Self-organised criticality—what it is and what it isn’t

The last decade and a half has seen an ardent development of self-organised criticality (SOC), a new approach to complex systems, which has become important in many domains of natural as well as social science, such as geology, biology, astronomy, and economics, to mention just a few. This has led many to adopt a generalist stance towards SOC, which is now repeatedly claimed to be a universal theory of complex behaviour. The aim of this paper is twofold. First, I provide a brief and non-technical introduction to SOC. Second, I critically discuss the various bold claims that have been made in connection with it. Throughout, I will adopt a rather sober attitude and argue that some people have been too readily carried away by fancy contentions. My overall conclusion will be that none of these bold claims can be maintained. Nevertheless, stripped of exaggerated expectations and daring assertions, many SOC models are interesting vehicles for promising scientific research.     

The methodological defense of realism scrutinized

I revisit an older defense of scientific realism, the methodological defense, a defense developed by both Popper and Feyerabend. The methodological defense of realism concerns the attitude of scientists, not philosophers of science. The methodological defense is as follows: a commitment to realism leads scientists to pursue the truth, which in turn is apt to put them in a better position to get at the truth. In contrast, anti-realists lack the tenacity required to develop a theory to its fullest. As a consequence, they are less likely to get at the truth.My aim is to show that the methodological defense is flawed. I argue that a commitment to realism does not always benefit science, and that there is reason to believe that a research community with both realists and anti-realists in it may be better suited to advancing science. A case study of the Copernican Revolution in astronomy supports this claim.     

Overlapping ontologies and Indigenous knowledge. From integration to ontological self-determination

Current controversies about knowledge integration reflect conflicting ideas of what it means to “take Indigenous knowledge seriously”. While there is increased interest in integrating Indigenous and Western scientific knowledge in various disciplines such as anthropology and ethnobiology, integration projects are often accused of recognizing Indigenous knowledge only insofar as it is useful for Western scientists. The aim of this article is to use tools from philosophy of science to develop a model of both successful integration and integration failures. On the one hand, I argue that cross-cultural recognition of property clusters leads to an ontological overlap that makes knowledge integration often epistemically productive and socially useful. On the other hand, I argue that knowledge integration is limited by ontological divergence. Adequate models of Indigenous knowledge will therefore have to take integration failures seriously and I argue that integration efforts need to be complemented by a political notion of ontological self-determination.     

Modelling and knowledge transfer in complexity science

I analyse the construction and transfer of models in complexity science. Thereby, I introduce a distinction between (i) vertical model construction, which is based on knowledge about a specific target system, (ii) horizontal model construction, which is based on the alteration of an existing model and therefore does not require any references to a specific target system; and (iii) the transfer of models, which consists of the assignment of an existing model to a new target system. I argue that, in complexity science, all three of those modelling activities take place. Furthermore, I show that these activities can be divided into two general categories: (i) the creation of a repository of models without specific target systems, which have been created by large-scale horizontal construction; and (ii) the transfer of these models to particular target systems in the natural sciences, which can also be followed by an extension of the transferred model through vertical construction of adaptions and additions to its dynamics. I then argue that this interplay of different modelling activities in complexity science provides a mechanism for the transfer of knowledge between different scientific fields. It is also crucial to the interdisciplinary nature of complexity science.     

Analogical reflection as a source for the science of life: Kant and the possibility of the biological sciences

In contrast to the previously widespread view that Kant's work was largely in dialogue with the physical sciences, recent scholarship has highlighted Kant's interest in and contributions to the life sciences. Scholars are now investigating the extent to which Kant appealed to and incorporated insights from the life sciences and considering the ways he may have contributed to a new conception of living beings. The scholarship remains, however, divided in its interest: historians of science are concerned with the content of Kant's claims, and the ways in which they may or may not have contributed to the emerging science of life, while historians of philosophy focus on the systematic justifications for Kant's claims, e.g., the methodological and theoretical underpinnings of Kant's statement that living beings are mechanically inexplicable. My aim in this paper is to bring together these two strands of scholarship into dialogue by showing how Kant's methodological concerns (specifically, his notion of reflective judgment) contributed to his conception of living beings and to the ontological concern with life as a distinctive object of study. I argue that although Kant's explicit statement was that biology could not be a science, his implicit and more fundamental claim was that the study of living beings necessitates a distinctive mode of thought, a mode that is essentially analogical. I consider the implications of this view, and argue that it is by developing a new methodology for grasping organized beings that Kant makes his most important contribution to the new science of life.     

Constructive empiricism, observability and three kinds of ontological commitment

In this paper, I argue that, contrary to the constructive empiricist’s position, observability is not an adequate criterion as a guide to ontological commitment in science. My argument has two parts. First, I argue that the constructive empiricist’s choice of observability as a criterion for ontological commitment is based on the assumption that belief in the existence of unobservable entities is unreasonable because belief in the existence of an entity can only be vindicated by its observation. Second, I argue that the kind of ontological commitment that is under consideration when accepting a scientific theory is commitment to what I call theoretical kinds and that observation can vindicate commitment to kinds only in exceptional cases.     

