When behaviors assemble into combinations, then synergies have a central role in the discovery of productive patterns of behavior. In our view—what we call the Synergy Emergence Principle (SEP)—synergies are dynamic attractors, drawing interactions toward greater returns as they happen, in the moment. This Principle offers an alternative to the two conventionally acknowledged routes to discovery: directed problem solving, involving forethought and planning; and the complete randomness of trial and error. Natural selection has a role in the process, in humans (...) favoring the maintenance and improvement of certain key underlying capabilities, such as prosocial helping and episodic foresight, but selection is not required for discovery by synergy (which occurs too rapidly for selection anyway). Here we discuss the consequences of the SEP for the evolution in humans of key synergies such as tool usage and interactions that reward cooperation, show how discovery by synergy and the selection of synergy-supporting abilities formed a positive feedback loop, and show how synergies can combine, forming clusters and packages that are the core of institutions and cultures. Finally, clusters and packages represent an intermediate level of organization above the individual and below whole society, with consequences for our understanding of the major transitions in evolution. (shrink)

Virtue and Law in Plato and Beyond, by AnnasJulia. Oxford: Oxford University Press, 2017. pp. 234.

A Mark of the Mental, by NeanderKaren. Cambridge, MA: MIT Press, 2017. Pp. xv + 327.

This paper introduces and contextualizes my book Naturalizing Critical Realist Social Ontology (London: Routledge, 2013).

ABSTRACTThis article responds to McWherter’s detailed critique of my assessment of Roy Bhaskar’s method of transcendental argumentation in chapter four of my Naturalizing Critical Realist Social Ontology. I begin by describing some naturalist ontological and epistemological views defended in my book, thereby showing that my naturalist challenge to the original version of critical realism is not only methodological but also substantial. I also indicate that this point is effectively downplayed in McWherter’s framing of the debate in terms of competing metaphilosophies. (...) I then consider how the doctrine of transcendental idealism is presupposed in Kant’s transcendental deduction and question the consistency of McWherter’s various descriptions of Bhaskar’s transcendental arguments. Finally, I provide detailed responses to McWherter’s objectives to my views. My conclusion is that naturalized critical realism is a more coherent and scientifically viable position than the neo-Kantian version of critical realism defended by McWherter. Nevertheless, I think that there is enough overlap between original and naturalized critical realism to regard the latter as a revised and elaborated version of the former. (shrink)

This paper analyzes what it means for philosophy of science to be normative. It argues that normativity is a multifaceted phenomenon rather than a general feature that a philosophical theory either has or lacks. It analyzes the normativity of philosophy of science by articulating three ways in which a philosophical theory can be normative. Methodological normativity arises from normative assumptions that philosophers make when they select, interpret, evaluate, and mutually adjust relevant empirical information, on which they base their philosophical theories. (...) Object normativity emerges from the fact that the object of philosophical theorizing can itself be normative, such as when philosophers discuss epistemic norms in science. Metanormativity arises from the kind of claims that a philosophical theory contains, such as normative claims about science as it should be. Distinguishing these three kinds of normativity gives rise to a nuanced and illuminating view of how philosophy of science can be normative. (shrink)

The article makes four interrelated claims: (1) The mechanism approach to social explanation does not presuppose a commitment to the individual-level microfoundationalism. (2) The microfoundationalist requirement that explanatory social mechanisms should always consists of interacting individuals has given rise to problematic methodological biases in social research. (3) It is possible to specify a number of plausible candidates for social macro-mechanisms where interacting collective agents (e.g. formal organizations) form the core actors. (4) The distributed cognition perspective combined with organization studies could (...) provide us with explanatory understanding of the emergent cognitive capacities of collective agents. (shrink)

This paper addresses the relationship between psychological capacities, as they are understood within cognitive psychology, and neurobiological activities. First, Lycan’s (1987) account of this relationship is examined and certain problems with his account are explained. According to Lycan, psychological capacities occupy a higher level than neurobiological activities in a hierarchy of levels of nature, and psychological entities can be decomposed into neurobiological entities. After discussing some problems with Lycan’s account, a similar, more recent account built around levels of mechanisms is (...) examined (Craver 2007). In the second half of this paper, an alternative is laid out. This new account uses levels of organization and levels of explanation to create a two-dimensional model. Psychological capacities occupy a high level of explanation relative to the cellular and molecular levels of organization. As a result, according to this model, psychological capacities are a particular way of describing the activities that occur at the cellular and molecular levels of organization. (shrink)

