations are more likely to be epistemic rather than ontic. (shrink)

It is often claimed—especially by scientific realists—that science provides understanding of the world only if its theories are (at least approximately) true descriptions of reality, in its observable as well as unobservable aspects. This paper critically examines this ‘realist thesis’ concerning understanding. A crucial problem for the realist thesis is that (as study of the history and practice of science reveals) understanding is frequently obtained via theories and models that appear to be highly unrealistic or even completely fictional. So we (...) face the dilemma of either giving up the realist thesis that understanding requires truth, or allowing for the possibility that in many if not all practical cases we do not have scientific understanding. I will argue that the first horn is preferable: the link between understanding and truth can be severed. This becomes a live option if we abandon the traditional view that scientific understanding is a special type of knowledge. While this view implies that understanding must be factive, I avoid this implication by identifying understanding with a skill rather than with knowledge. I will develop the idea that understanding phenomena consists in the ability to use a theory to generate predictions of the target system’s behavior. This implies that the crucial condition for understanding is not truth but intelligibility of the theory, where intelligibility is defined as the value that scientists attribute to the theoretical virtues that facilitate the construction of models of the phenomena. I will show, first, that my account accords with the way practicing scientists conceive of understanding, and second, that it allows for the use of idealized or fictional models and theories in achieving understanding. (shrink)

I argue that scientific knowledge is collective knowledge, in a sense to be specified and defended. I first consider some existing proposals for construing collective knowledge and argue that they are unsatisfactory, at least for scientific knowledge as we encounter it in actual scientific practice. Then I introduce an alternative conception of collective knowledge, on which knowledge is collective if there is a strong form of mutual epistemic dependence among scientists, which makes it so that satisfaction of the justification condition (...) on knowledge ineliminably requires a collective. Next, I show how features of contemporary science support the conclusion that scientific knowledge is collective knowledge in this sense. Finally, I consider implications of my proposal and defend it against objections. (shrink)

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. (shrink)

Numerous studies in the fields of Science and Technology Studies and philosophy of technology have repeatedly stressed that scientific practices are collective practices that crucially depend on the presence of scientific technologies. Postphenomenology is one of the movements that aims to draw philosophical conclusions from these observations through an analysis of human–technology interactions in scientific practice. Two other attempts that try to integrate these insights into philosophy of science are Ronald Giere’s Scientific Perspectivism and Davis Baird’s Thing Knowledge. In this (...) paper, these two approaches will be critically discussed from the perspective of postphenomenology. We will argue that Giere and Baird problematically assume that scientific instruments have a determined function, and that all human members of a scientific collective have immediate access to this function. However, these assumptions also allow them to offer a clear answer to the question how scientists can collectively relate to scientific phenomena. Such an answer is not yet formulated within the postphenomenological perspective. By adding a postphenomenological touch to the semiotic approach in Actor-Network Theory, we offer an account of how different individual human–technology relations are integrated into larger scientific collectives. We do so by showing that scientific instruments not only help constitute scientific phenomena, but also the intersubjectivity within such collectives. (shrink)

This brief commentary has three goals. The first is to argue that ‘‘framework debate’’ in cognitive science is unresolvable. The idea that one theory or framework can singly account for the vast complexity and variety of cognitive processes seems unlikely if not impossible. The second goal is a consequence of this: We should consider how the various theories on offer work together in diverse contexts of investigation. A final goal is to supply a brief review for readers who are compelled (...) by these points to explore existing literature on the topic. Despite this literature, pluralism has garnered very little attention from broader cognitive science. We end by briefly considering what it might mean for theoretical cognitive science. (shrink)

Double dissociations between perceivable colors and physical properties of colored objects have led many philosophers to endorse relationalist accounts of color. I argue that there are analogous double dissociations between attitudes of belief—the beliefs that people attribute to each other in everyday life—and intrinsic cognitive states of belief—the beliefs that some cognitive scientists posit as cogs in cognitive systems—pitched at every level of psychological explanation. These dissociations provide good reason to refrain from conflating attitudes of belief with intrinsic cognitive states (...) of belief. I suggest that interpretivism provides an attractive account of the former. Like colors, attitudes of belief evolved to be ecological signifiers, not cogs in cognitive systems. (shrink)

