A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge bioengineering (...) scientists integrate the cognitive, social, material, and cultural dimensions of practice. Her findings and conclusions have broad implications for researchers in philosophy, science studies, cognitive science, and interdisciplinary studies, as well as scientists, educators, policy makers, and funding agencies. In studying the epistemic practices of scientists, Nersessian pushes the boundaries of the philosophy of science and cognitive science into areas not ventured before. She recounts a decades-long, wide-ranging, and richly detailed investigation of the innovative interdisciplinary modeling practices of bioengineering researchers in four university laboratories. She argues and demonstrates that the methods of cognitive ethnography and qualitative data analysis, placed in the framework of distributed cognition, provide the tools for a philosophical analysis of how scientific discoveries arise from complex systems in which the cognitive, social, material, and cultural dimensions of problem-solving are integrated into the epistemic practices of scientists. Specifically, she looks at how interdisciplinary environments shape problem-solving. Although Nersessian’s case material is drawn from the bioengineering sciences, her analytic framework and methodological approach are directly applicable to scientific research in a broader, more general sense, as well. (shrink)

Three accounts of effective realism (ER) have been advanced to solve three problems for scientific realism: Fraser and Vickers (forthcoming) develop a version of ER about non-relativistic quantum mechanics that they argue is compatible with all the main realist versions (‘interpretations’) of quantum mechanics avoiding the problem of underdetermination among them; Williams (2019) and Fraser (2020b) propose ER about quantum field theory as a response to the problems facing realist interpretations; Robertson and Wilson (forthcoming) propose ER to deal with the (...) dubious ontological status of the entities belonging to superseded theories. This paper argues for the unification of these proposals based on realism about modal structure and the idea of scale relativity of ontology developed by ontic structural realists. This solves problems some or all the accounts of ER face, especially that of making explicit in what way they are realist. Furthermore, we respond to a recent critique that has been raised against the ontic structural realist account of quantum mechanics that we employ. (shrink)

A long-standing problem in understanding goal-directed systems has been the insufficiency of mechanistic explanations to make sense of them. This paper offers a solution to this problem. It begins by observing the limitations of mechanistic decompositions when it comes to understanding physical fields. We argue that introducing the field concept, as it has been developed in field theory, alongside mechanisms is able to provide an account of goal directedness in the sciences.

Here we defend the view that one ought to categorize and classify at least some mental disorders as clusters of interrelated dysfunctions of (usually, several) cognitive capacities – that is, the kinds of capacities that are postulated in cognitive science; capacities that are understood as entities that are primarily individuated in cognitive-functional terms (CF-systems); systems that have a set of peculiar properties in their manner of operation when processing information or representations. Usually, some of the mental disorders postulated in psychiatry (...) are clinically heterogeneous with respect to their symptoms, and tend to be comorbid – that is, one disorder is often accompanied by other disorders – for example, schizophrenia often comes with major depression. We argue that describing the manner in which CF-systems operate within themselves and with other CF-systems as well as with stimuli and other kinds of information can best explain why certain mental disorders are very heterogeneous with respect to their symptoms, and why comorbidity is so frequent among these disorders. A consequence is that both within-category heterogeneity and comorbodity are not necessarily indications of defective classifications but are rather a consequence of the actual cognitive functional architecture itself and are therefore to be expected in these cases. (shrink)

Interdisciplinarity is strongly promoted in science policy across the world. It is seen as a necessary condition for providing practical solutions to many pressing complex problems for which no single disciplinary approach is adequate alone. In this article we model multi- and interdisciplinary research as an instance of collective problem solving. Our goal is to provide a basic representation of this type of problem solving and chart the epistemic benefits and costs of researchers engaging in different forms of cognitive coordination. (...) Our findings suggest that typical forms of interdisciplinary collaboration are unlikely to find optimal solutions to complex problems within short time frames and can lead to methodological conservatism. This provides some grounds for both reflecting on current science policy and envisioning more effective scientific practices with respect to interdisciplinary problem solving. (shrink)

Phylogenetic models traditionally represent the history of life as having a strictly-branching tree structure. However, it is becoming increasingly clear that the history of life is often not strictly-branching; lateral gene transfer, endosymbiosis, and hybridization, for example, can all produce lateral branching events. There is thus motivation to allow phylogenetic models to have a reticulate structure. One proposal involves the reconciliation of genealogical discordance. Briefly, this method uses patterns of disagreement – discordance – between trees of different genes to add (...) lateral branching events to phylogenetic trees of taxa, and to estimate the most likely cause of these events. I use this practice to argue for: (1) a need for expanded accounts of multiple-models idealization, (2) a distinction between automatic and manual de-idealization, and (3) recognition that idealization may serve the meso-level aims of science in a different way than hitherto acknowledged. (shrink)

This is a paper about the methodology of normative ethics. I claim that much work in normative ethics can be interpreted as modelling, the form of inquiry familiar from science, involving idealised representations. I begin with the anti-theory debate in ethics, and note that the debate utilises the vocabulary of scientific theories without recognising the role models play in science. I characterise modelling, and show that work with these characteristics is common in ethics. This establishes the plausibility of my interpretation. (...) Taking methodological inspiration from modelling in science gives us new tools for managing idealisations, and a new perspective on pluralism. I demonstrate why this interpretation is a fruitful way of interpreting ethics, by looking at three case studies. First, I return to the anti-theory debate and argue that modelling opens up a new middle ground. Second, I argue that a modelling lens offers a new way of understanding impossibility theorems in population ethics, and their bearing on ethics as a whole. Finally, I show how viewing our work as modelling can be deployed in debates within ethics, using the debate over prioritarianism as an example. I close with further methodological suggestions for those who choose to see themselves as modellers. I discuss the role of counterexamples, our responses to moral disagreement, and the training of new ethicists. (shrink)