In a recent opinion piece, Denis Duboule has claimed that the increasing shift towards systems biology is driving evolutionary and developmental biology apart, and that a true reunification of these two disciplines within the framework of evolutionary developmental biology may easily take another 100 years. He identifies methodological, epistemological, and social differences as causes for this supposed separation. Our article provides a contrasting view. We argue that Duboule’s prediction is based on a one-sided understanding of systems biology as a science (...) that is only interested in functional, not evolutionary, aspects of biological processes. Instead, we propose a research program for an evolutionary systems biology, which is based on local exploration of the configuration space in evolving developmental systems. We call this approach—which is based on reverse engineering, simulation, and mathematical analysis—the natural history of configuration space. We discuss a number of illustrative examples that demonstrate the past success of local exploration, as opposed to global mapping, in different biological contexts. We argue that this pragmatic mode of inquiry can be extended and applied to the mathematical analysis of the developmental repertoire and evolutionary potential of evolving developmental mechanisms and that evolutionary systems biology so conceived provides a pragmatic epistemological framework for the EvoDevo synthesis. (shrink)

Weisberg (2006) and Godfrey-Smith (2006, 2009) distinguish between two forms of theorising: data-driven ‘abstract direct representation’ and modeling. The key difference is that when using a data-driven approach, theories are intended to represent specific phenomena, so directly represent them, while models may not be intended to represent anything, so represent targets indirectly, if at all. The aim here is to compare and analyse these practices, in order to outline an account of model-based theorising that involves direct representational relationships. This is (...) based on the way that computational templates Humphreys (2002, 2004) are now used in cognitive neuroscience, and draws on the dynamic and tentative process of any kind of theory construction, and the idea of partial, purpose-relative representation. (shrink)

The Fukushima nuclear accident from 2011 provided an occasion for the public display of radiation maps generated using decision-support systems for nuclear emergency management. Such systems rely on computer models for simulating the atmospheric dispersion of radioactive materials and estimating potential doses in the event of a radioactive release from a nuclear reactor. In Germany, as in Japan, such systems are part of the national emergency response apparatus and, in case of accidents, they can be used by emergency task forces (...) for planning radioprotection countermeasures. In this context, the paper addresses the epistemology of dose projections by critically analyzing some of the sources of epistemic opacity and non-knowledge affecting them, and the different methods and practices used by German radioprotection experts to improve their trustworthiness and reliability. It will be argued that dose projections are part of an entire radioprotection regime or assemblage built around the belief that the effects of nuclear accidents can be effectively mitigated thanks to the simulation technologies underlying different protocols and practices of nuclear preparedness. And, as the Fukushima experience showed, some of these expectations will not be met in real emergencies due to the inherent uncertainties entailed by the use of dose projections when planning protective countermeasures. (shrink)

The cis-regulatory hypothesis is one of the most important claims of evolutionary developmental biology. In this paper I examine the theoretical argument for cis-regulatory evolution and its role within evolutionary theorizing. I show that, although the argument has some weaknesses, it acts as a useful example for the importance of current scientific debates for science education.

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)

Research on the human microbiome has gen- erated a staggering amount of sequence data, revealing variation in microbial diversity at the community, species (or phylotype), and genomic levels. In order to make this complexity more manageable and easier to interpret, new units—the metagenome, core microbiome, and entero- type—have been introduced in the scientific literature. Here, I argue that analytical tools and exploratory statisti- cal methods, coupled with a translational imperative, are the primary drivers of this new ontology. By reducing the (...) dimensionality of variation in the human microbiome, these new units render it more tractable and easier to interpret, and hence serve an important heuristic role. Nonetheless, there are several reasons to be cautious about these new categories prematurely ‘‘hardening’’ into natural units: a lack of constraints on what can be sequenced metagenomically, freedom of choice in taxonomic level in defining a ‘‘core microbiome,’’ typological framing of some of the concepts, and possible reification of statistical constructs. Finally, lessons from the Human Genome Project have led to a translational imperative: a drive to derive results from the exploration of microbiome variation that can help to articulate the emerging paradigm of per- sonalized genomic medicine (PGM). There is a tension between the typologizing inherent in much of this research and the personal in PGM. (shrink)

