After an initial discussion of the character of interdisciplinary linkages between complex disciplines, I consider an area with confluences of many diverse disciplines—the study of cultural evolution. This must embrace not only the traditional biological sciences, but also the multiple often warring disciplines of the human sciences. This interdisciplinary articulation is in its early stages compared, e.g., to that of evolutionary biology or evolutionary developmental biology, and I try to lay out major axes along which its articulation should plausibly occur, (...) given the relevant causal processes acting at different levels. One cannot have an adequate account of cultural evolution without recognizing a central role for cognitive and social development and the social and cultural organizations and institutions and artifactual tools and infrastructure that support and structure these developmental processes. These induce a population structure that mediates the transmission, expression, and elaboration of culture, and in particular the different ways in which they scaffold learning and the development and articulation of complex skills. I consider how these elements should articulate the disciplines that tend to focus separately on them. Intentions and the market are not explicitly included in this account, and I consider ways in which these perspectives might enter. (shrink)

Criticism of big data has focused on showing that more is not necessarily better, in the sense that data may lose their value when taken out of context and aggregated together. The next step is to incorporate an awareness of pitfalls for aggregation into the design of data infrastructure and institutions. A common strategy minimizes aggregation errors by increasing the precision of our conventions for identifying and classifying data. As a counterpoint, we argue that there are pragmatic trade-offs between precision (...) and ambiguity that are key to designing effective solutions for generating big data about biodiversity. We focus on the importance of theory-dependence as a source of ambiguity in taxonomic nomenclature and hence a persistent challenge for implementing a single, long-term solution to storing and accessing meaningful sets of biological specimens. We argue that ambiguity does have a positive role to play in scientific progress as a tool for efficiently symbolizing multiple aspects of taxa and mediating between conflicting hypotheses about their nature. Pursuing a deeper understanding of the trade-offs and synthesis of precision and ambiguity as virtues of scientific language and communication systems then offers a productive next step for realizing sound, big biodiversity data services. (shrink)

Cancer is not one, but many diseases, and each is a product of a variety of causes acting (and interacting) at distinct temporal and spatial scales, or “levels” in the biological hierarchy. In part because of this diversity of cancer types and causes, there has been a diversity of models, hypotheses, and explanations of carcinogenesis. However, there is one model of carcinogenesis that seems to have survived the diversification of cancer types: the multi-stage model of carcinogenesis. This paper examines the (...) history of the multistage theory, and uses the theory as a case study in the limits and goals of unification as a theoretical virtue, comparing and contrasting it with “integrative” research. (shrink)

One way to articulate the promise of interdisciplinary research is in terms of the relationship between knowledge and ignorance. Disciplinary research yields deep knowledge of a circumscribed range of issues, but remains ignorant of those issues that stretch outside its purview. Because complex problems such as climate change do not respect disciplinary boundaries, disciplinary research responses to such problems are limited and partial. Interdisciplinary research responses, by contrast, integrate disciplinary perspectives by combining knowledge about different issues and as a result (...) reduce ignorance about more aspects of the problem. In this paper, we develop this idea and argue that while interdisciplinary research can help remediate damaging ignorance about complex problems, it also creates conditions in which other damaging forms of ignorance can arise. We illustrate this point in detail with three case studies before discussing three implications of our analysis for identifying and managing deleterio... (shrink)

Social studies of interdisciplinary science investigate how scientific collaborations approach complex challenges that require multiple disciplinary perspectives. In order for collaborators to meet these complex challenges, interdisciplinary collaborations must develop and maintain integrative capacity, understood as the ability to anticipate and weigh tradeoffs in the employment of different disciplinary approaches. Here we provide an account of how one group of interdisciplinary fog scientists intentionally catalyzed integrative capacity. Through conversation, collaborators negotiated their commitments regarding the ontology of fog systems and the (...) methodologies appropriate to studying fog systems, thereby enhancing capabilities which we take to constitute integrative capacity. On the ontological front, collaborators negotiated their commitments by setting boundaries to and within the system, layering different subsystems, focusing on key intersections of these subsystems, and agreeing on goals that would direct further investigation. On the methodological front, collaborators sequenced various methods, anchored methods at different scales, validated one method with another, standardized the outputs of related methods, and coordinated methods to fit a common model. By observing the process and form of collaborator conversations, this case study demonstrates that social studies of science can bring into critical focus how interdisciplinary collaborators work toward an integrated conceptualization of study systems. (shrink)