In western philosophy and beyond, a tension between pluralism and monism has sparked many developments and debates. Pluralism of norms, of forms of knowledge, of aesthetic and moral values, of interests etc. has often been pitted against monism. Monism usually implies a hierarchical order of such norms etc. After having traced the origin of this tension between pluralism and monism in ancient tragedy and philosophy, I’m asking in this article whether a rejection of monism and embrace of pluralism necessarily raises (...) the specter of inconsistency and contradiction. The threat of inconsistency need not be associated with pluralism as even with regard to logic an argument can be made for a ‘multiplicity of logics’, as van Lambalgen and Stenning argue in several places. They refer to the varieties in reasoning that can be observed in humans and which are partly due to there being ‘dual systems’ of reasoning: System 1 processes information fast, automatized, and emotional, while System 2 is rather slow, more deliberative, and more rational. In contrast to a widely held view, the authors argue that System 1 processing is not without logic, even though it is a different form of logic from System 2. In addition, the multiplicity of logics they discuss is related to the multiple semantics required for distinct domains of reasoning. This perspective raises the subsequent question how this pluralism can be available while maintaining consistency, how should the available options be configured or related to each other? In the remainer of this chapter I’m addressing several such options for configurating pluralism like: non-foundational pluralism and foundational pluralism, moderate or temporary pluralism, antagonistic pluralism, incompatible pluralism, incommensurable pluralism, ‘Anything goes’ pluralism, complementary pluralism, integrative pluralism, and interactive pluralism. The discussion and examples of these options show that irrespective of its domain, the encounter with different configurations of pluralism shows how some forms of pluralism are likely to be productive, whereas others are less so - which is an important lesson given the prominent pluralism of pluralisms in philosophy and beyond. (shrink)

One of the biggest problems in applications of animal welfare science is our ability to make comparisons between different individuals, particularly different species. Although welfare science provides methods for measuring the welfare of individual animals, there’s no established method for comparing measures between individuals. This problem occurs because of the underdetermination of the conclusions given the data, arising from two sources of variation that we cannot distinguish – variation in the underlying target variable (welfare experience) and in the relationship of (...) measured indicators to the target. In this paper I describe the similarity assumptions that underlie our current applications of interspecies comparisons and examine in which cases they are justified, as well as describing alternative methods we may use when they are not. In the end, all our available options for making interspecies comparisons are imperfect, and we need to make explicit context-specific decisions about which will be best for the task at hand while acknowledging their potential limitations. Future developments in our understanding of the biology of sentience will help strengthen our methods of making welfare comparisons. (shrink)

This chapter examines the influence of the empirical sciences (e.g., physics, biology, psychology) in contemporary analytic philosophy, with focus on philosophical theories that are guided by findings from the empirical sciences. Scientific approaches to philosophy follow a tradition of philosophical naturalism associated with Quine, which strives to ally philosophical methods and theories more closely with the empirical sciences and away from a priori theorizing and conceptual analysis.

Many philosophers of science are ontologically committed to a lush rainforest of special science entities ), but are often reticent about the criteria that determine which entities count as real. On the other hand, the metaphysics literature is much more forthcoming about such criteria, but often links ontological commitment to irreducibility. We argue that the irreducibility criteria are in tension with scientific realism: for example, they would exclude viruses, which are plausibly theoretically reducible and yet play a sufficiently important role (...) in scientific accounts of the world that they should be included in our ontology. In this paper, we show how the inhabitants of the rainforest can be inoculated against the eliminative threat of reduction: by demonstrating that they are emergent. According to our account, emergence involves a screening off condition as well as novelty. We go on to demonstrate that this account of emergence, which is compatible with theoretical reducibility, satisfies common intuitions concerning what should and shouldn't count as real: viruses are emergent, as are trouts and turkeys, but philosophically gerrymandered objects like trout-turkeys do not qualify. (shrink)

There are at least two senses in which human beings can be called “naturally artificial”: being adapted for creation of and participation in niche constructed environments, and being adapted for creation of and participation in such environments despite an exceptional indeterminacy in the details of the niche constructed environments themselves. The former puts human beings in a common category with many niche-constructing organisms while the latter is arguably distinctive of our species. I explain how this can be so by developing (...) an account of supporting concepts of complexity, contingency, and content-openness, and show how to defend the position against a common style of objection by a single comparative case study: hermit crabs and their shells versus humans and their movable dwellings. Finally, I consider evidence that such a feature is indeed species-typical and evolved in human populations. (shrink)

I argue that normative formal epistemology (NFE) is best understood as modelling, in the sense that this is the reconstruction of its methodology on which NFE is doing best. I focus on Bayesianism and show that it has the characteristics of modelling. But modelling is a scientific enterprise, while NFE is normative. I thus develop an account of normative models on which they are idealised representations put to normative purposes. Normative assumptions, such as the transitivity of comparative credence, are characterised (...) as modelling idealisations motivated normatively. I then survey the landscape of methodological options: what might formal epistemologists be up to? I argue the choice is essentially binary: modelling or theorising. If NFE is theorising it is doing very poorly: generating false claims with no clear methodology for separating out what is to be taken seriously. Modelling, by contrast, is a successful methodology precisely suited to the management of useful falsehoods. Regarding NFE as modelling is not costless, however. First, our normative inferences are less direct and are muddied by the presence of descriptive idealisations. Second, our models are purpose-specific and limited in their scope. I close with suggestions for how to adapt our practice. (shrink)

