Scientific realists argue that a good track record of multi-agent, and multiple method, validation of empirical claims is itself evidence that those claims, at least partially and approximately, reflect ways nature actually is independent of the ways we conceptualize it. Constructivists contend that successes in validating empirical claims only suffice to establish that our ways of modelling the world, our “constructions,” are useful and adequate for beings like us. This essay presents a thought experiment in which beings like us intersubjectively (...) validate claims about properties of particular things in nature under conditions in which those beings have profoundly different personal phenomenological experiences of those properties. I submit that the thought experiment scenario parallels our actual situation, and argue that this shows that successes in intersubjectively validating empirical claims are indeed enough to claim victory for the realist. More specifically, I champion a variation of realism that marries Ronald Giere’s brand of ‘perspectival realism’ with Philip Kitcher’s ‘real realism,’ and posits that causal relations between ourselves and properties instantiated in nature ground our references to the relevant properties even though our conceptions of them are perspective relative. (shrink)

This comment discusses Kaidesoja and raises the issue whether his analysis justifies stronger conclusions than he presents in the book. My comments focus on four issues. First, I argue that his naturalistic reconstruction of critical realist transcendental arguments shows that transcendental arguments should be treated as a rare curiosity rather than a general argumentative strategy. Second, I suggest that Kaidesoja’s analysis does not really justify his optimism about the usefulness of causal powers ontology in the social sciences. Third, I raise (...) some doubts about the heuristic value of Mario Bunge’s social ontology that Kaidesoja presents as a replacement for critical realist ontology. Finally, I propose an alternative way to analyze failures of aggregativity that might better serve Kaidesoja’s purposes than the Wimsattian scheme he employs in the book. (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)

Humans are capable of understanding an incredible variety of actions performed by other humans. Even though these range from primary biological actions, like eating and fleeing, to acts in parliament or in poetry, humans generally can make sense of each other’s actions. Action understanding is the cognitive ability to make sense of another person’s action by integrating perceptual information about the behavior with knowledge about the immediate and sociocultural contexts of the action, understanding of relevant meanings and one’s own experience. (...) Given the importance of action understanding in every domain of human life and society, and in light of the complexities that surround it, a comprehensive scientific understanding of this capacity is needed. Scholars are increasingly dissatisfied with monodisciplinary approaches to understanding human action, like when an action is interpreted only in sociocultural terms while overlooking cognitive constraints, or when an action is understood in biological terms while neglecting its psychological impact on the agent. Recent interdisciplinary endeavors demonstrate how an interdisciplinary approach is possible when investigating complex functions like action understanding. Ever more insight is gained in the mutual influences between biological, cognitive and sociocultural processes that together contribute to action and action understanding. The purpose of this chapter is to describe how a ‘mechanistic explanation’, or a ‘mechanism-based explanation’ of action understanding provides a theoretical framework for integrating various and often conflicting disciplinary insights. By applying the heuristics of ‘definition’, ‘decomposition’ and ‘localization’, researchers can determine the phenomenon that they collaboratively investigate while at the same time dividing this task into smaller component tasks of which the results must eventually be put together. Some researchers, for example, can apply a hermeneutic approach to the sociocultural environment in which action understanding takes place, while others aim to specify the cognitive processes or the neuro-electrical pathways that are activated under those conditions. After having presented a step-by-step analysis of an interdisciplinary investigation of action understanding by way of developing a mechanistic explanation the chapter closes with some suggestions for testing its result and mentions some limitations of this approach. (shrink)

. Reproducible results and repeatable measurements at the same location are fundamental to science, yet of grave concern to scientists. Involvement in biological re-surveys under MVZ-Berkeley, Harvard-LTER and Hamaarag elucidated “replication” and “location” and untangled “incommensurability” from “no fact of the matter” and “indeterminacy.” All cases revealed incommensurability without indeterminacy on the smallest scale and indeterminacy without incommensurability on higher scales, with communication failure in the former and successful workarounds in the latter. I argue that an involved philosophy helps clarify (...) fundamental concepts in this case, and since it could also help other cases it therefore should be examined in every case before being ruled out. (shrink)