Meeting grand challenges requires responses that constructively combine multiple forms of expertise, both academic and non-academic; that is, it requires cross-disciplinary integration. But just what is cross-disciplinary integration? In this paper, we supply a preliminary answer by reviewing prominent accounts of cross-disciplinary integration from two literatures that are rarely brought together: cross-disciplinarity and philosophy of biology. Reflecting on similarities and differences in these accounts, we develop a framework that integrates their insights—integration as a generic combination process the details of which (...) are determined by the specific contexts in which particular integrations occur. One such context is cross-disciplinary research, which yields cross-disciplinary integration. We close by reflecting on the potential applicability of this framework to research efforts aimed at meeting grand challenges. (shrink)

Pluralism is widely appealed to in many areas of philosophy of science, though what is meant by ‘pluralism’ may profoundly vary. Because explanations of behaviour have been a favoured target for pluralistic theses, the sciences of behaviour offer a rich context in which to further investigate pluralism. This is what the topical collection The Biology of Behaviour: Explanatory pluralism across the life sciences is about. In the present introduction, we briefly review major strands of pluralist theses and their motivations. We (...) highlight three distinct types of pluralisms—type pluralism, fragmentation pluralism and insular pluralism—and introduce the articles of the topical collection. (shrink)

Research on interdisciplinary science has for the most part concentrated on the institutional obstacles that discourage or hamper interdisciplinary work, with the expectation that interdisciplinary interaction can be improved through institutional reform strategies such as through reform of peer review systems. However institutional obstacles are not the only ones that confront interdisciplinary work. The design of policy strategies would benefit from more detailed investigation into the particular cognitive constraints, including the methodological and conceptual barriers, which also confront attempts to work (...) across disciplinary boundaries. Lessons from cognitive science and anthropological studies of labs in sociology of science suggest that scientific practices may be very domain specific, where domain specificity is an essential aspect of science that enables researchers to solve complex problems in a cognitively manageable way. The limit or extent of domain specificity in scientific practice, and how it constrains interdisciplinary research, is not yet fully understood, which attests to an important role for philosophers of science in the study of interdisciplinary science. This paper draws upon two cases of interdisciplinary collaboration; those between ecologists and economists, and those between molecular biologists and systems biologists, to illustrate some of the cognitive barriers which have contributed to failures and difficulties of interactions between these fields. Each exemplify some aspect of domain specificity in scientific practice and show how such specificity may constrain interdisciplinary work. (shrink)

Integrative systems biology is an emerging field that attempts to integrate computation, applied mathematics, engineering concepts and methods, and biological experimentation in order to model large-scale complex biochemical networks. The field is thus an important contemporary instance of an interdisciplinary approach to solving complex problems. Interdisciplinary science is a recent topic in the philosophy of science. Determining what is philosophically important and distinct about interdisciplinary practices requires detailed accounts of problem-solving practices that attempt to understand how specific practices address the (...) challenges and constraints of interdisciplinary research in different contexts. In this paper we draw from our 5-year empirical ethnographic study of two systems biology labs and their collaborations with experimental biologists to analyze a significant problem-solving approach in ISB, which we call adaptive problem solving. ISB lacks much of the methodological and theoretical resources usually found in disciplines in the natural sciences, such as methodological frameworks that prescribe reliable model-building processes. Researchers in our labs compensate for the lack of these and for the complexity of their problems by using a range of heuristics and experimenting with multiple methods and concepts from the background fields available to them. Using these resources researchers search out good techniques and practices for transforming intractable problems into potentially solvable ones. The relative freedom lab directors grant their researchers to explore methodological options and find good practices that suit their problems is not only a response to the complex interdisciplinary nature of the specific problem, but also provides the field itself with an opportunity to discover more general methodological approaches and develop theories of biological systems. Such developments in turn can help to establish the field as an identifiably distinct and successful approach to understanding biological systems. (shrink)

Many philosophers of biology have embraced a version of pluralism in response to the failure of theory reduction but overlook how concepts, methods, and explanatory resources are in fact coordinated, such as in interdisciplinary research where the aim is to integrate different strands into an articulated whole. This is observable for the origin of evolutionary novelty—a complex problem that requires a synthesis of intellectual resources from different fields to arrive at robust answers to multiple allied questions. It is an apt (...) locus for exploring new dimensions of explanatory integration because it necessitates coordination among historical and experimental disciplines . These coordination issues are widespread for the origin of novel morphologies observed in the Cambrian Explosion. Despite an explicit commitment to an integrated, interdisciplinary explanation, some potential disciplinary contributors are excluded. Notable among these exclusions is the physics of ontogeny. We argue that two different dimensions of integration—data and standards—have been insufficiently distinguished. This distinction accounts for why physics-based explanatory contributions to the origin of novelty have been resisted: they do not integrate certain types of data and differ in how they conceptualize the standard of uniformitarianism in historical, causal explanations. Our analysis of these different dimensions of integration contributes to the development of more adequate and integrated explanatory frameworks. (shrink)