Argues that a pluralistic understanding of truth can foster productive conversations about common concerns involving religion, science, ethics, politics, economics, and ecology without falling into relativism. In this book, Donald A. Crosby defends the idea that all claims to truth are at best partial. Recognizing this, he argues, is a necessary safeguard against arrogance, close-mindedness, and potentially violent reactions to differences of outlook and practice. Crosby demonstrates how “partial truths” are inevitably at work in conversations and debates about religion, science, (...) morality, economics, ecology, and social and political progress. He then focuses on the concept in the discipline of philosophy, looking at a number of distinctions that are taken to be strictly binary—those between fact and value, continuity and novelty, rationalism and empiricism, mind and body, and good and evil—and demonstrates how in all of these cases, each on its own can offer only an incomplete picture. Partial Truths and Our Common Future invites ongoing dialogue with others for the sake of mutual enlargements of understanding rather than mere civility, and provides incentive for continuing open-minded and shared inquiries into the important issues of life. “This is a transdisciplinary philosophical work that moves with grace across traditions, time periods, and thinkers. It is a master class in the existential and public relevance of philosophy and a rare example of a book that is both timely and timeless.” — Michael S. Hogue, author of The Promise of Religious Naturalism. (shrink)

Despite its potential implications for the objectivity of scientific knowledge, the claim that “scientific instruments are perspectival” has received little critical attention. I show that this claim is best understood as highlighting the dependence of instruments on different perspectives. When closely analyzed, instead of constituting a novel epistemic challenge, this dependence can be exploited to mount novel strategies for resolving two old epistemic problems: conceptual relativism and theory-ladeness. The novel content of this article consists in articulating and developing these strategies (...) by introducing two fine-grained notions of perspectives as the key units of analysis: “broad perspectives” and “narrow perspectives.”. (shrink)

, 3661–3678, 2020) argues that a positivistic defense of science’s objectivity is incoherent because bias in the generation of scientific theories (implies that the rational evaluation of theories will also be biased. Even though this is an idea easy to agree with, this approach is flawed for two different but related reasons. First, Dellsén’s notion of bias does not account for many ordinary biases. Second, Dellsén’s use of bias at the community-level is inconsistent. It shifts from individual scientists generating new (...) theories and making decisions to scientific communities evaluating and accepting what theories are valid. This article offers a stronger response than Dellsén’s about aseptic objectivity in science by providing a more adequate account of bias, where psychological and behavioral aspects of individual scientists and community-level scientific practices are considered. (shrink)

An important obstacle to lawhood in the special sciences is the worry that such laws would require metaphysically extravagant conspiracies among fundamental particles. How, short of conspiracy, is this possible? In this paper we'll review a number of strategies that allow for the projectibility of special science generalizations without positing outlandish conspiracies: non-Humean pluralism, classical MRL theories of laws, and Albert and Loewer's theory. After arguing that none of the above fully succeed, we consider the conspiracy problem through the lens (...) of our preferred view of laws, an elaboration of the MRL view that we call the Better Best System (BBS) theory. BBS offers a picture on which, although all events supervene on a fundamental level, there is no one unique locus of projectibility; rather there are a large number of loci corresponding to the different areas (ecology, economics, solid-state chemistry, etc.) in which there are simple and strong generalizations to be made. While we expect that some amount of conspiracy-fear-inducing special science projectibility is inevitable given BBS, we'll argue that this is unobjectionable. It follows from BBS that the laws of any particular special or fundamental science amount to a proper subset of the laws. From this vantage point, the existence of projectible special science generalizations not guaranteed by the fundamental laws is not an occasion for conspiracy fantasies, but a predictable fact of life in a complex world. (shrink)