William Whewell’s 19th century philosophy of science is sometimes glossed over as a footnote to Kant. There is however a key feature of Whewell’s account worth noting. This is his appeal to Aristotle’s form/matter hylomorphism as a metaphor to explain how mind and world merge in successful scientific inquiry. Whewell’s hylomorphism suggests a middle way between rationalism and empiricism reminiscent of experience pragmatists like Steven Levine’s view that mind and world are entwined in experience. I argue however that Levine does (...) not adequately explain exactly how mind and world entwine. He could nonetheless do so if he appealed to Whewell’s hylomorphic metaphor. We may prefer a reductive metaphysical explanation, but I suggest that pragmatists only have recourse to metaphor in this case. Both reductive and metaphorical explanations can enjoy great explanatory power if they exhibit a suitable measure of what I will call sematic distance. Semantic distance measures how close or how far apart explanandum and explanans are from each other in meaning. Metaphorical explanation - as evident in Whewell’s hylomorphism and as detailed via the notion of semantic distance - presents a valuable new explanatory tool to those who hold that mind and world are entwined sans recourse to metaphysics. (shrink)

We review some of the major accounts in the current epistemology of modality and identify some shared issues that plague all of them. In order to provide insight into the nature of modal statements in science, philosophy, and beyond, a satisfactory epistemology of modality would need to be suitably applicable to practical and theoretical contexts by limited beings. However, many epistemologies of modality seem to work only when we have access to the kind of knowledge that is at least currently (...) beyond our reach. Or, in the extreme case, it is argued that even if we knew all the relevant information about the respective domain – or even the entire state of the world – there would still remain a special class of modal truths that would be left unaccounted for. Neither picture bodes well for practical applicability, nor for the philosophical justification of these epistemologies. This is especially the case as we hold that one of the main motivations for modal inquiry typically arises in cases of imperfect information and limited cognitive resources. We close by providing a partial remedy to the situation by suggesting an overall framework of relative modality (RM) that can be used to both unify some existing modal epistemologies and, at the same time, make them more metaphysically modest. (shrink)

This paper examines two parallel discussions of scientific modeling which have invoked experimentation in addressing the role of models in scientific inquiry. One side discusses the experimental character of models, whereas the other focuses on their exploratory uses. Although both relate modeling to experimentation, they do so differently. The former has considered the similarities and differences between models and experiments, addressing, in particular, the epistemic value of materiality. By contrast, the focus on exploratory modeling has highlighted the various kinds of (...) exploratory functions of models in the early stages of inquiry. These two perspectives on modeling are discussed through a case study in the field of synthetic biology. The research practice in question explores biological control by making use of an ensemble of different epistemic means: mathematical models and simulations, synthetic genetic circuits and intracellular measuring devices, and finally electronic circuits. We argue that the study of exploratory modeling should trace the ways different epistemic means, in different materialities, are being combined over time. Finally, the epistemic status of such novel investigative objects as synthetic genetic circuits is evaluated, with the conclusion that they can function as both experiments and models. (shrink)

ABSTRACT This paper compares Spinoza with Daniel Dennett and uncovers a number of striking parallels. Genevieve Lloyd’s recent work on Spinoza reveals a picture of a philosopher that anticipated many of Dennett’s later ideas. Both share a fervent opposition to Descartes’ conception of mind and body and endorse a strikingly similar naturalist philosophy. It is the goal of this paper to tease out these connections and once again highlight the richness of a Spinozist lens of the world.

Bio-ontologies are digital frameworks for handling biological and biomedical data. They consist of theoretical entities and relations with explicitly defined logical structures and precise definitions, whose purpose is to provide a shared language for representing information to be distributed and integrated across diverse scientific contexts. It is tempting to view bio-ontologies as clear and formal expressions of a scientific community’s ontological commitments about their domain of inquiry, and to view their integration as tantamount to the metaphysical unification of science that (...) some philosophers have envisaged. However, I argue that the local, practical, social and technological factors that influence their design prevent us from straightforwardly reading metaphysical conclusions from them. I discuss these complications and suggest how they can be overcome, revealing more general lessons for the development of a well-founded scientific metaphysics. (shrink)

Teleology has a complicated history in the biological sciences. Some have argued that Darwin’s theory has allowed biology to purge itself of teleological explanations. Others have been content to retain teleology and to treat it as metaphorical, or have sought to replace it with less problematic notions like teleonomy. And still others have tried to naturalize it in a way that distances it from the vitalism of the nineteenth century, focusing on the role that function plays in teleological explanation. No (...) consensus has seemed possible in this debate. This paper takes a different approach. It argues that teleology is a perfectly acceptable scientific notion, but that the debate took an unfortunate misstep some 2300 years ago, one that has confused things ever since. The misstep comes in the beginning of Aristotle’s Physics when a distinction is made between two types of teleological explanation. One type pertains to artifacts while the other pertains to entities in nature. For Aristotle, artifacts are guided by something external to themselves, human intentions, while natural entities are guided by an internal nature. We aim to show that there is, in fact, only one type of legitimate teleological explanation, what Aristotle would have considered a variant of an artifact model, where entities are guided by external fields. We begin with an analysis of the differences between the two types of explanation. We then examine some evidence in Aristotle’s biological works suggesting that on account of his natural-artifactual distinction, he encountered difficulties in trying to provide teleological accounts of spontaneous generation. And we show that it is possible to resolve these difficulties with a more robust version of an artifact model of teleology, in other words, with an externalist teleology. This is McShea’s model, in which goal-directed entities are guided by a nested series of upper-level fields. To explain teleological behavior, this account invokes only external physical forces rather than mysterious internal natures. We then consider how field theory differs from other efforts to naturalize teleology in biology. And finally, we show how the account enables us to grapple with certain difficult cases – genes and intentions – where, even in biology today, the temptation to posit internal natures remains strong. (shrink)