Research on the human microbiome has generated a staggering amount of sequence data, revealing variation in microbial diversity at the community, species (or phylotype), and genomic levels. In order to make this complexity more manageable and easier to interpret, new units—the metagenome, core microbiome, and enterotype—have been introduced in the scientific literature. Here, I argue that analytical tools and exploratory statistical methods, coupled with a translational imperative, are the primary drivers of this new ontology. By reducing the dimensionality of variation (...) in the human microbiome, these new units render it more tractable and easier to interpret, and hence serve an important heuristic role. Nonetheless, there are several reasons to be cautious about these new categories prematurely ‘‘hardening’’ into natural units: a lack of constraints on what can be sequenced metagenomically, freedom of choice in taxonomic level in defining a ‘‘core microbiome,’’ typological framing of some of the concepts, and possible reification of statistical constructs. Finally, lessons from the Human Genome Project have led to a translational imperative: a drive to derive results from the exploration of microbiome variation that can help to articulate the emerging paradigm of personalized genomic medicine (PGM). There is a tension between the typologizing inherent in much of this research and the personal in PGM. (shrink)

Papers in experimental philosophy rarely offer an account of what it would take to reveal a philosophically significant effect. In part, this is because experimental philosophers tend to pay insufficient attention to the hierarchy of models that would be required to justify interpretations of their data; as a result, some of their most exciting claims fail as explanations. But this does not impugn experimental philosophy. My aim is to show that experimental philosophy could be made more successful by developing, articulating, (...) and advancing plausible models of the data that are collected and the analyses that are employed. (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)

There is a long-standing debate in the philosophy of mind and philosophy of science regarding how best to interpret the relationship between neuroscience and psychology. It has traditionally been argued that either the two domains will evolve and change over time until they converge on a single unified account of human behaviour, or else that they will continue to work in isolation given that they identify properties and states that exist autonomously from one another (due to the multiple-realizability of psychological (...) states). In this paper, I argue that progress in psychology and neuroscience is contingent on the fact that both of these positions are false. Contra the convergence position, I argue that the theories of psychology and the theories of neuroscience are scientifically valuable as representational tools precisely because they cannot be integrated into a single account. However, contra the autonomy position, I propose that the theories of psychology and neuroscience are deeply dependent on one another for further refinement and improvement. In this respect, there is an irreconcilable codependence between psychology and neuroscience that is necessary for both domains to improve and progress. The two domains are forever linked while simultaneously being unable to integrate. (shrink)

Despite the increasing recognition that heuristics may be involved in myriad scientific activities, much about how to use them prudently remains obscure. As typically defined, heuristics are efficient rules or procedures for converting complex problems into simpler ones. But this increased efficiency and problem-solving power comes at the cost of a systematic bias. As Wimsatt showed, biased modelling heuristics can conceal errors, leading to poor decisions or inaccurate models. This liability to produce errors presents a fundamental challenge to the philosophical (...) value of heuristic analyses. Heuristics may be powerful and efficient procedures, but their practical value for science and epistemology is significantly mitigated if we do not have a principled methodology for knowing how to use them wisely. In this essay, I extend Wimsatt’s analyses to argue that this challenge for a heuristic methodology can be met by appealing to second-order, or meta-, heuristics—that is, practical guidelines that prescribe the appropriate conditions for a first-order heuristic’s use. 1 Introduction2 Background3 Heuristics and Meta-heuristics4 A Hierarchical Model and Three Applications4.1 Decision making in emergency medicine4.2 Mathematical explanation in physics4.3 Resilience in ecological management5 Conclusion. (shrink)

Marc Ereshefsky’s project of eliminative pluralism holds that, as there is no unifying feature among all species concepts, we ought to doubt the existence of the species category. Here, I argue that one promising strategy for saving the species category is to reframe it as a natural kind after the practice turn. I suggest situating the species category within a recent account of natural kinds proposed by Marc Ereshefsky and Thomas Reydon called “scientific kinds”. Scientific kinds highlight ontological boundaries. More (...) importantly, they recognize boundaries drawn from the lab and the field, not only from the armchair. The point of this exercise is to situate the species category within an account of natural kinds that is sensitive to scientific practice. In order to argue for a realist interpretation of the species category, and not merely a pragmatic one, I rely on an approach to scientific metaphysics from Ken Waters that shifts the attention from “theory focused” to “practice-centered” analysis. (shrink)