In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...) computational neuroscience that creates difficulties for the mechanist project. Carandini and Heeger (Nat Rev Neurosci 13:51–62, 2012) propose that many neural response properties can be understood in terms of canonical neural computations. These are “standard computational modules that apply the same fundamental operations in a variety of contexts.” Importantly, these computations can have numerous biophysical realisations, and so straightforward examination of the mechanisms underlying these computations carries little explanatory weight. Through a comparison between this modelling approach and minimal models in other branches of science, I argue that computational neuroscience frequently employs a distinct explanatory style, namely, efficient coding explanation. Such explanations cannot be assimilated into the mechanistic framework but do bear interesting similarities with evolutionary and optimality explanations elsewhere in biology. (shrink)

Even though it has been argued that scientific cognition is distributed, there is no consensus on the exact nature of distributed cognition. This paper aims to characterize distributed cognition as appropriate for philosophical studies of science. I first classify competing characterizations into three types: the property approach, the task approach, and the system approach. It turns out that the property approach and the task approach are subject to criticism. I then argue that the most preferable way to understand distributed cognition (...) in science is provided by the system approach that takes a distributed-cognitive system as the unit of analysis. I clarify this position by considering possible objections and replies. (shrink)

This article argues that the credibility of both theoretical and empirical models in economics is best understood through their connection with the empirical aspects of the real world. The discussion herein demonstrates that the similarity between the model and the real world is not enough to justify a theoretical model’s explanatory power. The best way to secure the model’s credibility is to prove the existence of representation theorems.

Que papel exercem os modelos nas investigações científicas? Que características deve ter um modelo para que seja designado como científico? Como operam os modelos nas ciências humanas e qual seu impacto nas ações humanas? Esses são alguns dos questionamentos que dão ensejo às discussões propostas por Luiz Henrique de Araújo Dutra em sua obra Pragmática de modelos, cuja terceira edição, revista e ampliada, fora recentemente lançada pela Editora Agrya.

I discuss various reactions to my article “Again, what the philosophy of science is not” [Callebaut (Acta Biotheor 53:92–122 (2005a))], most of which concern the naturalism issue, the place of the philosophy of biology within philosophy of science and philosophy at large, and the proper tasks of the philosophy of biology.

The terms “perspectivism” and “perspectivalism” have been the focus of an intense philosophical discussion with important repercussions for the debate about the role of mechanisms in scientific explanations. However, leading exponents of the new mechanistic philosophy have conceded more than was necessary to the radically subjectivistic perspectivalism, and fell into the opposite error, by retaining not negligible residues of objectivistic views about mechanisms. In order to remove this vacillation between the subjective-cultural and the objective-natural sides of mechanisms, we shall raise (...) the question about theory-ladenness over again and interpret it in its connection with the technical–experimental nature of scientific knowledge, as affirming the perspectival character of scientific knowledge: It is because of the character at once theory-laden and practice-laden, i.e. technique-laden, of our putting questions to nature that empirical reality must be investigated from particular perspectives: nature can be known scientifically only from a potentially infinite number of perspectives or theoretical points of view, concretely exemplified by mechanisms or experimental ‘machines’ that allow specific access to specific aspects of sensible reality. (shrink)

Discussions about perspectivism in the current philosophical literature often focus on questions concerning perspectival modeling or the compatibility between perspectivism and realism. In this paper, I propose to extend the debate on perspectivism by taking into account the social dimension of scientific perspectives. Scientific perspectives are always adopted and advocated for by individual scientists and groups of scientists with different epistemic affinities. I describe an example of a current and ongoing controversy in the field of epigenetics in order to illustrate (...) that diverging scientific perspectives on open scientific questions are often not fully explained by empirical underdetermination or diverging theoretical approaches alone. Opposing perspectives frequently arise from differences in systems of practice and the scientific socializations of the involved scientists, including differences in training, experimental skills, and epistemic priorities. The paper ends with a discussion of the important epistemic function of perspectives in scientific discovery. Ultimately, perspectivism is described as a valid philosophical position that explains how scientific knowledge is generated in situations of empirical underdetermination and why trust in science can be justified even in the absence of a community consensus. (shrink)

