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)

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)

We lay groundwork for applying ethnographic methods in philosophy of science. We frame our analysis in terms of two tasks: to identify the benefits of an ethnographic approach in philosophy of science and to structure an ethnographic approach for philosophical investigation best adapted to provide information relevant to philosophical interests and epistemic values. To this end, we advocate for a purpose-guided form of cognitive ethnography that mediates between the explanatory and normative interests of philosophy of science, while maintaining openness and (...) independence when framing such an investigation to achieve robust unbiased results. (shrink)

In this paper we take a close look at current interdisciplinary modeling practices in the environmental sciences, and suggest that closer attention needs to be paid to the nature of scientific practices when investigating and planning interdisciplinarity. While interdisciplinarity is often portrayed as a medium of novel and transformative methodological work, current modeling strategies in the environmental sciences are conservative, avoiding methodological conflict, while confining interdisciplinary interactions to a relatively small set of pre-existing modeling frameworks and strategies (a process we (...) call crystallization). We argue that such practices can be rationalized as responses in part to cognitive constraints which restrict interdisciplinary work. We identify four salient integrative modeling strategies in environmental sciences, and argue that this crystallization, while contradicting somewhat the novel goals many have for interdisciplinarity, makes sense when considered in the light of common disciplinary practices and cognitive constraints. These results provide cause to rethink in more concrete methodological terms what interdisciplinarity amounts to, and what kinds of interdisciplinarity are obtainable in the environmental sciences and elsewhere. (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)

In this article, we provide a case study examining how integrative systems biologists build simulation models in the absence of a theoretical base. Lacking theoretical starting points, integrative systems biology researchers rely cognitively on the model-building process to disentangle and understand complex biochemical systems. They build simulations from the ground up in a nest-like fashion, by pulling together information and techniques from a variety of possible sources and experimenting with different structures in order to discover a stable, robust result. Finally, (...) we analyze the alternative role and meaning theory has in systems biology expressed as canonical template theories like Biochemical Systems Theory. (shrink)

The importation of computational methods into biology is generating novel methodological strategies for managing complexity which philosophers are only just starting to explore and elaborate. This paper aims to enrich our understanding of methodology in integrative systems biology, which is developing novel epistemic and cognitive strategies for managing complex problem-solving tasks. We illustrate this through developing a case study of a bimodal researcher from our ethnographic investigation of two systems biology research labs. The researcher constructed models of metabolic and cell-signaling (...) pathways by conducting her own wet-lab experimentation while building simulation models. We show how this coupling of experiment and simulation enabled her to build and validate her models and also triangulate and localize errors and uncertainties in them. This method can be contrasted with the unimodal modeling strategy in systems biology which relies more on mathematical or algorithmic methods to reduce complexity. We discuss the relative affordances and limitations of these strategies, which represent distinct opinions in the field about how to handle the investigation of complex biological systems. (shrink)

Really statistical explanation is a hitherto neglected form of noncausal scientific explanation. Explanations in population biology that appeal to drift are RS explanations. An RS explanation supplies a kind of understanding that a causal explanation of the same result cannot supply. Roughly speaking, an RS explanation shows the result to be mere statistical fallout.

Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to (...) handle the cognitive complexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations. (shrink)

Interdisciplinarity is widely considered necessary to solving many contemporary problems, and new funding structures and instruments have been created to encourage interdisciplinary research at universities. In this article, we study a small technical university specializing in green technology which implemented a strategy aimed at promoting and developing interdisciplinary collaboration. It did so by reallocating its internal research funds for at least five years to “research platforms” that required researchers from at least two of the three schools within the university to (...) participate. Using data from semi-structured interviews from researchers in three of these platforms, we identify specific tensions that the strategy has generated in this case: in the allocation of platform resources, in the division of labor and disciplinary relations, in choices over scientific output and academic careers. We further show how the particular platform format exacerbates the identified tensions in our case. We suggest that certain features of the current platform policy incentivize shallow interdisciplinary interactions, highlighting potential limits on the value of attempting to push for interdisciplinarity through internal funding. (shrink)