Discussions over whether these natural kinds exist, what is the nature of their existence, and whether natural kinds are themselves natural kinds aim to not only characterize the kinds of things that exist in the world, but also what can knowledge of these categories provide. Although philosophically critical, much of the past discussions of natural kinds have often answered these questions in a way that is unresponsive to, or has actively avoided, discussions of the empirical use of natural kinds and (...) what I dub “activities of natural kinding” and “natural kinding practices”. The natural kinds of a particular discipline are those entities, events, mechanisms, processes, relationships, and concepts that delimit investigation within it—but we might reasonably ask: How are these natural kinds discovered?, How are they made?, Are they revisable?, and Where do they come from? A turn to natural kinding practices reveals a new set of questions open for investigation: How do natural kinds explain through practice?, What are natural kinding practices and classifications and why should we care?, What is the nature of natural kinds viewed as a set of activities?, and How do practice approaches to natural kinds shape and reconfigure scientific disciplines? Natural kinds have traditionally been discussed in terms of how they classify the contents of the world. The metaphysical project has been one which identifies essences, laws, sameness relations, fundamental properties, and clusters of family resemblances and how these map out the ontological space of the world. But actually how this is done has been less important in the discussion than the resultant categories that are produced. I aim to rectify these omissions and suggest a new metaphysical project investigating kinds in practice. (shrink)

This paper offers a critique of an account of explanatory integration that claims that explanations of cognitive capacities by functional analyses and mechanistic explanations can be seamlessly integrated. It is shown that achieving such explanatory integration requires that the terms designating cognitive capacities in the two forms of explanation are stable but that experimental practice in the mind-brain sciences currently is not directed at achieving such stability. A positive proposal for changing experimental practice so as to promote such stability is (...) put forward and its implications for explanatory integration are briefly considered. (shrink)

This paper addresses philosophical issues concerning whether mental disorders are natural kinds and how the DSM should classify mental disorders. I argue that some mental disorders (e.g., schizophrenia, depression) are natural kinds in the sense that they are natural classes constituted by a set of stable biological mechanisms. I subsequently argue that a theoretical and causal approach to classification would provide a superior method for classifying natural kinds than the purely descriptive approach adopted by the DSM since DSM-III. My argument (...) suggests that the DSM should classify natural kinds in order to provide predictively useful (i.e., projectable) diagnostic categories and that a causal approach to classification would provide a more promising method for formulating valid diagnostic categories. (shrink)

In robustness analysis, hypotheses are supported to the extent that a result proves robust, and a result is robust to the extent that we detect it in diverse ways. But what precise sense of diversity is at work here? In this paper, I show that the formal explications of evidential diversity most often appealed to in work on robustness – which all draw in one way or another on probabilistic independence – fail to shed light on the notion of diversity (...) relevant to robustness analysis. I close by briefly outlining a promising alternative approach inspired by Horwich’s (1982) eliminative account of evidential diversity. (shrink)

I propose a distinct type of robustness, which I suggest can support a confirmatory role in scientific reasoning, contrary to the usual philosophical claims. In model robustness, repeated production of the empirically successful model prediction or retrodiction against a background of independentlysupported and varying model constructions, within a group of models containing a shared causal factor, may suggest how confident we can be in the causal factor and predictions/retrodictions, especially once supported by a variety of evidence framework. I present climate (...) models of greenhouse gas global warming of the 20th Century as an example, and emphasize climate scientists’ discussions of robust models and causal aspects. The account is intended as applicable to a broad array of sciences that use complex modeling techniques. (shrink)

There is increasing attention to the centrality of idealization in science. One common view is that models and other idealized representations are important to science, but that they fall short in one or more ways. On this view, there must be an intermediary step between idealized representation and the traditional aims of science, including truth, explanation, and prediction. Here I develop an alternative interpretation of the relationship between idealized representation and the aims of science. In my view, continuing, widespread idealization (...) calls into question the idea that science aims for truth. I argue that understanding must replace truth as the ultimate epistemic aim of science. Additionally, science has a wide variety aims, epistemic and non-epistemic, and these aims motivate different kinds of scientific products. Finally, I show how these diverse aims---all rather distant from truth---result in the expanded influence of social values on science. (shrink)