This article sketches the main features of traditional philosophical models of evidence, indicating idealizations in such models that it regards as doing more harm than good. It then proceeds to elaborate on an alternative model of evidence that is functionalist, complex, dynamic, and contextual, a view the author calls dynamic evidential functionalism (DEF). This alternative builds on insights from philosophy of scientific practice, Kuhnian philosophy of science, pragmatist epistemology, philosophy of experimentation, and functionalist philosophy of mind. Along the way, the (...) article raises concerns about the total evidence condition, requirements of certainty or incorrigibility on evidence, and accounts that restrict the type of things that can serve as evidence (to, for example, sense data, facts about particulars). DEF can also help us see the special value of novel predictions and experiments as evidence, as well as help us think about how to critically evaluate the putative evidence to determine whether it is evidence. (shrink)

The ‘death of evidence’ issue in Canada raises the spectre of politicized science, and thus the question of what role social values may have in science and how this meshes with objectivity and evidence. I first criticize philosophical accounts that have to separate different steps of research to restrict the influence of social and other non-epistemic values. A prominent account that social values may play a role even in the context of theory acceptance is the argument from inductive risk. It (...) maintains that the more severe the social consequences of erroneously accepting a theory would be, the more evidence is needed before the theory may be accepted. However, an implication of this position is that increasing evidence makes the impact of social values converge to zero; and I argue for a stronger role for social values. On this position, social values may determine a theory’s conditions of adequacy, which among other things can include co.. (shrink)

This article outlines a philosophy of science in practice that focuses on the engineering sciences. A methodological issue is that these practices seem to be divided by two different styles of scientific reasoning, namely, causal-mechanistic and mathematical reasoning. These styles are philosophically characterized by what Kuhn called ?disciplinary matrices?. Due to distinct metaphysical background pictures and/or distinct ideas of what counts as intelligible, they entail distinct ideas of the character of phenomena and what counts as a scientific explanation. It is (...) argued that the two styles cannot be reduced to each other. At the same time, although they are incompatible, they must not be regarded as competing. Instead, they produce different kinds of epistemic results, which serve different kinds of epistemic functions. Moreover, some scientific breakthroughs essentially result from relating them. This view of complementary styles of scientific reasoning is supported by pluralism about metaphysical background pictures. (shrink)

The purpose of this article is to develop an epistemology of scientific models in scientific research practices, and to show that disciplinary perspectives have crucial role in such an epistemology. A transcendental approach is taken, aimed at explanations of the kinds of questions relevant to the intended epistemology, such as “How is it possible that models provide knowledge about aspects of reality?” The approach is also pragmatic in the sense that the questions and explanations must be adequate and relevant to (...) concrete scientific practice. First it is explained why the idea of models as representations in terms of similarity or isomorphism between a model and its target is too limited as a basis for this epistemology. An important finding is that the target-phenomenon is usually not something that can be observed in a straightforward manner, but requires both characterization in terms of measurable variables and subsumption under concepts. The loss of this basis leads to a number of issues, such as: how can models be interpreted as representations if models also include conceptually meaningful linguistic content; how can researchers identify non-observable real-world target-phenomena that are then represented in the model; how do models enable inferential reasoning in performing epistemic tasks by researchers; and, how to justify scientific models. My proposal is to deal with these issues by analyzing how models are constructed, rather than by looking at ready-made models. Based on this analysis, I claim that the identification of phenomena and the construction of scientific models is guided and also confined by the disciplinary perspective within which researchers in a scientific discipline have learned to work. I propose a Kuhnian framework by which the disciplinary perspective can be systematically articulated. Finally, I argue that harmful forms of subjectivism, due to the loss of the belief that models objectively represent aspects of reality, can be overcome by making the disciplinary perspective in a research project explicit, thereby enabling its critical assessment, for which the proposed Kuhnian framework provides a tool. (shrink)