Jonathan Y. Tsou examines and defends positions on central issues in philosophy of psychiatry. The positions defended assume a naturalistic and realist perspective and are framed against skeptical perspectives on biological psychiatry. Issues addressed include the reality of mental disorders; mechanistic and disease explanations of abnormal behavior; definitions of mental disorder; natural and artificial kinds in psychiatry; biological essentialism and the projectability of psychiatric categories; looping effects and the stability of mental disorders; psychiatric classification; and the validity of the DSM's (...) diagnostic categories. The main argument defended by Tsou is that genuine mental disorders are biological kinds with harmful effects. This argument opposes the dogma that mental disorders are necessarily diseases that result from biological dysfunction. Tsou contends that the broader ideal of biological kinds offers a more promising and empirically ascertainable naturalistic standard for assessing the reality of mental disorders and the validity of psychiatric categories. (shrink)

In a recent special issue dedicated to Dani Rodrik’s (2015) influential monograph Economics Rules, Grüne-Yanoff and Marchionni (2018) raise a potentially damning problem for Rodrik’s suggestion that progress in economics should be understood and measured laterally, by a continuous expansion of new models. They argue that this could lead to an “embarrassment of riches”, i.e. the rapid expansion of our model library to such an extent that we become unable to choose between the available models, and thus needs to be (...) solved to make ‘model pluralism’ viable. Drawing on Veit’s (2019a) ‘model pluralism’ account, this paper argues that model pluralism as a thesis about the relationship between science and nature undermines the very idea of a general model selection framework for policy making. (shrink)

Introduction: Interdisciplinary, transdisciplinary and action research of a city in lockdown. As we write this chapter, most cities across the world are subject to a similar set of measures due to the spread of COVID-19 coronavirus, which is now a global pandemic. Independent of city size, location, or history, an observer would note that almost all cities have now ground to a halt, with their citizens being confined to their private dwellings, social and public gatherings being almost entirely forbidden, and (...) commercial areas being nearly devoid of visitors. Striking as these apparent similarities are, closer scrutiny would reveal important differences between cities and within cities – differences that can be highly relevant to consider when scholars are assessing the responses of cities to this pandemic or trying to predict the consequences of those responses. For example, the public health systems in some cities are better prepared than in others for coping with the increasing number of patients in life threatening conditions. Multigenerational households, which are associated with a greater risk for elderly members, are not equally common in all cities. Tourist destinations have taken a more severe economic hit from the lockdown than those cities which are economically less dependent upon this particular source of income. Communal celebrations in one city will result in a higher number of contagions and perhaps even deaths in this situation, whereas that same social fabric generally does contribute to a population’s health. The pandemic has also had unprecedented effects on differences and inequalities within cities. In cities in the United States, neighborhoods primarily inhabited by African Americans have been disproportionately affected by COVID-19 due to living and health conditions, yet also due to the fact they disproportionately perform vital jobs. Parks and green spaces are crowded, while city centers like Amsterdam’s Red Light District have suddenly lost the bustle of tourism, providing opportunities for citizens to reoccupy scarce public spaces and reclaim ownership. Clearly, such differences between cities are in many cases only discernible to the eye of an expert, possessing the necessary background knowledge to interpret the perceptible local changes caused by the global pandemic. Typically, drawing upon his or her disciplinary training, the expert also knows how to further probe the impact of the pandemic in an appropriate way. However, compared to the usual application of expertise, this crisis situation might, in an unusual way, test even experts. For the pandemic has created a unique situation, imposing unfamiliar constraints on the health, economic, social, and other conditions of cities, constraints that interact in sometimes unexpected ways with each other. Such interactions in turn force experts to collaborate across the boundaries commonly associated with disciplines, their concepts, theories, methods, and assumptions (Klein, 1996). These brief observations of how a virus pandemic can have differential impacts upon various cities, and what this exceptional situation might mean for the application of city methods, allow us to draw a few consequences for the current context of this chapter on interdisciplinary and transdisciplinary research. First, whenever we are investigating a complex and dynamic phenomenon it is by no means easy to determine which disciplinary perspectives are required to do justice to it. Indeed, the choice of useful disciplines can only be made after an initial overview of the situation and a preliminary selection of what appear to be the most important features of the situation. Relevance is key in guiding this selection process and scholars must remain open to the possibility that they may need to revise their earlier assessments of what is relevant and what is not. Second, if scholars from different disciplines were to study different features of a city in isolation, their ‘multidisciplinary’ account would miss important dynamic and complex interactions, such as those between a city’s demographics and geographical situation, its governance and economy. In other words, it is the integration of the perspectives of different disciplines that is crucial, as only then are such interactions taken into account. Indeed, this integration between disciplinary perspectives is what distinguishes an interdisciplinary from a multidisciplinary account. Thirdly, in addition to checking the relevance of disciplines and aiming for their integration, the outcome of interdisciplinary and transdisciplinary research has typically limited generalizability. Since a city is sensitive to a multitude of internal and external dynamical factors, in ways that partly rest upon its socio-cultural history, its investigation will often have the nature of a case study rather than be capable of leading to law-like insights (Krohn, 2010; Menken & Keestra, 2016). As can be seen from these three characteristics of ascertaining the relevance of different disciplinary contributions, the challenge of their integration, and the limited generalizability of their results owing to the specificity of interdisciplinary (ID) and transdisciplinary (TD) research, such research into ‘real world problems’ is clearly distinct from most monodisciplinary research. A consequence of this distinction is the absence of a general ID/TD methodology that can guide specific case studies. By contrast, the collaboration implied in such research requires researchers – and stakeholders, if they are involved – to reflect upon their potential contribution and the implicit assumptions associated with that. We will elaborate on this in the next section. Next, we offer several typologies of integration that urban scholars could employ for their research projects, after which we will offer a few brief analyses of initial collaborations of urban research. Finally, we discuss in more detail the process of the interdisciplinary research project. This will include a brief reflection upon the decision-making process that is implied in such projects. In sum, we aim to provide some guidance in conducting an ID/TD project, albeit not in the form of a definite methodology. (shrink)