The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory of computational explanation, I (...) argue that large-scale simulations require that the explanandum phenomenon is identified; otherwise, the explanatory value of such explanations is difficult to establish, and testing the model empirically by comparing its behavior with the explanandum remains practically impossible. The completeness of the explanation, and hence of the explanatory value of the explanatory model, is to be assessed vis-à-vis the explanandum phenomenon, which is not to be conflated with raw observational data and may be idealized. I argue that idealizations, which include building models of a single phenomenon displayed by multi-functional mechanisms, lumping together multiple factors in a single causal variable, simplifying the causal structure of the mechanisms, and multi-model integration, are indispensable for complex systems such as brains; otherwise, the model may be as complex as the explanandum phenomenon, which would make it prone to so-called Bonini paradox. I conclude by enumerating dimensions of empirical validation of explanatory models according to new mechanism, which are given in a form of a “checklist” for a modeler. (shrink)

In this article I address the issue of the ontological conditions of possibility for a naturalistic notion of emergence, trying to determine its fundamental differences from the atomist, vitalist, preformationist and potentialist alternatives. I will argue that a naturalistic notion of ontological emergence can only succeed if we explicitly refuse the atomistic fundamental ontological postulate that asserts that every entity is endowed with a set of absolutely intrinsic properties, being qualitatively immutable through its extrinsic relations. Furthermore, it will be shown (...) that, ironically enough, this metaphysical assumption is implicitly shared by all the above mentioned alternatives to Emergentism. The current article concludes that the notion of organization by itself is not enough, and that ontological emergence can only be justified by assuming a relational ontological perspective that, in opposition both to atomism and holism, defends that the existence-conditions, the identity and the causal behavior of any emergent systemic property can only be conceived, and explained, as constructed by and through specific networks of qualitatively transformative relational processes that occur between the system’s components and between the system and its environment. Additionally, I try to explain how one can make sense of the idea that an emergent phenomenon is both dependent on, and autonomous from, its emergence base. (shrink)

Scientists use models to understand the natural world, and it is important not to conflate model and nature. As an illustration, we distinguish three different kinds of populations in studies of ecology and evolution: theoretical, laboratory, and natural populations, exemplified by the work of R.A. Fisher, Thomas Park, and David Lack, respectively. Biologists are rightly concerned with all three types of populations. We examine the interplay between these different kinds of populations, and their pertinent models, in three examples: the notion (...) of “effective” population size, the work of Thomas Park on /Tribolium/ populations, and model-based clustering algorithms such as /Structure/. Finally, we discuss ways to move safely between three distinct population types while avoiding confusing models and reality. (shrink)

In this contribution, I comment on Raffaella Campaner’s defense of explanatory pluralism in psychiatry (in this volume). In her paper, Campaner focuses primarily on explanatory pluralism in contrast to explanatory reductionism. Furthermore, she distinguishes between pluralists who consider pluralism to be a temporary state on the one hand and pluralists who consider it to be a persisting state on the other hand. I suggest that it would be helpful to distinguish more than those two versions of pluralism – different understandings (...) of explanatory pluralism both within philosophy of science and psychiatry – namely moderate/temporary pluralism, anything goes pluralism, isolationist pluralism, integrative pluralism and interactive pluralism. Next, I discuss the pros and cons of these different understandings of explanatory pluralism. Finally, I raise the question of how to implement or operationalize explanatory pluralism in scientific practice; how to structure the “genuine dialogue” or shape “the pluralistic attitude” Campaner is referring to. As tentative answers, I explore a question-based framework for explanatory pluralism as well as social-epistemological procedures for interaction among competing approaches and explanations. (shrink)

We argue that the mathematization of science should be understood as a normative activity of advocating for a particular methodology with its own criteria for evaluating good research. As a case study, we examine the mathematization of taxonomic classification in systematic biology. We show how mathematization is a normative activity by contrasting its distinctive features in numerical taxonomy in the 1960s with an earlier reform advocated by Ernst Mayr starting in the 1940s. Both Mayr and the numerical taxonomists sought to (...) formalize the work of classification, but Mayr introduced a qualitative formalism based on human judgment for determining the taxonomic rank of populations, while the numerical taxonomists introduced a quantitative formalism based on automated procedures for computing classifications. The key contrast between Mayr and the numerical taxonomists is how they conceptualized the temporal structure of the workflow of classification, specifically where they allowed meta-level discourse about difficulties in producing the classification. (shrink)

Many philosophers are skeptical about the scientific value of the concept of biological information. However, several have recently proposed a more positive view of ascribing information as an exercise in scientific modeling. I argue for an alternative role: guiding empirical data collection for the sake of theorizing about the evolution of semantics. I clarify and expand on Bergstrom and Rosvall’s suggestion of taking a “diagnostic” approach that defines biological information operationally as a procedure for collecting empirical cases. The more recent (...) modeling-based accounts still perpetuate a theory-centric view of scientific concepts, which motivated philosophers’ misplaced skepticism in the first place. (shrink)