I begin to develop a framework for emergence in the physical sciences. Namely, I propose to explicate ontological emergence in terms of the notion of ‘novel reference’, and of an account of interpretation as a map from theory to world. I then construe ontological emergence as the “failure of the interpretation to mesh” with an appropriate linkage map between theories. Ontological emergence can obtain between theories that have the same extension but different intensions, and between theories that have both different (...) extensions and intensions. I illustrate the framework in three examples: the emergence of spontaneous magnetisation in a ferromagnet, the emergence of masslessness, and the emergence of space, in specific models of physics. The account explains why ontological emergence is independent of reduction: namely, because emergence is primarily concerned with adequate interpretation, while the sense of reduction that is relevant here is concerned with inter-theoretic relations between uninterpreted theories. (shrink)

This paper explicates Husserl’s usage of what he calls “radical Besinnung” in Formale und transzendentale Logik. Husserl introduces radical Besinnung as his method in the introduction to FTL. Radical Besinnung aims at criticizing the practice of formal sciences by means of transcendental phenomenological clarification of its aims and presuppositions. By showing how Husserl applies this method to the history of formal sciences down to mathematicians’ work in his time, the paper explains in detail the relationship between historical critical Besinnung and (...) transcendental phenomenology. Ultimately the paper suggests that radical Besinnung should be viewed as a general methodological framework within which transcendental phenomenological descriptions are used to criticize historically given goal-directed practices. (shrink)

This paper presents methods and challenges attendant on the use of protocol analysis to develop a model of heuristic processing applied to research ethics. Participants are exposed to ethically complex scenarios and asked to verbalize their thoughts as they formulate a requested decision. The model identifies functional parts of the decision-making task: interpretation, retrieval, judgment and editing and seeks to reliably code participant verbalizations to those tasks as well as to a set of cognitive tools generally useful in such work. (...) Important difficulties in the reliability and external validity of measurement are evaluated and a small set of illustrative data is used in support of that discussion. Results indicate that both intuitive emotional but also more deliberative cognition is present which is consistent with work in related literatures in expertise and in neuropsychology. Finally, the theoretical and practical potential of the approach is elaborated, particularly through links to a framing in Aristotelian ethics. (shrink)

Charles Mills has argued against ideal theory in political philosophy on the basis that it contains idealizations. He calls for political philosophers to do more nonideal theory, namely political theory that pays more attention to the most visible oppressions in society, such as those based on race, gender, and class. Mills's argument relies on a distinction between idealization and abstraction. Idealizations involve adding false assumptions to one's model, which is unacceptable, whereas abstractions merely leave out details without undermining descriptive power. (...) By studying formal models of injustice, I argue that the idealization/abstraction distinction is unhelpful. Either the distinction exists only relative to one's modeling purposes, or all models in political theory contain idealizations. Either way, the distinction does not help Mills's cause. Furthermore, there are arguments from philosophy of science for the epistemic benefits of idealizations. However, Mills's call for greater emphasis on the most visible mechanisms of oppression can be supported without relying on an idealization/abstraction distinction. I provide three alternative reasons for why we should prefer political theories that place more emphasis on race-, class-, and gender-based oppression. (shrink)

The 2011 Nobel Prize in Physics was awarded to researchers from the Supernova Cosmology Project and the High-z Supernova Search Team for the discovery of the accelerating expansion of the universe. In this paper, I provide a historical analysis of the supernova cosmology evidence put forward by these teams for the accelerating universe, in terms of an iterative model of scientific progress developed by Hasok Chang in the context of his study of the development of measurement standards. I argue, using (...) the key concept of epistemic iteration, that the iterative model adequately accounts for evidence production in experimental science as well. In order to apply Chang’s model to the experimental evidence for the accelerating universe, I introduce the concept of endorsement as a particular mode of progress, and argue that supernova scientists produced an endorsed measurement system to claim evidence for their discovery. Furthermore, I show that the credibility of the evidence was not based on a particular measurement, rather, what proved to be decisive was the “robust consistency” of many individual results. (shrink)

Do I cause global warming, climate change and their related harms when I go for a leisure drive with my gas-guzzling car? The current verdict seems to be that I do not; the emissions produced by my drive are much too insignificant to make a difference for the occurrence of global warming and its related harms. I argue that our verdict on this issue depends on what we mean by ‘causation’. If we for instance assume a simple counterfactual analysis of (...) causation according to which ‘C causes E’ means ‘if C had not occurred, E would not have occurred’, we must conclude that a single drive does not cause global warming. However, this analysis of causation is well-known for giving counterintuitive results in some important cases. If we instead adopt Lewis’s analysis of causation, it turns out that it is indeterminate whether I cause global warming when I go for a single drive. Still, in contexts where we seek to control or understand global warming, there is a pressure to adopt a more fragile view of this event. When we adopt such a view, it turns out that a single drive does cause global warming. This means that we cannot like Sinnott-Armstrong and Kingston and Sinnott-Armstrong reject the idea that I should refrain from going for a leisure drive simply because such a drive does not cause global warming. (shrink)