We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR view provides insight into the common (...) but little-discussed practices of iteratively reusing and repurposing data, which result in many datasets’ having a phylogeny—an origin and complex evolutionary history—that is relevant to their evaluation and future use. We relate these insights to the open-data and data-rescue movements, and highlight several future avenues of research that build on the PR view of data. (shrink)

This paper reviews the contemporary discussion on the epistemological and ontological effects of Big Data within social science, observing an increased focus on relationality and complexity, and a tendency to naturalize social phenomena. The epistemic limits of this emerging computational paradigm are outlined through a comparison with the discussions in the early days of digitalization, when digital technology was primarily seen through the lens of dematerialization, and as part of the larger processes of “postmodernity”. Since then, the online landscape has (...) become increasingly centralized, and the “liquidity” of dematerialized technology has come to empower online platforms in shaping the conditions for human behavior. This contrast between the contemporary epistemological currents and the previous philosophical discussions brings to the fore contradictions within the study of digital social life: While qualitative change has become increasingly dominant, the focus has gone towards quantitative methods; while the platforms have become empowered to shape social behavior, the focus has gone from social context to naturalizing social patterns; while meaning is increasingly contested and fragmented, the role of hermeneutics has diminished; while platforms have become power hubs pursuing their interests through sophisticated data manipulation, the data they provide is increasingly trusted to hold the keys to understanding social life. These contradictions, we argue, are partially the result of a lack of philosophical discussion on the nature of social reality in the digital era; only from a firm metatheoretical perspective can we avoid forgetting the reality of the system under study as we are affected by the powerful social life of Big Data. (shrink)

This discussion centers on two desiderata: the role of measurement in information-gathering and physical interaction in scientific practice. By taking inspiration from van Fraassen’s view, we present a methodological account of perspectival measurement that addresses empirical practice where there is complex intervention, disagreeing results, and limited theory. The specific aim of our account is to provide a methodological prescription for developing measurement processes in the context of limited theory. The account should be useful to philosophers of science, who are interested (...) in the intersection between representation and intervention; scientists, who are interested in methodological suggestions for theory-development and reliability; and interdisciplinary researchers, who are interested in the intersections between the pandemic, built environments, and social processes. We apply the process-view of measurement to COVID-19, specifically, measuring replication in the SARS-CoV-2 virus. The aim is to show that our account tracks key elements—manipulation/intervention, independence, invariance, and theory-development—by organizing unfolding measurement processes. Additionally, we use our account to make prescriptive suggestions for measurement practice in the COVID-19 context by discussing the need to broaden measurement perspective on interaction, manipulation, and production. (shrink)

Animal welfare has a long history of disregard. While in recent decades the study of animal welfare has become a scientific discipline of its own, the difficulty of measuring animal welfare can still be vastly underestimated. There are three primary theories, or perspectives, on animal welfare - biological functioning, natural living and affective state. These come with their own diverse methods of measurement, each providing a limited perspective on an aspect of welfare. This paper describes a perspectival pluralist account of (...) animal welfare, in which all three theoretical perspectives and their multiple measures are necessary to understand this complex phenomenon and provide a full picture of animal welfare. This in turn will offer us a better understanding of perspectivism and pluralism itself. (shrink)

The use of multiple means of determination to “triangulate” on the existence and character of a common phenomenon, object, or result has had a long tradition in science but has seldom been a matter of primary focus. As with many traditions, it is traceable to Aristotle, who valued having multiple explanations of a phenomenon, and it may also be involved in his distinction between special objects of sense and common sensibles. It is implicit though not emphasized in the distinction between (...) primary and secondary qualities from Galileo onward. It is arguably one of several conceptions involved in Whewell’s method of the “consilience of inductions” (Laudan 1971) and is to be found in several places in Peirce. (From M. Brewer and B. Collins, eds., (1981); Scientific Inquiry in the Social Sciences (a festschrift for Donald T. Campbell), San Francisco: Jossey-Bass, pp. 123–162.). (shrink)

Scientists represent their world, grouping and organizing phenomena into classes by means of concepts. Philosophers of science have historically been interested in the nature of these concepts, the criteria that inform their application and the nature of the kinds that the concepts individuate. They also have sought to understand whether and how different systems of classification are related and more recently, how investigative practices shape conceptual development and change. Our aim in this paper is to provide a critical overview of (...) some of the key developments in this philosophical literature and identify some interesting issues it raises about the prospects of the so-called “special sciences”, including psychiatry, psychology, and the mind-brain sciences more generally, to discover natural kinds. (shrink)