In science policy, it is generally acknowledged that science-based problem-solving requires interdisciplinary research. For example, policy makers invest in funding programs such as Horizon 2020 that aim to stimulate interdisciplinary research. Yet the epistemological processes that lead to effective interdisciplinary research are poorly understood. This article aims at an epistemology for interdisciplinary research, in particular, IDR for solving ‘real-world’ problems. Focus is on the question why researchers experience cognitive and epistemic difficulties in conducting IDR. Based on a study of educational (...) literature it is concluded that higher-education is missing clear ideas on the epistemology of IDR, and as a consequence, on how to teach it. It is conjectured that the lack of philosophical interest in the epistemology of IDR is due to a philosophical paradigm of science, which prevents recognizing severe epistemological challenges of IDR, both in the philosophy of science as well as in science education and research. The proposed alternative philosophical paradigm entails alternative philosophical presuppositions regarding aspects such as the aim of science, the character of knowledge, the epistemic and pragmatic criteria for accepting knowledge, and the role of technological instruments. This alternative philosophical paradigm assume the production of knowledge for epistemic functions as the aim of science, and interprets ‘knowledge’ as epistemic tools that must allow for conducting epistemic tasks by epistemic agents, rather than interpreting knowledge as representations that objectively represent aspects of the world independent of the way in which it was constructed. The engineering paradigm of science involves that knowledge is indelibly shaped by how it is constructed. Additionally, the way in which scientific disciplines construct knowledge is guided by the specificities of the discipline, which can be analyzed in terms of disciplinary perspectives. This implies that knowledge and the epistemic uses of knowledge cannot be understood without at least some understanding of how the knowledge is constructed. Accordingly, scientific researchers need so-called metacognitive scaffolds to assist in analyzing and reconstructing how ‘knowledge’ is constructed and how different disciplines do this differently. In an engineering paradigm of science, these metacognitive scaffolds can also be interpreted as epistemic tools, but in this case as tools that guide, enable and constrain analyzing and articulating how knowledge is produced. In interdisciplinary research, metacognitive scaffolds assist interdisciplinary communication aiming to analyze and articulate how the discipline constructs knowledge. (shrink)

The complex societal challenges of the twenty-first Century require scientific researchers and academically educated professionals capable of conducting scientific research in complex problem contexts. Our central claim is that educational approaches inspired by a traditional empiricist epistemology insufficiently foster the required deep conceptual understanding and higher-order thinking skills necessary for epistemic tasks in scientific research. Conversely, we argue that constructivist epistemologies provide better guidance to educational approaches to promote research skills. We also argue that teachers adopting a constructivist learning theory (...) do not necessarily embrace a constructivist epistemology. On the contrary, in educational practice, novel educational approaches that adopt constructivist learning theories often maintain traditional empiricist epistemologies. Philosophers of science can help develop educational designs focused on learning to conduct scientific research, combining constructivist learning theory with constructivist epistemology. We illustrate this by an example from a bachelor’s program in Biomedical Engineering, where we introduce conceptual models and modeling as an alternative to the traditional focus on hypothesis testing in conducting scientific research. This educational approach includes the so-called B&K method for constructing scientific models to scaffold teaching and learning conceptual modeling. (shrink)

Deep neural networks have become increasingly successful in applications from biology to cosmology to social science. Trained DNNs, moreover, correspond to models that ideally allow the prediction of new phenomena. Building in part on the literature on ‘eXplainable AI’, I here argue that these models are instrumental in a sense that makes them non-explanatory, and that their automated generation is opaque in a unique way. This combination implies the possibility of an unprecedented gap between discovery and explanation: When unsupervised models (...) are successfully used in exploratory contexts, scientists face a whole new challenge in forming the concepts required for understanding underlying mechanisms. (shrink)