Several advocates of the lively field of “metaphysics of science” have recently argued that a naturalistic metaphysics should be based solely on current science, and that it should replace more traditional, intuition-based, forms of metaphysics. The aim of the present paper is to assess that claim by examining the relations between metaphysics of science and general metaphysics. We show that the current metaphysical battlefield is richer and more complex than a simple dichotomy between “metaphysics of science” and “traditional metaphysics”, and (...) that it should instead be understood as a three dimensional “box”, with one axis distinguishing “descriptive metaphysics” from “revisionary metaphysics”, a second axis distinguishing a priori from a posteriori metaphysics, and a third axis distinguishing “commonsense metaphysics”, “traditional metaphysics” and “metaphysics of science”. We use this three-dimensional figure to shed light on the project of current metaphysics of science, and to demonstrate that, in many instances, the target of that project is not defined with enough precision and clarity. (shrink)

Systems biologists often distance themselves from reductionist approaches and formulate their aim as understanding living systems “as a whole.” Yet, it is often unclear what kind of reductionism they have in mind, and in what sense their methodologies would offer a superior approach. To address these questions, we distinguish between two types of reductionism which we call “modular reductionism” and “bottom-up reductionism.” Much knowledge in molecular biology has been gained by decomposing living systems into functional modules or through detailed studies (...) of molecular processes. We ask whether systems biology provides novel ways to recompose these findings in the context of the system as a whole via computational simulations. As an example of computational integration of modules, we analyze the first whole-cell model of the bacterium M. genitalium. Secondly, we examine the attempt to recompose processes across different spatial scales via multi-scale cardiac models. Although these models rely on a number of idealizations and simplifying assumptions as well, we argue that they provide insight into the limitations of reductionist approaches. Whole-cell models can be used to discover properties arising at the interfaces of dynamically coupled processes within a biological system, thereby making more apparent what is lost through decomposition. Similarly, multi-scale modeling highlights the relevance of macroscale parameters and models and challenges the view that living systems can be understood “bottom-up.” Specifically, we point out that system-level properties constrain lower-scale processes. Thus, large-scale modeling reveals how living systems at the same time are more and less than the sum of the parts. (shrink)

An adequate account of how inferences and discoveries are made in modern biology is a difficult prospect for a philosopher. Do we really deduce conclusions from Darwin’s principles? Once Darwinian biology is integrated with molecular biology, can we deduce the organism from its DNA? What does induction look like in an era where data sets are often too large to be processed by a human being? What is the role of abductive explanatory claims that try to define the biological individual (...) in relation to the microbiome with which it may be associated, or to revise the notion of evolution when the interaction of organism and environment comes to seem much more complex than earlier generations imagined. How should we evaluate “origins of life” experiments conducted in the laboratory, where chemistry shifts to biology and we try to recreate early conditions on earth to which we have no empirical access? How are the carefully controlled conditions in the lab to be brought into productive relationship with the messy, contingent outdoor work of biologists in the field, studying crabs or eelgrass at the edge of the Pacific Ocean, or prairie plants at the end of woods, on the plains of the Midwest. To answer these questions, I sent my graduate student Tano Posteraro to work with Ted Grosholz, a marine biologist at the University of California / Davis, and my undergraduate student Alex Grigas to work with Ruth Geyer Shaw, a population geneticist at the University of Minnesota. They came back with complex and interesting answers to these questions. (shrink)

Even though complexity is a concept that is ubiquitously used by biologists and philosophers of biology, it is rarely made precise. I argue that a clarification of the concept is neither trivial nor unachievable, and I propose a unifying framework based on the technical notion of “effective complexity” that allows me to do justice to conflicting intuitions about biological complexity, while taking into account several distinctions in the usage of the concept that are often overlooked. In particular, I propose a (...) distinction between two kinds of complexity, “mechanical” and “emergent”, which can be understood as different ways of relating the effective complexity of mechanisms and of behaviors in biological explanations. I illustrate the adequacy of this framework by discussing different attempts to understand intracellular organization in terms of pathways and networks. My framework provides a different way of thinking about recent philosophical debates, for example, on the difference between mechanistic and topological explanations and about the concept of emergence. Moreover, it can contribute to a proper assessment of metascientific arguments that invoke biological complexity. (shrink)