Integrative systems biology is among the most innovative fields of contemporary science, bringing together scientists from a range of diverse backgrounds and disciplines to tackle biological complexity through computational and mathematical modeling. The result is a plethora of problem-solving techniques, theoretical perspectives, lab-structures and organizations, and identity labels that have made it difficult for commentators to pin down precisely what systems biology is, philosophically or sociologically. In this paper, through the ethnographic investigation of two ISB laboratories, we explore the particular (...) structural features of ISB thinking and organization and its relations to other disciplines that necessitate cognitive innovation at all levels from lab PI’s to individual researchers. We find that systems biologists face numerous constraints that make the production of models far from straight-forward, while at the same time they inhabit largely unstructured task environments in comparison to other fields. We refer to these environments as adaptive problem spaces. These environments they handle by relying substantially on the flexibility and affordances of model-based reasoning to integrate these various constraints and find novel adaptive solutions. Ultimately what is driving this innovation is a determination to construct new cognitive niches in the form of functional model building frameworks that integrate systems biology within the biological sciences. The result is an industry of diverse and different innovative practices and solutions to the problem of modeling complex, large-scale biological systems. (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)

Prediction and control sufficient for reliable medical and other interventions are prominent aims of modeling in systems biology. The short-term attainment of these goals has played a strong role in projecting the importance and value of the field. In this paper I identify the standard models must meet to achieve these objectives as predictive robustness—predictive reliability over large domains. Drawing on the results of an ethnographic investigation and various studies in the systems biology literature, I explore four current obstacles to (...) achieving predictive robustness; data constraints, parameter uncertainty, collaborative constraints and system-scale requirements. I use a case study and the commentary of systems biologists themselves to show that current practices in the field, rather than pursuing these goals, frequently use models heuristically to investigate and build understanding of biological systems that do not meet standards of predictive robustness but are nonetheless effective uses of computation. A more heuristic conception of modeling allows us to interpret current practices as ways that manage these obstacles more effectively, particularly collaborative constraints, such that modelers can in the long-run at least work towards prediction and control. (shrink)

Interdisciplinarity is one of the most prominent ideas driving science and research policy today.1 It is applied widely as a conception of what particularly creative and socially relevant research processes should consist of, whether in the natural sciences, the social sciences, the humanities, or elsewhere. Its advocates, many of whom are located in current science and research administration themselves, are using ideas of interdisciplinarity to reshape university organization and research funding. For the last 40 years, researchers studying interdisciplinarity have built (...) up a substantial body of literature constructing various visions of what it should be and how to taxonomize the different forms it can... (shrink)

Interdisciplinarity has become a dominant research policy imperative1 – exercised by European Research Council and other funding agencies at different scales – and a substantial topic in science studies fields outside philosophy of science, including science education, research management (particularly team management) and scientometrics. Philosophers of science have only recently begun to dedicate more attention to this feature of contemporary science. The present collection of studies aspires to promote this line of philosophical inquiry in terms of case studies on various (...) aspects of interdisciplinarity in science, and to bring philosophical concepts and principles to bear in its analysis. While much current philosophical work has focused on the possibility of conceptual and methodological unification and integration amongst specific fields, we aim to widen the scope of philosophical treatment of this issue by mapping out the broader landscape of philosophical issues that emerge from interdisciplinary interactions, and by identifying the points where philosophical analysis can make important and relevant contributions. (shrink)

Universals are a class of mind independent entities, usually contrasted with individuals, postulated to ground and explain relations of qualitative identity and resemblance among individuals. Individuals are said to be similar in virtue of sharing universals. An apple and a ruby are both red, for example, and their common redness results from sharing a universal. If they are both red at the same time, the universal, red, must be in two places at once. This makes universals quite different from individuals, (...) and controversial. (shrink)

Many philosophers of science think scientific practice can benefit from philosophical concepts, and as such philosophy of science should play a direct role in science and engineering education. In this paper we consider a highly integrative course design strategy for integrating philosophy of science in specific disciplinary educational programmes through adaptation, operationalization and embedding of philosophy of science material to fit both the scientific and educational structure of a programme. The goal of the strategy is to help encourage students to (...) recognize the value of philosophical concepts to scientific decision making and to apply them in their own scientific practice. We use the example of a 7.5 ECTS civil engineering course which implements this design at a European technical university, to elaborate these concepts, and present some evidence on how students receive the course. We discuss some of challenges and limitations of implementing this kind of strategy for teaching philosophy of science. (shrink)