In this paper, we use the case of the COVID-19 pandemic in Europe to address the question of what kind of knowledge we should incorporate into public health policy. We show that policy-making during the COVID-19 pandemic has been biomedicine-centric in that its evidential basis marginalised input from non-biomedical disciplines. We then argue that in particular the social sciences could contribute essential expertise and evidence to public health policy in times of biomedical emergencies and that we should thus strive for (...) a tighter integration of the social sciences in future evidence-based policy-making. This demand faces challenges on different levels, which we identify and discuss as potential inhibitors for a more pluralistic evidential basis. (shrink)

This paper discusses what it means and what it takes to integrate data in order to acquire new knowledge about biological entities and processes. Maureen O’Malley and Orkun Soyer have pointed to the scientific work involved in data integration as important and distinct from the work required by other forms of integration, such as methodological and explanatory integration, which have been more successful in captivating the attention of philosophers of science. Here I explore what data integration involves in more detail (...) and with a focus on the role of data-sharing tools, like online databases, in facilitating this process; and I point to the philosophical implications of focusing on data as a unit of analysis. I then analyse three cases of data integration in the field of plant science, each of which highlights a different mode of integration: inter-level integration, which involves data documenting different features of the same species, aims to acquire an interdisciplinary understanding of organisms as complex wholes and is exemplified by research on Arabidopsis thaliana; cross-species integration, which involves data acquired on different species, aims to understand plant biology in all its different manifestations and is exemplified by research on Miscanthus giganteus; and translational integration, which involves data acquired from sources within as well as outside academia, aims at the provision of interventions to improve human health and is exemplified by research on Phytophtora ramorum. Recognising the differences between these efforts sheds light on the dynamics and diverse outcomes of data dissemination and integrative research; and the relations between the social and institutional roles of science, the development of data-sharing infrastructures and the production of scientific knowledge. (shrink)

1. A multidisciplinary group of scholars within the International Commission on Stratigraphy – known as the Anthropocene Working Group – recently recommended the Anthropocene as a new geological ep...

Why is it rational for scientists to pursue multiple models of a phenomenon at the same time? The literatures on mechanistic inquiry and scientific pursuit each develop answers to a version of this question which is rarely discussed by the other. The mechanistic literature suggests that scientists pursue different complementary models because each model provides detailed insights into different aspects of the phenomenon under investigation. The pursuit literature suggests that scientists pursue competing models because alternative models promise to solve outstanding (...) empirical and conceptual problems. Looking into research on visual processing as a case study, we suggest an integrated account of why it is rational for scientists to pursue both complementary and competing models of the same mechanism in scientific practice. (shrink)

We present two case studies from contemporary biology in which we observe conflicts between established and emerging approaches. The first case study discusses the relation between molecular biology and systems biology regarding the explanation of cellular processes, while the second deals with phylogenetic systematics and the challenge posed by recent network approaches to established ideas of evolutionary processes. We show that the emergence of new fields is in both cases driven by the development of high-throughput data generation technologies and the (...) transfer of modeling techniques from other fields. New and emerging views are characterized by different philosophies of nature, i.e. by different ontological and methodological assumptions and epistemic values and virtues. This results in a kind of conflict we call “epistemic competition” that manifests in two ways: On the one hand, opponents engage in mutual critique and defense of their fundamental assumptions. On the other hand, they compete for the acceptance and integration of the knowledge they provide by a broader scientific community. Despite an initial rhetoric of replacement, the views as well as the respective audiences come to be seen as more clearly distinct during the course of the debate. Hence, we observe—contrary to many other accounts of scientific change—that conflict results in the formation of new niches of research, leading to co-existence and perceived complementarity of approaches. Our model thus contributes to the understanding of the pluralization of the scientific landscape. (shrink)

Some scholars see interdisciplinarity as a special case of a broader unificationist program. They accept the unification of the sciences as a regulative ideal, and derive from this the normative justification of interdisciplinary research practices. The crucial link for this position is the notion of integration: integration increases the cohesion of concepts and practices, and more specifically of explanations, ontologies, methods and data. Interdisciplinary success then consists in the integration of fields or disciplines, and this constitutes success in the sense (...) that unification is epistemically desirable. In contrast to this account, I defend the thesis that successful interdisciplinary interaction does not necessarily imply the integration of these disciplines. I show this at the hand of two cases. In both the case of evolutionary game theory and the case of hyperbolic discounting, genuine interdisciplinary exchange took place. From both exchanges, the respective economic fields emerged substantially altered – it wasn’t just a juxtaposition of disciplines in which disciplinary identities remained unchanged. Yet in neither case did the disciplines integrate. Rather, they developed their own concepts and methods, their own explanations, own ontologies, and their own views of what proper data standards were. Furthermore, the fields that emerged from these exchanges were very successful, if measured at the hand of properties like explanatory success, increase of control, bibliometrics and grant yields. Thus, I argue, there are cases of interdisciplinary success without integration. (shrink)