A lot of philosophy taught to science students consists of scientific methodology. But many philosophy of science textbooks have a fraught relationship with methodology, presenting it either a system of universal principles or entirely permeated by contingent factors not subject to normative assessment. In this paper, I argue for an alternative, heuristic perspective for teaching methodology: as fallible, purpose- and context-dependent, subject to cost-effectiveness considerations and systematically biased, but nevertheless subject to normative assessment. My pedagogical conclusion from this perspective is (...) that philosophers should aim to teach science students heuristic reasoning: strategies of normative method choice appraisal that are sensitive to purposes, contexts, biases and cost-effectiveness considerations; and that we should do so by teaching them exemplars of such reasoning. I illustrate this proposal at the hand of three such exemplars, showing how they help students to appreciate the heuristic nature of both methods and methodology, and to normatively assess method choice in such circumstances. (shrink)

Scientific methods are heuristic in nature. Heuristics are simplifying, incomplete, underdetermined and fallible problem-solving rules that can nevertheless serve certain goals in certain contexts better than truth-preserving algorithms. Because of their goal- and context-dependence, a framework is needed for systematic choosing between them. This is the domain of scientific methodology. Such a methodology, I argue, relies on a form of instrumental rationality. Three challenges to such an instrumentalist account are addressed. First, some authors have argued that the rational choice of (...) at least some methods, namely those supporting belief formation, is not goal-dependent. Second, some authors have observed that some method choices seem intuitively rational, even though relevant goals are lacking. Thirdly, some authors have argued that instrumental rationality itself depends on a goal-independent form of rationality. It is the heuristic nature of scientific methods that affords me the arguments against these challenges. This heuristic-instrumentalist account provides the means-ends analysis needed to evaluate heuristic method choice. The paper thus offers the conceptual basis for a scientific methodology that is both compatible with the heuristic nature of actual scientific practice and also normatively relevant for assessing method choice. (shrink)

Many scientific models lack an established representation relation to actual targets and instead refer to merely possible processes, background conditions, and results. This article shows how such models can be appraised. On the basis of the discussion of how-possibly explanations, five types of learning opportunities are distinguished. For each of these types, an example—from economics, biology, psychology, and sociology—is discussed. Contexts and purposes are identified in which the use of a model offers a genuine opportunity to learn. These learning opportunities (...) offer novel justifications for modeling practices that fall between the cracks of standard representationalist appraisals of models. (shrink)

I characterize Wimsatt’s approach to philosophy of science as philosophy for science and then briefly consider a theme emerging from his work that informs just one of the many current developments in philosophy of biology that he inspired: scaffolding as a problem of mechanistic explanation for functionalists.

Dobzhansky argued that biology only makes sense if life on earth has a shared history. But his dictum is often reinterpreted to mean that biology only makes sense in the light of adaptation. Some philosophers of science have argued in this spirit that all work in ‘proximal’ biosciences such as anatomy, physiology and molecular biology must be framed, at least implicitly, by the selection histories of the organisms under study. Others have denied this and have proposed non-evolutionary ways in which (...) biologists can frame these investigations. This paper argues that an evolutionary perspective is indeed necessary, but that it must be a forward-looking perspective informed by a general understanding of the evolutionary process, not a backward-looking perspective informed by the specific evolutionary history of the species being studied. Interestingly, it turns out that there are aspects of proximal biology that even a creationist cannot study except in the light of a theory of their effect on future evolution. (shrink)

Exact sciences are described as sciences whose theories are formalized. These are contrasted to inexact sciences, whose theories are not formalized. Formalization is described as a broader category than mathematization, involving any form/content distinction allowing forms, e.g., as represented in theoretical models, to be studied independently of the empirical content of a subject-matter domain. Exactness is a practice depending on the use of theories to control subject-matter domains and to align theoretical with empirical models and not merely a state of (...) a science. Inexact biological sciences tolerate a degree of “mismatch” between theoretical and empirical models and concepts. Three illustrations from biological sciences are discussed in which formalization is achieved by various means: Mendelism, Weismannism, and Darwinism. Frege’s idea of a “conceptual notation” is used to further characterize the notion of a form/content distinction. (shrink)