There have been repeated attempts in the history of comparative biology to provide a mechanistic account of morphological homology. However, it is well-established that homologues can develop from diverse sets of developmental causes, appearing not to share any core causal architecture that underwrites character identity. We address this challenge with a new conceptual model of Character Identity Mechanisms. ChIMs are cohesive mechanisms with a recognizable causal profile that allows them to be traced through evolution as homologues despite having a diverse (...) etiological organization. Our model hypothesizes that anatomical units at different levels of organization—cell types, tissues, and organs—have level-specific ChIMs with different conserved parts, activities, and organization. Relying on a methodology of conceptual engineering, we show how the ChIM concept advances our understanding of the developmental basis of morphological characters, while forging an important link between comparative and mechanistic biology. (shrink)

Sustainability science seeks to extend scientific investigation into domains characterized by a distinct problem-solving agenda, physical and social complexity, and complex moral and ethical landscapes. In this endeavor it arguably pushes scientific investigation beyond its usual comfort zones, raising fundamental issues about how best to structure such investigation. Philosophers of science have long scrutinized the structure of science and scientific practices, and the conditions under which they operate effectively. We propose a critical engagement between sustainability scientists and philosophers of science (...) with respect to how to engage in scientific activity in these complex domains. We identify specific issues philosophers of science raise concerning current sustainability science and the contributions philosophers can make to resolving them. In conclusion we reflect on the steps philosophers of science could take to advance sustainability science. (shrink)

Philosophy of immunology is a subfield of philosophy of biology dealing with ontological and epistemological issues related to the studies of the immune system. While speculative investigations and abstract analyses have always been part of immune theorizing, until recently philosophers have largely ignored immunology. Yet the implications for understanding the philosophical basis of organismal functions framed by immunity offer new perspectives on fundamental questions of biology and medicine. Developed in the context of history of medicine, theoretical biology, and medical anthropology, (...) philosophy of immunology differs from these related branches of study in its focus on traditional philosophical questions concerning identity, individuality, ecology, cognition, scientific methodology and theory construction. This broad agenda derives from immunology’s multifaceted research program that has developed from its initial clinical challenges of host defense, transplantation, autoimmunity, tumor immunology, and allergy. In addition to these well-established research areas, immunity is now understood to play a central role in other physiological functions, development, ecology, and evolutionary mechanics. Holding together these diverse domains of inquiry lie philosophical commitments oriented by organismal identity. In this regard, pertinent issues are raised concerning cognition (organization of immune perception and information processing), the character of individuality (framed by the ecological context of immune-mediated assimilation and rejection), and the dynamics of complex systems (understood as holistic systems biology). Indeed, immunology, in the context of cognitive science, evolutionary biology, environmental sciences, and development provides multi-focal perspectives for philosophy of science. (shrink)

I develop an interdisciplinary framework for understanding the nature of agents and agency that is compatible with recent developments in the metaphysics of science and that also does justice to the mechanistic and normative characteristics of agents and agency as they are understood in moral philosophy, social psychology, neuroscience, robotics, and economics. The framework I develop is internal perspectivalist. That is to say, it counts agents as real in a perspective-dependent way, but not in a way that depends on an (...) external perspective. Whether or not something counts as an agent depends on whether it is able to have a certain kind of perspective. My approach differs from many others by treating possession of a perspective as more basic than the possession of agency, representational content/vehicles, cognition, intentions, goals, concepts, or mental or psychological states; these latter capabilities require the former, not the other way around. I explain what it means for a system to be able to have a perspective at all, beginning with simple cases in biology, and show how self-contained normative perspectives about proper function and control can emerge from mechanisms with relatively simple dynamics. I then describe how increasingly complex control architectures can become organized that allow for more complex perspectives that approach agency. Next, I provide my own account of the kind of perspective that is necessary for agency itself, the goal being to provide a reference against which other accounts can be compared. Finally, I introduce a crucial distinction that is necessary for understanding human agency: that between inclinational and committal agency, and venture a hypothesis about how the normative perspective underlying committal agency might be mechanistically realized. (shrink)

In biomedical measurement, biomarkers are used to achieve reliable prediction of, and useful causal information about patient outcomes while minimizing complexity of measurement, resources, and invasiveness. A biomarker is an assayable metric that discloses the status of a biological process of interest, be it normative, pathophysiological, or in response to intervention. The greatest utility from biomarkers comes from their ability to help clinicians (and researchers) make and evaluate clinical decisions. In this paper we discuss a specific methodological use of clinical (...) biomarkers in pharmacological measurement: Some biomarkers, called ‘surrogate markers’, are used to substitute for a clinically meaningful endpoint corresponding to events and their penultimate risk factors. We confront the reliability of clinical biomarkers that are used to gather information about clinically meaningful endpoints. Our aim is to present a systematic methodology for assessing the reliability of multiple surrogate markers (and biomarkers in general). To do this we draw upon the robustness analysis literature in the philosophy of science and the empirical use of clinical biomarkers. After introducing robustness analysis we present two problems with biomarkers in relation to reliability. Next, we propose an intervention-based robustness methodology for organizing the reliability of biomarkers in general. We propose three relevant conditions for a robust methodology for biomarkers: (R1) Intervention-based demonstration of partial independence of modes: In biomarkers partial independence can be demonstrated through exogenous interventions that modify a process some number of “steps” removed from each of the markers. (R2) Comparison of diverging and converging results across biomarkers: By systematically comparing partially-independent biomarkers we can track under what conditions markers fail to converge in results, and under which conditions they successfully converge. (R3) Information within the context of theory: Through a systematic cross-comparison of the markers we can make causal conclusions as well as eliminate competing theories. We apply our robust methodology to currently developing Alzheimer’s research to show its usefulness for making causal conclusions. (shrink)