H. B. Smith, Professor of Philosophy at the influential 'Pennsylvania School' was (roughly) a contemporary of C. I. Lewis who was similarly interested in a proper account of 'implication'. His research also led him into the study of modal logic but in a different direction than Lewis was led. His account of modal logic does not lend itself as readily as Lewis' to the received 'possible worlds' semantics, so that the Smith approach was a casualty rather than a beneficiary of (...) the renewed interest in modality. In this essay we present some of the main points of the Smith approach, in a new guise. (shrink)

We argue that many recent philosophical discussions about the reference of everyday concepts of intentional states have implicitly been predicated on descriptive theories of reference. To rectify this, we attempt to demonstrate how a causal theory can be applied to intentional concepts. Specifically, we argue that some phenomena in early social de- velopment ðe.g., mimicry, gaze following, and emotional contagionÞ can serve as refer- ence fixers that enable children to track others’ intentional states and, thus, to refer to those states. (...) This allows intentional concepts to be anchored to their referents, even if folk psy- chological descriptions turn out to be false. (shrink)

Many of the current comparisons of taxic phylogenetic and biological homology in the context of morphology focus on what are seen as categorical distinctions between the two concepts. The first, it is claimed, identifies historical patterns of conservation and variation relating taxa; the second provides a causal framework for the explanation of this conservation and variation. This leads to the conclusion that the two need not be placed in conflict and are in fact compatible, having non-competing epistemic purposes or mapping (...) the same extensions in the form of monophyletic groupings (see Roth, The biological basis of homology 1–26, 1988; Sluys, J Zool Syst Evol Res 34:145–152, 1996; Abouheif, Trends Ecol Evol 12:405–408, 1997; Brigandt, J Exp Zool 299:9–17, 2003, Biol Philos 22:709–725, 2007; Assis and Brigandt, Evol Biol 36:248–255, 2009). This article argues that moves in this direction miss the essential disagreement between these concepts as they have been developed in the context of the debate concerning the best concept for evolutionary investigation. We should rather see these concepts employing a common fundamental methodological approach to homology, but disagreeing about how to apply the methodology effectively. Both concepts employ class reasoning, which pursues homologies as units of generalization—more precisely, as sources of reliable and relevant group-bound information in the form of shared underlying causes. The dispute can be better understood by two poles that structure such reasoning: the need for a reliable basis for projections about the causal history of shared structures, and the desire to identify homologous characters with more informative and specific causal information relevant to generalizing about evolutionary processes. Judgments in favor of one or the other in turn have affected the scope or extension of these competing homology concepts. (shrink)

Participatory modeling in sustainability science allows scientists to take stakeholders’ interests, knowledge and values into account when designing a model-based solution to a sustainability problem, by incorporating stakeholders in the model-building process. This improves the chance of generating socially robust knowledge and consensus on solutions. Part of what helps in this regard is that scientists, through involving stakeholders, limit their own values from influencing the outcome, thus achieving some level of value-neutrality. We argue that while it might achieve this to (...) some extent, it comes at a cost to the reliability of the outcomes, which is ethically problematic. (shrink)

BackgroundThe ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines are widely endorsed but compliance is limited. We sought to determine whether journal-requested completion of an ARRIVE checklist improves full compliance with the guidelines.MethodsIn a randomised controlled trial, manuscripts reporting in vivo animal research submitted to PLOS ONE (March–June 2015) were randomly allocated to either requested completion of an ARRIVE checklist or current standard practice. Authors, academic editors, and peer reviewers were blinded to group allocation. Trained reviewers performed outcome adjudication (...) in duplicate by assessing manuscripts against an operationalised version of the ARRIVE guidelines that consists 108 items. Our primary outcome was the between-group differences in the proportion of manuscripts meeting all ARRIVE guideline checklist subitems.ResultsWe randomised 1689 manuscripts (control: n = 844, intervention: n = 845), of which 1269 were sent for peer review and 762 (control: n = 340; intervention: n = 332) accepted for publication. No manuscript in either group achieved full compliance with the ARRIVE checklist. Details of animal husbandry (ARRIVE subitem 9b) was the only subitem to show improvements in reporting, with the proportion of compliant manuscripts rising from 52.1 to 74.1% (X2 = 34.0, df = 1, p = 2.1 × 10−7) in the control and intervention groups, respectively.ConclusionsThese results suggest that altering the editorial process to include requests for a completed ARRIVE checklist is not enough to improve compliance with the ARRIVE guidelines. Other approaches, such as more stringent editorial policies or a targeted approach on key quality items, may promote improvements in reporting. (shrink)