I am knowledge. Get me out of here! On localism and the universality of science

It has become increasingly common in historiography of science to understand science and its products as inherently local. However, this orientation is faced with three problems. First, how can one explain the seeming universality of contemporary science? Second, if science is so reflective of its local conditions of production, how can it travel so effortlessly to other localities and even globally? And third, how can scientific knowledge attain validity outside its context of origin? I will argue that the notion of standardization and theories of delocalization manage to explain the ‘globality’ of science, but that localism denies ‘universality’ if it is understood non-spatially. Further, localism limits the validity of scientific knowledge unacceptably inside the laboratory walls or other boundaries of knowledge creation. This is not consistent with scientific practice. I will consider on what grounds extra-local knowledge inferences that transcend the boundaries of locality could be seen as justified.     

Can patents prohibit research? On the social epistemology of patenting and licensing in science

A topic of growing importance within philosophy of science is the epistemic implications of the organization of research. This paper identifies a promising approach to social epistemology—nonideal systems design—and uses it to examine one important aspect of the organization of research, namely the system of patenting and licensing and its role in structuring the production and dissemination of knowledge. The primary justification of patenting in science and technology is consequentialist in nature. Patenting should incentivize research and thereby promote the development of knowledge, which in turn facilitates social progress. Some have disputed this argument, maintaining that patenting actually inhibits knowledge production. In this paper, I make a stronger argument; in some areas of research in the US—in particular, research on GM seeds—patents and patent licenses can be, and are in fact being, used to prohibit some research. I discuss three potential solutions to this problem: voluntary agreements, eliminating patents, and a research exemption. I argue against eliminating patents, and I show that while voluntary agreements and a research exemption could be helpful, they do not sufficiently address the problems of access that are discussed here. More extensive changes in the organization of research are necessary.     

Science, truth and history, part II. Metaphysical bolt-holes for the Sociology of Scientific Knowledge?

Historians of science have frequently sought to exclude modern scientific knowledge from their narratives. Part I of this paper, published in the previous issue, cautioned against seeing more than a literary preference at work here. In particular, it was argued—contra advocates of the Sociology of Scientific Knowledge (SSK)—that a commitment to epistemological relativism should not be seen as having straightforward historiographical consequences. Part II considers further SSK-inspired attempts to entangle the currently fashionable historiography with particular positions in the philosophy of science. None, I argue, is promising. David Bloor’s proposed alliance with scientific realism relies upon a mistaken view of contrastive explanation; Andrew Pickering’s appeal to instrumentalism is persuasive for particle physics but much less so for science as a whole; and Bruno Latour’s home-grown metaphysics is so bizarre that its compatibility with SSK is, if anything, a further blow to the latter’s plausibility.     

Ten reasons to embrace scientism

A strong version of scientism, such as that of Alex Rosenberg, says, roughly, that natural science reliably delivers rational belief or knowledge, whereas common sense sources of belief, such as moral intuition, memory, and introspection, do not. In this paper I discuss ten reasons that adherents of scientism have or might put forward in defence of scientism. The aim is to show which considerations could plausibly count in favour of scientism and what this implies for the way scientism ought to be formulated. I argue that only three out of these ten reasons potentially hold water and that the evidential weight is, therefore, on their shoulders. These three reasons for embracing scientism are, respectively, particular empirical arguments to the effect that there are good debunking explanations for certain common sense beliefs, that there are incoherences and biases in the doxastic outputs of certain common sense sources of belief, and that beliefs that issue from certain common sense doxastic sources are illusory. From what I argue, it follows that only a version of scientism that is significantly weaker than many versions of scientism that we find in the literature is potentially tenable. I conclude the paper by stating what such a significantly weaker version of scientism could amount to.     

Immanent philosophy of X

In this paper I examine the relationship between historians, philosophers and sociologists of science, and indeed scientists themselves. I argue that (i) they co-habit a shared intellectual territory (science and its past); and (ii) they should be able to do so peacefully, and with mutual respect, even if they disagree radically about how to describe the methods and results of science. I then go on to explore some of the challenges to mutually respectful cohabitation between history, philosophy and sociology of science. I conclude by identifying a familiar kind of project in the philosophy of science which seeks to explore the worldview of a particular scientific discipline, and argue that it too has a right to explore the shared territory even though some historians and sociologists may find it methodologically suspect.     

Process tracing in political science: What's the story?

Methodologists in political science have advocated for causal process tracing as a way of providing evidence for causal mechanisms. Recent analyses of the method have sought to provide more rigorous accounts of how it provides such evidence. These accounts have focused on the role of process tracing for causal inference and specifically on the way it can be used with case studies for testing hypotheses. While the analyses do provide an account of such testing, they pay little attention to the narrative elements of case studies. I argue that the role of narrative in case studies is not merely incidental. Narrative does cognitive work by both facilitating the consideration of alternative hypotheses and clarifying the relationship between evidence and explanation. I consider the use of process tracing in a particular case (the Fashoda Incident) in order to illustrate the role of narrative. I argue that process tracing contributes to knowledge production in ways that the current focus on inference tends to obscure.     