Scientists appeal to models when explaining phenomena. Such explanations are often dubbed model explanations or model-based explanations. But what are the precise conditions for ME? Are ME special explanations? In our paper, we first rebut two definitions of ME and specify a more promising one. Based on this analysis, we single out a related conception that is concerned with explanations that are induced from working with a model. We call them ‘model-induced explanations’. Second, we study three paradigmatic cases of alleged (...) ME. We argue that all of them are MIE, upon closer examination. Third, we argue that this undermines the building consensus that model explanations are special explanations that, e.g., challenge the factivity of explanation. Instead, it suggests that what is special about models in science is the epistemology behind how models induce explanations. (shrink)

In this paper, I first outline the view developed in my recent book on the role of idealization in scientific understanding. I discuss how this view leads to the recognition of a number of kinds of variability among scientific representations, including variability introduced by the many different aims of scientific projects. I then argue that the role of idealization in securing understanding distances understanding from truth, but that this understanding nonetheless gives rise to scientific knowledge. This discussion will clarify how (...) my view relates to three other recent books on understanding by Henk de Regt, Catherine Elgin, and Kareem Khalifa. (shrink)

We critique the organizational account of biological functions by showing how its basis in the closure of constraints fails to be objective. While the account treats constraints as objective features of physical systems, the number and relationship of potential constraints are subject to potentially arbitrary redescription by investigators. For example, we show that self-maintaining systems such as candle flames can realize closure on a more thorough analysis of the case, contradicting the claim that these “simple” systems lack functional organization. This (...) also raises problems for Moreno and Mossio’s associated theory of biological autonomy, which asserts that living beings are distinguished by their possession of a closed system of constraints that channel and regulate their metabolic processes. (shrink)

This paper applies the theoretical criteria laid out by D’Arms et al. to various aspects of evolutionary models of signalling. The question that D’Arms et al. seek to answer can be formulated as follows: Are the models that we use to explain the phenomena in question conceptually adequate? The conceptual adequacy question relates the formal aspects of the model to those aspects of the natural world that the model is supposed to capture. Moreover, this paper extends the analysis of D’Arms (...) et al. by asking the following additional question: Are the models that we use sufficient to explain the phenomena in question? The sufficiency question asks what formal resources are minimally required for the model to get the right results most of the time. (shrink)

Despite its pervasiveness, the concept of ‘levels of organization’ has received relatively little attention in its own right. I propose here an emerging approach that posits ‘levels’ as a fragmentary concept situated within an interest-relative matrix of operational usage within scientific practice. To this end I propose one important component of meaning, namely the epistemic goal motivating the term’s usage, which recovers a remarkably conserved and sufficiently unifying significance attributable to ‘levels’ across different instances of usage. This epistemic goal, to (...) provide structure to scientific problems, delegates tasks whose execution generates the term’s expressed content in a given instance. This treatment of levels does not diminish the concept’s general importance to science, but rather allows for its use in, and usefulness for, scientific practice to be better contextualized to particular tasks encompassing varying breadths of activity. (shrink)

This paper introduces and defends an account of model-based science that I dub model pluralism. I argue that despite a growing awareness in the philosophy of science literature of the multiplicity, diversity, and richness of models and modeling practices, more radical conclusions follow from this recognition than have previously been inferred. Going against the tendency within the literature to generalize from single models, I explicate and defend the following two core theses: any successful analysis of models must target sets of (...) models, their multiplicity of functions within science, and their scientific context and history and for almost any aspect x of phenomenon y, scientists require multiple models to achieve scientific goal z. (shrink)

Of all the demands that mathematics imposes on its practitioners, one of the most fundamental is that proofs ought to be correct. It has been common since the turn of the twentieth century to take correctness to be underwritten by the existence of formal derivations in a suitable axiomatic foundation, but then it is hard to see how this normative standard can be met, given the differences between informal proofs and formal derivations, and given the inherent fragility and complexity of (...) the latter. This essay describes some of the ways that mathematical practice makes it possible to reliably and robustly meet the formal standard, preserving the standard normative account while doing justice to epistemically important features of informal mathematical justification. (shrink)

I present a novel, collaborative, methodology for linguistics: what I call the ‘explanatory economy’. According to this picture, multiple models/theories are evaluated based on the extent to which they complement one another with respect to data coverage. I show how this model can resolve a long-standing worry about the methodology of generative linguistics: that by creating too much distance between data and theory, the empirical credentials of this research program are tarnished. I provide justifications of such methodologically central distinctions as (...) the competence/performance and core/periphery distinction, and then show how we can understand the push for simplicity in the history of generative grammar in this light. (shrink)

Emergence is much discussed by both philosophers and scientists. But, as noted by Mitchell (2012), there is a significant gulf; philosophers and scientists talk past each other. We contend that this is because philosophers and scientists typically mean different things by emergence, leading us to distinguish being emergence and pattern emergence. While related to distinctions offered by others between, for example, strong/weak emergence or epistemic/ontological emergence (Clayton, 2004, pp. 9–11), we argue that the being vs. pattern distinction better captures what (...) the two groups are addressing. In identifying pattern emergence as the central concern of scientists, however, we do not mean that pattern emergence is of no interest to philosophers. Rather, we argue that philosophers should attend to, and even contribute to, discussions of pattern emergence. But it is important that this discussion be distinguished, not conflated, with discussions of being emergence. In the following section we explicate the notion of being emergence and show how it has been the focus of many philosophical discussions, historical and contemporary. In section 3 we turn to pattern emergence, briefly presenting a few of the ways it figures in the discussions of scientists (and philosophers of science who contribute to these discussions in science). Finally, in sections 4 and 5, we consider the relevance of pattern emergence to several central topics in philosophy of biology: the emergence of complexity, of control, and of goal-directedness in biological systems. (shrink)