Okasha claims at the outset of his book "Evolution and the Levels of Selection" (2006) that the Price equation lays bare the fundamentals underlying all selection phenomena. However, the thoroughness of his subsequent analysis of multi-level selection theories leads him to abandon his fundamentalist commitments. At critical points he invokes cost benefit analyses that sometimes favors the Price approach and sometimes the contextual approach, sometimes favors MLS1 and sometimes MLS2. And although he doesn’t acknowledge it, even the Price approach breaks (...) down into a family of alternative equations that parse the causes in different ways, none of which is uniquely correct and none of which achieves the ultimate isolation of effects due to what Okasha believes are the fundamental causes. I argue that his book provides good reason to re-conceive our understanding of evolutionary theorizing in terms of a toolbox view (developed here) and to stop subjecting the analyses of evolutionary concepts to a universalist standard. (shrink)

Biologists seems to hold two fundamental beliefs: Organisms are organized into levels and the individuals at these levels differ in their properties. Together these suggest that there will be massive multiple realization, i.e. that many human psychological properties are multiply realized at many neurobiological levels. This paper provides some documentation in support of this suggestion.

In the past half century, the theory of the firm has become a specific and prolific research field. However, the social ontology of this central institution of capitalism has never truly been the subject of investigation. I consider this negligence harmful for organizational economics and management and, more broadly, for the social sciences, notably because the first and central question raised by the theory of the firm relates to its nature: What is a firm? For this reason, I propose some (...) novel considerations for a social ontology of the firm by focusing on social emergence, reconstitution, the two-level institutional logic of the firm, complex organizational dynamics and interacting mechanisms, and power. (shrink)

A participant–observer who is both informed and interested in ethical issues, and is embedded within a nanotechnology research and development facility may be able to influence the ethical awareness of researchers in nanotechnology, and tease out the societal implications of the work being conducted. Two inter-disciplinary methods were employed: (1) regular involvement in the technical and scientific research at the facility by the participant–observer, and (2) repeated interactions and discussions between the participant–observer and the scientists. As a result of this (...) qualitative approach, an ethics questionnaire was developed and tested. This questionnaire has been incorporated into the admissions procedures for researchers as they commence use of the nanotech facility. The questionnaire highlights the importance of ethical issues in nanotechnology research and draws researchers into an engagement with possible ethical consequences and with future societal implications of their work. (shrink)

In this article we use a hybrid methodology to better understand the skilful performance of sports teams as an exemplar of distributed cognition. We highlight key differences between a team of individual experts and an expert team, and outline the kinds of shared characteristics likely to be found in an expert team. We focus on the way that shared knowledge contributes to expert team performance. In particular, we suggest that certain kinds of shared knowledge and shared skill, potentially developed through (...) a team’s history of playing and training together, facilitate successful coordination. These kinds of shared knowledge and skill may be less developed in a team of experts without a shared history. Exploring the expert performance of sports teams informs our understanding of distributed cognition and collaboration more generally and creates avenues for further philosophical and empirical investigation. (shrink)

In this article, I argue that the use of scientific models that attribute intentional content to complex systems bears a striking similarity to the way in which statistical descriptions are used. To demonstrate this, I compare and contrast an intentional model with a statistical model, and argue that key similarities between the two give us compelling reasons to consider both as a type of phenomenological model. I then demonstrate how intentional descriptions play an important role in scientific methodology as a (...) type of phenomenal model, and argue that this makes them as essential as any other model of this type. (shrink)

We propose another positive illusion that fits with McKay & Dennett's (M&D's) criteria for adaptive misbeliefs. This illusion is pervasive in adult reasoning but we focus on its prevalence in children's developing theories. It is a strongly held conviction arising from normal functioning of the doxastic system that confers adaptive advantage on the individual.