Re-orienting discussions of scientific explanation: A functional perspective

Philosophy of science offers a rich lineage of analysis concerning the nature of scientific explanation, but the vast majority of this work, aiming to provide an analysis of the relation that binds a given explanans to its corresponding explanandum, presumes the proper analytic focus rests at the level of individual explanations. There are, however, other questions we could ask about explanation in science, such as: What role(s) does explanatory practice play in science? Shifting focus away from explanations, as achievements, toward explaining, as a coordinated activity of communities, the functional perspective aims to reveal how the practice of explanatory discourse functions within scientific communities given their more comprehensive aims and practices. In this paper, I outline the functional perspective, argue that taking the functional perspective can reveal important methodological roles for explanation in science, and consequently, that beginning here provides resources for developing more adequate responses to traditional concerns. In particular, through an examination of the ideal gas law, I emphasize the normative status of explanations within scientific communities and discuss how such status underwrites a compelling rationale for explanatory power as a theoretical virtue.     

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.     

Philosophy of science for globalized privatization: Uncovering some limitations of critical contextual empiricism

The purpose of this paper is to uncover some of the limitations that critical contextual empiricism, and in particular Longino's contextualism, faces when trying to provide a normative account of scientific knowledge that is relevant to current scientific research. After presenting the four norms of effective criticism, I show how the norms have limited scope when dealing with cases of current scientific practices. I then present some historical evidence for the claim that the organization of science has changed in recent decades, and I argue that the uncovered limitations emerge from this larger phenomenon. Finally, I conclude by suggesting two ways to overcome the previously uncovered limitations.     

Introspection and change in Carnap’s logical behaviourism

In the 1930s, Carnap set out to incorporate psychology into the unity of science, by showing that all cognitively meaningful sentences of psychology can be translated into the language of physics. I will argue that Carnap, relying on his notion of protocol languages, defends a physicalistic philosophy of psychology that shows due appreciation of ‘introspection’ as a strictly subjective, but reliable way to verify sentences about one’s own mind. Second, I will point out that Carnap’s philosophy of psychology not only takes into account overt behaviour, but must comprise neurophysiological processes as well. Last, I will show that Carnap aims to develop a philosophy of psychology that does justice to the ongoing changeability of scientific knowledge.     

How to infer explanations from computer simulations

Computer simulations are involved in numerous branches of modern science, and science would not be the same without them. Yet the question of how they can explain real-world processes remains an issue of considerable debate. In this context, a range of authors have highlighted the inferences back to the world that computer simulations allow us to draw. I will first characterize the precise relation between computer and target of a simulation that allows us to draw such inferences. I then argue that in a range of scientifically interesting cases they are particular abductions and defend this claim by appeal to two case studies.     

Thomas Reid and the problem of induction: from common experience to common sense

By the middle of the eighteenth century the new science had challenged the intellectual primacy of common experience in favor of recondite, expert and even counter-intuitive knowledge increasingly mediated by specialized instruments. Meanwhile modern philosophy had also problematized the perceptions of common experience — in the case of David Hume this included our perception of causal relations in nature, a fundamental precondition of scientific endeavor.In this article I argue that, in responding to the ‘problem of induction’ as advanced by Hume, Reid reformulated Aristotelian foundationalism in distinctly modern terms. An educator and mathematician self-consciously working within the framework of the new science, Reid articulated a philosophical foundation for natural knowledge anchored in the human constitution and in processes of adjudication in an emerging modern public sphere of enlightened discourse. Reid thereby transformed one of the bases of Aristotelian science — common experience — into a philosophically and socially justified notion of ‘common sense’. Reid's intellectual concerns had as much to do with the philosophy of science as they did with moral philosophy or epistemology proper, and were bound up with wider social and scientific changes taking place in the early modern period.     

Pure science and the problem of progress

How should we understand scientific progress? Kuhn famously discussed science as its own internally driven venture, structured by paradigms. He also famously had a problem describing progress in science, as problem-solving ability failed to provide a clear rubric across paradigm change—paradigm changes tossed out problems as well as solving them. I argue here that much of Kuhn’s inability to articulate a clear view of scientific progress stems from his focus on pure science and a neglect of applied science. I trace the history of the distinction between pure and applied science, showing how the distinction came about, the rhetorical uses to which the distinction has been put, and how pure science came to be both more valued by scientists and philosophers. I argue that the distinction between pure and applied science does not stand up to philosophical scrutiny, and that once we relinquish it, we can provide Kuhn with a clear sense of scientific progress. It is not one, though, that will ultimately prove acceptable. For that, societal evaluations of scientific work are needed.