A crucial question for a process view of life is how to identify a process and how to follow it through time. The genidentity view can contribute decisively to this project. It says that the identity through time of an entity X is given by a well-identified series of continuous states of affairs. Genidentity helps address the problem of diachronic identity in the living world. This chapter describes the centrality of the concept of genidentity for David Hull and proposes an (...) extension of Hull’s view to the ubiquitous phenomenon of symbiosis. Finally, using immunology as a key example, it shows that the genidentity view suggests that the main interest of a process approach is epistemological rather than ontological and that its principal claim is one of priority, namely that processes precede and define things, and not vice versa. (shrink)

Recently, several critics of the multiple realizability thesis have argued that philosophers have tended to accept the thesis on too weak grounds. On the one hand, the analytic challenge has problematized how philosophers have treated the multiple realization relation itself, claiming that assessment of the sameness of function and the relevant difference of realizers has been uncritical. On the other hand, it is argued that the purported evidence of the thesis is often left empirically unverified. This paper provides a novel (...) strategy to answer these worries by introducing a role for multiple realizability in the context of biological engineering. In the field of synthetic biology, bioengineers redesign the evolutionary realizations of biological functions, even constructing artificial chemical surrogates in the laboratory. I show how in the rational design approach to biological engineering, multiple realizability can function as a design heuristic in which the sameness of function and difference of realizers can be controlled. Although practically motivated, this engineering approach has also a theoretical, exploratory component that can be used to study the empirical limitations of multiple realizability. Successful realization of the engineering designs would amount to a concrete demonstration of multiple realizability, taking evidence for MRT beyond what is readily found in nature. (shrink)

Synthetic biology is described as a new field of biotechnology that models itself on engineering sciences. However, this view of synthetic biology as an engineering field has received criticism, and both biologists and philosophers have argued for a more nuanced and heterogeneous understanding of the field. This paper elaborates the heterogeneity of synthetic biology by clarifying the role of design and the variability of design methodologies in synthetic biology. I focus on two prominent design methodologies: rational design and directed evolution. (...) Rational design resembles the design methodology of traditional engineering sciences. However, it is often replaced and complemented by the more biologically-inspired method of directed evolution, which models itself on natural evolution. These two approaches take philosophically different stances to the design of biological systems. Rational design aims to make biological systems more machine-like, whereas directed evolution utilizes variation and emergent features of living systems. I provide an analysis of the methodological basis of these design approaches, and highlight important methodological differences between them. By analyzing the respective benefits and limitations of these approaches, I argue against the engineering-dominated conception of synthetic biology and its “methodological monism”, where the rational design approach is taken as the default design methodology. Alternative design methodologies, like directed evolution, should be considered as complementary, not competitive, to rational design. (shrink)

Ecological communities are seldom, if ever, biological individuals. They lack causal boundaries as the populations that constitute communities are not congruent and rarely have persistent functional roles regulating the communities’ higher-level properties. Instead we should represent ecological communities indexically, by identifying ecological communities via the network of weak causal interactions between populations that unfurl from a starting set of populations. This precisification of ecological communities helps identify how community properties remain invariant, and why they have robust characteristics. This respects the (...) diversity and aggregational nature of these complex systems while still vindicating them as units worthy of investigation. (shrink)

Are we entering a major new phase of modern science, one in which our standard, human modes of reasoning and understanding, including heuristics, have decreasing value? The new methods challenge human intelligibility. The digital revolution inspires such claims, but they are not new. During several historical periods, scientific progress has challenged traditional concepts of reasoning and rationality, intelligence and intelligibility, explanation and knowledge. The increasing intelligence of machine learning and networking is a deliberately sought, somewhat alien intelligence. As such, it (...) challenges the traditional, heuristic foresight of expert researchers. Nonetheless, science remains human-centered in important ways—and yet many of our ordinary human epistemic activities are alien to ourselves. This fact has always been the source of “the discovery problem”. It generalizes to the problem of understanding expert scientific practice. Ironically, scientific progress plunges us ever deeper into complexities beyond our grasp. But how is progress possible without traditional realism and the intelligibility realism requires? Pragmatic flexibility offers an answer. (shrink)

This essay develops an inferential account of model explanation, based on Mauricio Suárez’s inferential conception of scientific representation and Alisa Bokulich’s counterfactual account of model explanation. It is suggested that the fact that a scientific model can explain is essentially linked to how a modeler uses an established model to make various inferences about the target system on the basis of results derived from the model. The inference practice is understood as a two-step activity, with the first step involving making (...) counterfactual statements about the model itself and the second step involving making hypothetical statements transferring over claims derived from the model onto the target. To illustrate how this two-step activity proceeds, an agent-based simulation model is discussed. (shrink)

Philosophical analyses of scientific methodology have long understood intuition to be incompatible with a rule based reasoning that is often considered necessary for a rational scientific method. This paper seeks to challenge this contention by highlighting the indispensable role that intuition plays in the application of methodologies for scientific discovery. In particular, it seeks to outline a positive role for intuition and personal judgment in scientific discovery by exploring a comparison between the use of heuristic reasoning in scientific practice and (...) engineering design. While these discussions share many features, it will also be shown that the successful use of heuristics in engineering design is often considered to depend on a crucial factor that is markedly absent from accounts of the use of heuristics in scientific discovery; experienced judgment. In the final sections of this paper, I will compare attitudes to the role of computer analysis in scientific and engineering practices, with the aim of showing how the limitations of scientific discovery machines reveal the need for including intuition in philosophical accounts of heuristic reasoning in scientific discovery. (shrink)