Traditional accounts of the role of learning in evolution have concentrated upon its capacity as a source of fitness to individuals. In this paper I use a case study from invasive species biology—the role of conditioned taste aversion in mitigating the impact of cane toads on the native species of Northern Australia—to highlight a role for learning beyond this—as a source of evolvability to populations. This has two benefits. First, it highlights an otherwise under-appreciated role for learning in evolution that (...) does not rely on social learning as an inheritance channel nor “special” evolutionary processes such as genetic accommodation (both of which many are skeptical about). Second, and more significantly, it makes clear important and interesting parallels between learning and exploratory behaviour in development. These parallels motivate the applicability of results from existing research into learning and learning evolution to our understanding of the evolution of evolvability more generally. (shrink)

Two controversies exist regarding the appropriate characterization of hierarchical and adaptive evolution in natural populations. In biology, there is the Wright-Fisher controversy over the relative roles of random genetic drift, natural selection, population structure, and interdemic selection in adaptive evolution begun by Sewall Wright and Ronald Aylmer Fisher. There is also the Units of Selection debate, spanning both the biological and the philosophical literature and including the impassioned group-selection debate. Why do these two discourses exist separately, and interact relatively little? (...) We postulate that the reason for this schism can be found in the differing focus of each controversy, a deep difference itself determined by distinct general styles of scientific research guiding each discourse. That is, the Wright-Fisher debate focuses on adaptive process, and tends to be instructed by the mathematical modeling style, while the focus of the Units of Selection controversy is adaptive product, and is typically guided by the function style. The differences between the two discourses can be usefully tracked by examining their interpretations of two contested strategies for theorizing hierarchical selection: horizontal and vertical averaging. (shrink)

This paper is a supplement to, and provides a proof of principle of, Kuhn vs. Popper on Criticism and Dogmatism in Science: A Resolution at the Group Level. It illustrates how calculations may be performed in order to determine how the balance between different functions in science—such as imaginative, critical, and dogmatic—should be struck, with respect to confirmation (or corroboration) functions and rules of scientific method.

I argue that examining the explanatory power of the hypothesis of extended cognition (HEC) offers a fruitful approach to the problem of cognitive system demarcation. Although in the discussions on HEC it has become common to refer to considerations of explanatory power as a means for assessing the plausibility of the extended cognition approach, to date no satisfying account of explanatory power has been presented in the literature. I suggest that the currently most prominent theory of explanation in the special (...) sciences, James Woodward’s contrastive-counterfactual theory, and an account of explanatory virtues building on that theory can be used to develop a systematic picture of cognitive system demarcation in the psychological sciences. A major difference between my differential influence (DI) account and most other theories of cognitive extension is the cognitive systems pluralism implied by my approach. By examining the explanatory power of competing traditions in psychological memory research, I conclude that internalist and externalist classificatory strategies are characterized by different profiles of explanatory virtues and should often be considered as complementary rather than competing approaches. This suggests a deflationary interpretation of HEC. (shrink)

Many scientific models are non-representational in that they refer to merely possible processes, background conditions and results. The paper shows how such non-representational models can be appraised, beyond the weak role that they might play as heuristic tools. Using conceptual distinctions from the discussion of how-possibly explanations, six types of models are distinguished by their modal qualities of their background conditions, model processes and model results. For each of these types, an actual model example – drawn from economics, biology, psychology (...) or sociology – is discussed. For each case, contexts and purposes are identified in which the use of such a model offers a genuine opportunity to learn – i.e. justifies changing one’s confidence in a hypothesis about the world. These cases then offer novel justifications for modelling practices that fall between the cracks of standard representational accounts of models. (shrink)

Standard microbial evolutionary ontology is organized according to a nested hierarchy of entities at various levels of biological organization. It typically detects and defines these entities in relation to the most stable aspects of evolutionary processes, by identifying lineages evolving by a process of vertical inheritance from an ancestral entity. However, recent advances in microbiology indicate that such an ontology has important limitations. The various dynamics detected within microbiological systems reveal that a focus on the most stable entities (or features (...) of entities) over time inevitably underestimates the extent and nature of microbial diversity. These dynamics are not the outcome of the process of vertical descent alone. Other processes, often involving causal interactions between entities from distinct levels of biological organisation, or operating at different time scales, are responsible not only for the destabilisation of pre-existing entities, but also for the emergence and stabilisation of novel entities in the microbial world. In this article we consider microbial entities as more or less stabilised functional wholes, and sketch a network-based ontology that can represent a diverse set of processes including, for example, as well as phylogenetic relations, interactions that stabilise or destabilise the interacting entities, spatial relations, ecological connections, and genetic exchanges. We use this pluralistic framework for evaluating (i) the existing ontological assumptions in evolution (e.g. whether currently recognized entities are adequate for understanding the causes of change and stabilisation in the microbial world), and (ii) for identifying hidden ontological kinds, essentially invisible from within a more limited perspective. We propose to recognize additional classes of entities that provide new insights into the structure of the microbial world, namely “processually equivalent” entities, “processually versatile” entities, and “stabilized” entities. (shrink)