Notwithstanding the remarkable achievements made by medical science over the last half of the twentieth century, there is a palpable sense that a strictly medical view of human health, that is one founded on modernist assumptions, has become problematic, if not counterproductive. In this study, I argue that as nursing continues to eagerly welcome and indeed champion medical epistemology in the form of knowledge transfer, evidence‐based practice, research utilization, outcomes‐based practice, quantifiable efficiency and effectiveness, it risks becoming little more than (...) a medical science addendum and indeed one that inherits the problems now facing contemporary medicine. The purpose of this study then is to attempt to resituate nursing as a discipline at work within an ontopolitical matrix of radical democratic pluralism. I begin by tracing a philosophical line from Kuhn’s paradigms to Bloor’s strong programme of Sociology of Scientific Knowledge. Following this, I attempt to explicate the thought of Bruno Latour as a philosophical alternative to Sociology of Scientific Knowledge. Next, I outline the radical pluralism of William Connolly in an effort to demonstrate its similarity to Latour’s philosophy and finally how such a position is germane to contemporary nursing and the reality of politics. I do this with reference to the controversial issue of illicit drug use and harm reduction. In effect, I argue that such an issue cannot be dealt with using scientific evidence alone, but rather requires a philosophy of advocacy, what I term democratic advocacy, that is capable of responding to the politics of suffering, which is to say suffering that results from identity/difference. (shrink)

In current debates, many philosophers of science have sympathies for the project of introducing a new approach to the scientific realism debate that forges a middle way between traditional forms of scientific realism and anti-realism. One promising approach is perspectivism. Although different proponents of perspectivism differ in their respective characterizations of perspectivism, the common idea is that scientific knowledge is necessarily partial and incomplete. Perspectivism is a new position in current debates but it does have its forerunners. Figures that are (...) typically mentioned in this context include Dewey, Feyerabend, Leibniz, Kant, Kuhn, and Putnam. Interestingly, to my knowledge, there exists no work that discusses similarities to the phenomenological tradition. This is surprising because here one can find systematically similar ideas and even a very similar terminology. It is startling because early modern physics was noticeably influenced by phenomenological ideas. And it is unfortunate because the analysis of perspectival approaches in the phenomenological tradition can help us to achieve a more nuanced understanding of different forms of perspectivism. The main objective of this paper is to show that in the phenomenological tradition one finds a well-elaborated philosophy of science that shares important similarities with current versions of perspectivism. Engaging with the phenomenological tradition is also of systematic value since it helps us to gain a better understanding of the distinctive claims of perspectivism and to distinguish various grades of perspectivism. (shrink)

As is well known, the late Husserl warned against the dangers of reifying and objectifying the mathematical models that operate at the heart of our physical theories. Although Husserl’s worries were mainly directed at Galilean physics, the first aim of our paper is to show that many of his critical arguments are no less relevant today. By addressing the formalism and current interpretations of quantum theory, we illustrate how topics surrounding the mathematization of nature come to the fore naturally. Our (...) second aim is to consider the program of reconstructing quantum theory, a program that currently enjoys popularity in the field of quantum foundations. We will conclude by arguing that, seen from this vantage point, certain insights delivered by phenomenology and quantum theory regarding perspectivity are remarkably concordant. Our overall hope with this paper is to show that there is much room for mutual learning between phenomenology and modern physics. (shrink)

This paper argues for the theoretical and practical validity of similarity as a useful epistemological tool in scientific knowledge generation, specifically in chemistry. Classical analyses of similarity in philosophy of science do not account for the concept’s practical significance in scientific activities. We recur to examples from chemistry to counter the claim of authors like Quine or Goodman to the effect that similarity must be excluded from scientific practices . In conclusion we argue that more recent conceptualizations of the notion (...) of similarity, particularly Giere’s one, are appropriate for a philosophical analysis that considers scientific practices on equal terms with scientific theory. (shrink)