In recent years, the philosophical focus of the modeling literature has shifted from descriptions of general properties of models to an interest in different model functions. It has been argued that the diversity of models and their correspondingly different epistemic goals are important for developing intelligible scientific theories. However, more knowledge is needed on how a combination of different epistemic means can generate and stabilize new entities in science. This paper will draw on Rheinberger’s practice-oriented account of knowledge production. The (...) conceptual repertoire of Rheinberger’s historical epistemology offers important insights for an analysis of the modelling practice. I illustrate this with a case study on network modeling in systems biology where engineering approaches are applied to the study of biological systems. I shall argue that the use of multiple means of representations is an essential part of the dynamic of knowledge generation. It is because of – rather than in spite of – the diversity of constraints of different models that the interlocking use of different epistemic means creates a potential for knowledge production. (shrink)

This paper explores the relation between scientific knowledge and common sense intuitions as a complement to Hoyningen-Huene’s account of systematicity. On one hand, Hoyningen-Huene embraces continuity between these in his characterization of scientific knowledge as an extension of everyday knowledge, distinguished by an increase in systematicity. On the other, he argues that scientific knowledge often comes to deviate from common sense as science develops. Specifically, he argues that a departure from common sense is a price we may have to pay (...) for increased systematicity. I argue that to clarify the relation between common sense and scientific reasoning, more attention to the cognitive aspects of learning and doing science is needed. As a step in this direction, I explore the potential for cross-fertilization between the discussions about conceptual change in science education and philosophy of science. Particularly, I examine debates on whether common sense intuitions facilitate or impede scientific reasoning. While contending that these debates can balance some of the assumptions made by Hoyningen-Huene, I suggest that a more contextualized version of systematicity theory could supplement cognitive analysis by clarifying important organizational aspects of science. (shrink)

Design thinking in general, and optimality modeling in particular, have traditionally been associated with adaptationism—a research agenda that gives pride of place to natural selection in shaping biological characters. Our goal is to evaluate the role of design thinking in non-evolutionary analyses. Specifically, we focus on research into abstract design principles that underpin the functional organization of extant organisms. Drawing on case studies from engineering-inspired approaches in biology we show how optimality analysis, and other design-related methods, play a specific methodological (...) role that is tangential to the study of adaptation. To account for the role of these reasoning strategies in contemporary biology, we therefore suggest a reevaluation of the connection between design thinking and adaptationism. (shrink)

Concerns with the use of engineering approaches in biology have recently been raised. I examine two related challenges to biological research that I call the synchronic and diachronic underdetermination problem. The former refers to challenges associated with the inference of design principles underlying system capacities when the synchronic relations between lower-level processes and higher-level systems capacities are degenerate. The diachronic underdetermination problem regards the problem of reverse engineering a system where the non-linear relations between system capacities and lower-level mechanisms are (...) changing over time. Braun and Marom argue that recent insights to biological complexity leave the aim of reverse engineering hopeless - in principle as well as in practice. While I support their call for systemic approaches to capture the dynamic nature of living systems, I take issue with the conflation of reverse engineering with naïve reductionism. I clarify how the notion of design principles can be more broadly conceived and argue that reverse engineering is compatible with a dynamic view of organisms. It may even help to facilitate an integrated account that bridges the gap between mechanistic and systems approaches. (shrink)

Adaptationism has for decades been the topic of sophisticated debates in philosophy of biology but methodological adaptationism has not received as much attention as the empirical and explanatory issues. In addition, adaptationism has mainly been discussed in the context of evolutionary biology and not in fields such as zoophysiology and systems biology where this heuristic is also used in design analyses of physiological traits and molecular structures. This paper draws on case studies from these fields to discuss the productive and (...) problematic aspects of this heuristic in different research practices, in functional as well as evolutionary studies on different levels of biological organization. Gould and Lewontin’s Spandrels-paper famously criticized adaptationist methodology for implying the risk of generating ‘blind spots’ with respect to non-selective effects on evolution. Some have claimed that this bias can be accommodated through the testing of evolutionary hypotheses. Although this is an important aspect of overcoming naïve adaptationism, I argue that the issue of methodological biases is broader than the question of testability. I demonstrate the productivity of adaptationist heuristics but also discuss the deeper problematic aspects associated with the methodological imperialism that is part of the strong adaptationist position. (shrink)