In the contemporary life sciences more and more researchers emphasize the “limits of reductionism” (e.g. Ahn et al. 2006a, 709; Mazzocchi 2008, 10) or they call for a move “beyond reductionism” (Gallagher/Appenzeller 1999, 79). However, it is far from clear what exactly they argue for and what the envisioned limits of reductionism are. In this paper I claim that the current discussions about reductionism in the life sciences, which focus on methodological and explanatory issues, leave the concepts of a reductive (...) method and a reductive explanation too unspecified. In order to fill this gap and to clarify what the limits of reductionism are I identify three reductive methods that are crucial in the current practice of the life sciences: decomposition, focusing on internal factors, and studying parts in isolation. Furthermore, I argue that reductive explanations in the life sciences exhibit three characteristics: first, they refer only to factors at a lower level than the phenomenon at issue, second, they focus on internal factors and thus ignore or simplify the environment of a system, and, third, they cite only the parts of a system in isolation. (shrink)

Philosophy can shed light on mathematical modeling and the juxtaposition of modeling and empirical data. This paper explores three philosophical traditions of the structure of scientific theory—Syntactic, Semantic, and Pragmatic—to show that each illuminates mathematical modeling. The Pragmatic View identifies four critical functions of mathematical modeling: (1) unification of both models and data, (2) model fitting to data, (3) mechanism identification accounting for observation, and (4) prediction of future observations. Such facets are explored using a recent exchange between two groups (...) of mathematical modelers in plant biology. Scientific debate can arise from different modeling philosophies. (shrink)

This paper compares the two known logical forms of hierarchy, both of which have been used in models of natural phenomena, including the biological. I contrast their general properties, internal formal relations, modes of growth (emergence) in applications to the natural world, criteria for applying them, the complexities that they embody, their dynamical relations in applied models, and their informational relations and semiotic aspects.

A classic analytic approach to biological phenomena seeks to refine definitions until classes are sufficiently homogenous to support prediction and explanation, but this approach founders on cases where a single process produces objects with similar forms but heterogeneous behaviors. I introduce object spaces as a tool to tackle this challenging diversity of biological objects in terms of causal processes with well-defined formal properties. Object spaces have three primary components: (1) a combinatorial biological process such as protein synthesis that generates objects (...) with parts that are modular, independent, and organized according to an invariant syntax; (2) a notion of “distance” that relates the objects according to rules of change over time as found in nature or useful for algorithms; (3) mapping functions defined on the space that map its objects to other spaces or apply an evaluative criterion to measure an important quality, such as parsimony or biochemical function. Once defined, an object space can be used to represent and simulate the dynamics of phenomena on multiple scales; it can also be used as a tool for predicting higher-order properties of the objects, including stitching together series of causal processes. Object spaces are the basis for a strategy of theorizing, discovery, and analysis in biology: as heuristic idealizations of biology, they help us transform inchoate, intractable problems into articulated, well-structured ones. Developing an object space is a research strategy with a long, successful history under many other names, and it offers a unifying but not overreaching approach to biological theory. (shrink)

The concept of hierarchical organization is commonplace in science. Subatomic particles compose atoms, which compose molecules; cells compose tissues, which compose organs, which compose organisms; etc. Hierarchical organization is particularly prominent in ecology, a field of research explicitly arranged around levels of ecological organization. The concept of levels of organization is also central to a variety of debates in philosophy of science. Yet many difficulties plague the concept of discrete hierarchical levels. In this paper, we show how these difficulties undermine (...) various implications ascribed to hierarchical organization, and we suggest the concept of scale as a promising alternative to levels. Investigating causal processes at different scales offers a way to retain a notion of quasi-levels that avoids the difficulties inherent in the classic concept of hierarchical levels of organization. Throughout, our focus is on ecology, but the results generalize to other invocations of hierarchy in science and philosophy of science. (shrink)