Harmonides, speaking to his teacher Timotheus, says, I suggest that should be emended to for the following reasons: 1. The phrase is, in any case, very difficult indeed after , but becomes virtually impossible in view of the order, as we have as the subject of the first four infinitives, as the subject of , and then a reversion to as the subject of.

Large-scale book-length treatises on natural kinds are rather few compared to the amount of discussion on the subject and not since Brian Ellis’ Scientific Essentialism perhaps has anyone attempted to build a philosophical “world view” around a theory of natural kinds. Most discussion about natural kinds of the last decade has restricted itself to specific issues, such as the species debate or chemical kinds, or, as in the case of LaPorte (2009), the semantic practices surrounding kind concepts and conceptual change. (...) In this respect, Magnus’ Scientific Enquiry and Natural Kinds: From Planets to Mallards has a worthy ambition, not least for displaying how rich and informative natural kind discussion can be despite its recent characterization as a philosophical dead end (see Hacking 2007). This holds even more so because Magnus attempts this within the context of a highly naturalistic account of natural kinds, rather than a metaphysically driven approach already predisposed to metaphysic .. (shrink)

Modelers are tackling ever more complex systems with the aid of computation. Model-based inferences can play a key role in their ability to handle complexity and produce reliable or informative models. We study here the role of model-based inference in the modern field of computational systems biology. We illustrate how these inferences operate and analyze the material and theoretical bases or conditions underlying their effectiveness. Our investigation reiterates the significance and centrality of model-based reasoning in day-to-day problem-solving practices, and the (...) role that debugging processes of partial or incomplete models can play in scientific inference and scientific discovery, particularly with respect to complex systems. We present several deeper implications such an analysis has for philosophy of science regarding the role of models in scientific practice. (shrink)

Philosophy of science is a rapidly evolving and increasingly inclusive academic field. It is one of the most dynamic branches of philosophy. However, for the most part, philosophy of science has been taught historically by recounting and tracing through discussions and debates from the early to late twentieth century. Great texts of positivism, instrumentalism, demarcation, falsification, paradigm shifts, realism, observation and so on are handed out to students and critically assessed. There is something rather puzzling about this way of teaching (...) philosophy of science, since contemporary philosophy of science has moved on significantly and is arguably distinct from the historical subject, just as current science has many features different from the science of Kuhn’s and Popper’s day. Such philosophical work, however, often only seems to make a late appearance in such courses. It often seems that we teach philosophy of science solely as an exercise in point and refutation, leaving stu .. (shrink)

As shown by Goodwin and corroborated by A. C. Moorhouse , 1), with the future whether indicative, infinitive, or participle is proved by manuscript authority to be a permissible, though comparatively rare, Attic usage. Moorhouse's case, moreover, is strengthened, rather than weakened, as he supposed, by the usage of Lucian, for, though the construction may be condemned in Solecist, §§ 2 and 8, there are considerably more examples of with the future in Lucian than Asinus.

In this chapter we explore basic mathematical and other constraints which limit the often novel uses of computation employed in modern computational system biology. These constraints generate substantial obstacles for one goal prominent in the field; namely, the goal of producing models valid for predictive uses in clinical and other contexts. However on closer examination many applications of computation and simulation in the field have more pragmatic or investigative goals in mind, suggesting an important role for rationalizing uses of computation (...) in systems biology and elsewhere as investigative tools. We discuss the concept of an “investigative tool”, and what insights it might offer our understanding of modern computational strategies and the bases for them. (shrink)