This article examines a scientific controversy that raged for twenty years in physical organic chemistry during the second half of the twentieth century. After explaining what was at stake in the non-classical ion debate, I attempt—by examining the methodological reflections of some of the participants—a partial explanation of what sustained this controversy, particularly during its early stages. Instead of suggesting a breakdown of scientific method or the unavoidable historical contingency of scientific development, the endurance of this controversy instead reveals the (...) heuristic and pragmatic character of many of the explanations and predictions generated by theoretical organic chemistry. The results in this case are used to suggest a new role for the study of scientific controversies in revealing the economics of scientific inquiry. 1 Introduction2 The Non-classical Ion Debate3 Models for the 2-Norbornyl System4 Soft Theories and Reasoning by Analogy5 Scientific Controversy and the Non-classical Ion Debate6 Conclusion. (shrink)

Not by Genes Alone excellently explains Peter J. Richerson and Robert Boyd's important ideas about human gene-culture co-evolution to a broader audience but remains short of a larger vision of civilization. Several decades ago Ralph Burhoe had seen that fertile possibility in Richerson and Boyd's work. I suggest getting past present reductionistic customs to a scientific perspective having an integral place for virtue. Subsystem agency is part of this view, as is the driving role of abundance, whose ultimate origins are (...) in the mysterious, quintessentially energetic Big Bang. The free-rider problem may not impede higher social organization as inexorably as Richerson and Boyd believe; "the tragedy" of enervating leakage from "the commons" may often be less influential than an invigorating flow of externalities to the commons. Eukaryotic origins mark the origin of inevitable wider sharing as higher living systems evolve. I use a metaphor of flesh and spirit in drawing a parallel between that turning point and the wide sharing that occurs in civilization. This helps solve the enigma of the demographic transition. Why do so many productive participants in first-world societies severely restrict their selfish-gene reproduction to below replacement birth rate? It is not because culture is maladaptive but because civilization's brain and womb have become partially differentiated in distinct populations. Considerations of social boundaries, myths of sacrifice, and human creativity help in understanding how human social evolution taps potentials present in reality. Human beings' diverse vigorous activities—the organized ones and the inadvertent ones, the wise and the foolish, the good and the bad, the carefully thoughtful and the merely playful—provide the ground of being, or primordial soup, for cultural entities that transcend our intentions. If we have it right for the most part and are fortunate, we will continue to emerge at higher levels. (shrink)

Philosophers of science diverge on the question what drives the growth of scientific knowledge. Most of the twentieth century was dominated by the notion that theories propel that growth whereas experiments play secondary roles of operating within the theoretical framework or testing theoretical predictions. New experimentalism, a school of thought pioneered by Ian Hacking in the early 1980s, challenged this view by arguing that theory-free exploratory experimentation may in many cases effectively probe nature and potentially spawn higher evidence-based theories. Because (...) theories are often powerless to envisage workings of complex biological systems, theory-independent experimentation is common in the life sciences. Some such experiments are triggered by compelling observation, others are prompted by innovative techniques or instruments, whereas different investigations query big data to identify regularities and underlying organizing principles. A distinct fourth type of experiments is motivated by a major question. Here I describe two question-guided experimental discoveries in biochemistry: the cyclic adenosine monophosphate mediator of hormone action and the ubiquitin-mediated system of protein degradation. Lacking underlying theories, antecedent data bases, or new techniques, the sole guides of the two discoveries were respective substantial questions. Both research projects were similarly instigated by theory-free exploratory experimentation and continued in alternating phases of results-based interim working hypotheses, their examination by experiment, provisional hypotheses again, and so on. These two cases designate theory-free, question-guided, stepwise biochemical investigations as a distinct subtype of the new experimentalism mode of scientific enquiry. (shrink)

We argue that two powerful error-theoretic concepts provide a general framework that satisfactorily accounts for key aspects of the explanation of physical patterns. This method gives an objective criterion to determine which mathematical models in a class of neighboring models are just as good as the exact one. The method also emphasizes that abstraction is essential for explanation and provides a precise conceptual framework that determines whether a given abstraction is explanatorily relevant and justified. Hence, it increases our epistemological understanding (...) of how one should go about reconstructing scientific practices by making clear that, at a fundamental level, a key aspect of mathematical modeling consists in exactly solving nearby problems. (shrink)

Blumenthal-Barby and colleagues (2022) argue that philosophy continues to be relevant to bioethics. To support their argument, they offer several examples of how—not philosophy, exactly—but normati...

In this paper, we critically and constructively examine the methodology of evidence-based development economics, which deploys randomized field experiments as its main tool. We describe the...