This article argues for a different outlook on the concept of extension, especially for the reference of general terms in scientific practice. Scientific realist interpretations of the two predominant theories of meaning, namely Descriptivism and Causal Theory, contend that a stable cluster of descriptions or an initial baptism fixes the extension of a general term such as a natural kind term. This view in which the meaning of general terms is presented as monosemantic and the referents as stable, homogeneous, and (...) unchangeable, however, does not reflect the various practices involved in the investigation of research materials and the related application of general terms in scientific practice. By drawing on the taxonomic diversity, particularly of structure-based classifications in chemical databases, this article illustrates the limited utility of such a concept of extension. Research materials often exhibit a plurality of material dimensions that, within different research contexts, allow for various and often equally significant taxonomic demarcations. In light of this, the extension of a general term cannot be uniquely determined by a supposedly independent nature of the referent but is relative to the model context under which the materials are investigated. This significance and plurality of the model context, I claim, needs to be mirrored in an account of meaning that is supposed to reflect scientific reality. On this account, the aim of this article is to present an alternative perspective on the concept of extension to accommodate the diverse material practices that determine the application of general terms in science. (shrink)

When Ron Giere introduced perspectivism into philosophy of science, he provided a perspectivist analysis of both scientific instruments and scientific theorizing. Today, there is a burgeoning literature that extends Giere’s analysis of theorizing, with many philosophers examining the perspectivist approach to aspects of theorizing such as models, laws, explanations, and so on. However, relatively little attention has been paid to Giere’s analysis of instruments. In this article, I hope to fill this gap. I argue that the perspectivist analysis of instruments (...) should be rejected. First, I give a general account of the kind of instrumentation relevant to instrumental perspectivism, drawing on Cartwright’s notion of nomological machines, which forms the basis of my criticism of Giere’s argument for instrumental perspectivism. Next, I present the case against instrumental perspectivism. I argue that instrumental perspectivism is dependent on theoretical perspectivism in a way that robs it of philosophical significance, and that it introduces new puzzles while adding little to our understanding of instruments. (shrink)

In science policy, it is generally acknowledged that science-based problem-solving requires interdisciplinary research. For example, policy makers invest in funding programs such as Horizon 2020 that aim to stimulate interdisciplinary research. Yet the epistemological processes that lead to effective interdisciplinary research are poorly understood. This article aims at an epistemology for interdisciplinary research, in particular, IDR for solving ‘real-world’ problems. Focus is on the question why researchers experience cognitive and epistemic difficulties in conducting IDR. Based on a study of educational (...) literature it is concluded that higher-education is missing clear ideas on the epistemology of IDR, and as a consequence, on how to teach it. It is conjectured that the lack of philosophical interest in the epistemology of IDR is due to a philosophical paradigm of science, which prevents recognizing severe epistemological challenges of IDR, both in the philosophy of science as well as in science education and research. The proposed alternative philosophical paradigm entails alternative philosophical presuppositions regarding aspects such as the aim of science, the character of knowledge, the epistemic and pragmatic criteria for accepting knowledge, and the role of technological instruments. This alternative philosophical paradigm assume the production of knowledge for epistemic functions as the aim of science, and interprets ‘knowledge’ as epistemic tools that must allow for conducting epistemic tasks by epistemic agents, rather than interpreting knowledge as representations that objectively represent aspects of the world independent of the way in which it was constructed. The engineering paradigm of science involves that knowledge is indelibly shaped by how it is constructed. Additionally, the way in which scientific disciplines construct knowledge is guided by the specificities of the discipline, which can be analyzed in terms of disciplinary perspectives. This implies that knowledge and the epistemic uses of knowledge cannot be understood without at least some understanding of how the knowledge is constructed. Accordingly, scientific researchers need so-called metacognitive scaffolds to assist in analyzing and reconstructing how ‘knowledge’ is constructed and how different disciplines do this differently. In an engineering paradigm of science, these metacognitive scaffolds can also be interpreted as epistemic tools, but in this case as tools that guide, enable and constrain analyzing and articulating how knowledge is produced. In interdisciplinary research, metacognitive scaffolds assist interdisciplinary communication aiming to analyze and articulate how the discipline constructs knowledge. (shrink)