What gets integrated in integrative scientific practices has been a topic of much discussion. Traditional views focus on theories and explanations, with ideas of reduction and unification dominating the conversation. More recent ideas focus on disciplines, fields, or specialties; models, mechanisms, or methods; phenomena, problems. How integration works looks different on each of these views since the objects of integration are ontologically and epistemically various: statements, boundary conditions, practices, protocols, methods, variables, parameters, domains, laboratories, and questions all have their own (...) structures, functions and logics. I focus on one particular kind of scientific practice, integration of “approaches” in the context of a research system operating on a special kind of “platform.” Rather than trace a network of interactions among people, practices, and theoretical entities to be integrated, in this essay I focus on the work of a single investigator, David Wake. I describe Wake’s practice of integrative evolutionary biology and how his integration of approaches among biological specialties worked in tandem with his development of the salamanders as a model taxon, which he used as a platform to solve, re-work and update problems that would not have been solved so well by non-integrative approaches. The larger goal of the project to which this paper contributes is a counter-narrative to the story of 20th century life sciences as the rise and march of the model organisms and decline of natural history. (shrink)

Stem cells did not become a proper research object until the 1960 s. Yet the term and the basic mind-set—namely the conception of single undifferentiated cells, be they embryonic or adult, as the basic units responsible for a directed process of development, differentiation and increasing specialisation—were already in place at the end of the nineteenth century and then transmitted on a non-linear path in the form of tropes and diagrams. Ernst Haeckel and August Weismann played a special role in this (...) story. The first coined the term Stammzelle (stem cell), the second was the author of the first cellular stem-tree diagram. Even today, I shall argue, the understanding of stem cells, especially the popular perception, is to a large extent a Haeckelian–Weismannian one. After having demonstrated this, by analysing the terminology, in this essay I will focus on the use of cytogenetic tree diagrams between 1892 and 1925 and on the tacit understanding of stem cells that they transmit. (shrink)

The paper discusses how systems biology is working toward complex accounts that integrate explanation in terms of mechanisms and explanation by mathematical models—which some philosophers have viewed as rival models of explanation. Systems biology is an integrative approach, and it strongly relies on mathematical modeling. Philosophical accounts of mechanisms capture integrative in the sense of multilevel and multifield explanations, yet accounts of mechanistic explanation have failed to address how a mathematical model could contribute to such explanations. I discuss how mathematical (...) equations can be explanatorily relevant. Several cases from systems biology are discussed to illustrate the interplay between mechanistic research and mathematical modeling, and I point to questions about qualitative phenomena, where quantitative models are still indispensable to the explanation. Systems biology shows that a broader philosophical conception of mechanisms is needed, which takes into account functional-dynamical aspects, interaction in complex networks with feedback loops, system-wide functional properties such as distributed functionality and robustness, and a mechanism’s ability to respond to perturbations. I offer general conclusions for philosophical accounts of explanation. (shrink)

This introduction to the special section on integration in biology provides an overview of the different contributions. In addition to motivating the philosophical significance of analyzing integration and interdisciplinary research, I lay out common themes and novel insights found among the special section contributions, and indicate how they exhibit current trends in the philosophical study of integration. One upshot of the contributed papers is that there are different aspects to and kinds of integration, so that rather than attempting to offer (...) a universal construal of what integrations is, philosophers have to analyze in concrete cases in what respects particular aspects of scientific theorizing and/or practice are ‘integrative’ and how this instance of integration works and was achieved. (shrink)

This article is a study of the role and use of evidence in the evaluation of claims in the historical sciences. In order to do this, I develop a “snapshot” approach to Toulmin schemas. This framework is applied to the case of Archezoa, an initially supported then eventually rejected hypothesis in evolutionary biology. From this case study, I criticize Cleland’s “smoking gun” account of the methodology of the historical sciences. I argue that Toulmin schemas are conceptually precise tools that allow (...) for the building of enriched reconstructions of evidential reasoning. From the application of this framework, I discuss three ways in which the construction and use of facts in the historical sciences are theory-laden. Despite its inherent limits, TS are heuristically useful tools to identify epistemic moves that could be further investigated. It also sheds light on the positive roles of speculation in the historical sciences. Finally, I argue that it provides a context-specific and individuated understanding of hypothesis evaluation in the historical sciences. Overall, I think the application of Toulmin schemas to cases of evidential reasoning in the historical sciences is a promising descriptive and heuristic tool for philosophers of science. (shrink)