Humans are capable of understanding an incredible variety of actions performed by other humans. Even though these range from primary biological actions, like eating and fleeing, to acts in parliament or in poetry, humans generally can make sense of each other’s actions. Understanding other people’s actions is called action understanding, and it can transcend differences in race, gender, culture, age, and social and historical circumstances. Action understanding is the cognitive ability to make sense of another person’s action by integrating perceptual (...) information about the behavior with knowledge about the immediate and sociocultural contexts of the action and with one’s own experience. Scholars are increasingly dissatisfied with monodisciplinary approaches to understanding human action. Such one-sidedness can rest upon various motives. For example, “hermeneutic interpretations” of action understanding tend to emphasize historical and cultural influences while overlooking that ultimately such influences depend upon individual cognitive processes. This has provoked criticism of the corresponding assumption that humans are born as a “blank slate” and that culture is solely responsible for all cognitive contents. However, such critique in turn easily slides into an overemphasis on the biology of human nature and a denial of sociocultural influences on cognition (Pinker, 2003). Fortunately, recent interdisciplinary endeavors have shown that an interdisciplinary approach is preferable when investigating complex functions like action understanding. The purpose of this chapter is to propose a “mechanism-based explanation” of action understanding that will provide a theoretical framework for integrating various and often conflicting disciplinary insights. (shrink)

Philosophical accounts of emergence have been explicated in terms of logical relationships between statements (derivation) or static properties (function and realization). Jaegwon Kim is a modern proponent. A property is emergent if it is not explainable by (or reducible to) the properties of lower level components. This approach, I will argue, is unable to make sense of the kinds of emergence that are widespread in scientific explanations of complex systems. The standard philosophical notion of emergence posits the wrong dichotomies, confuses (...) compositional physicalism with explanatory physicalism, and is unable to represent the type of dynamic processes (self-organizing feedback) that both generate emergent properties and express downward causation. (shrink)

Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.

Most philosophical accounts of emergence are incompatible with reduction. Most scientists regard a system property as emergent relative to properties of its parts if it depends upon their mode of organization-a view consistent with reduction. Emergence is a failure of aggregativity, in which ``the whole is nothing more than the sum of its parts''. Aggregativity requires four conditions, giving powerful tools for analyzing modes of organization. Differently met for different decompositions of the system, and in different degrees, the structural conditions (...) can provide evaluation criteria for choosing decompositions, ``natural kinds'', and detecting functional localization fallacies, approximations, and various biases of vulgar reductionisms. This analysis of emergence and use of these conditions as heuristics is consistent with a broader reductionistic methodology. (shrink)

Ecological neutral theory has been controversial as an alternative to niche theory for explaining community structure. Neutral theory, which explains community structure in terms of ecological drift, is frequently charged with being unrealistic, but commentators have usually not provided an account of theory or model realism. In this paper, I propose a framework for comparing the “realism” or accuracy of alternative theories within a domain with respect to the extent to which the theories abstract and idealize. Using this framework I (...) argue, contrary to most previous commentators, that neutral and niche theories are similarly realistic. Realism cannot provide a basis for accepting or rejecting either type of theory; instead, community ecologists should continue working with a plurality of models. While theoretical unification may become possible, we should treat a plurality of complementary, partial models as the expected situation within community ecology. (shrink)

Argues that truth, moral right, political right, and aesthetic value may be understood as arising out of a naturalist account of humanity, if naturalism is rightly conceived.

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

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

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

The Galilean explanatory style is characterized by the search for the underlying structure of phenomena, the positing of "deep" explanatory principles, and a view of the relation between theory and data, on which the search for "crucial data" is of primary importance. In this paper, I trace the dynamics of adopting the Galilean style, focusing on the science of episodic memory. I argue that memory systems, such as episodic and semantic memory, were posited as underlying competences producing the observable phenomena (...) of memory. Considered in idealized isolation from other systems, episodic memory was taken to underlay the ability of individuals to remember events from their personal past. Yet, in reality, memory systems regularly interact, standing in many-to-many relations to actual memory tasks and experiences. Upon this backdrop, I explore a puzzle about the increasing prominence of the notion of autonoetic consciousness in Tulving's theory of episodic memory. I argue that, contrary to widespread belief, the prominence is not best explained by the purported essential link between autonoetic consciousness and episodic memory. Rather, it is explained by the fact that autonoetic consciousness, hypothesized to uniquely accompany episodic retrieval, was considered a source of crucial data, predictable only from theories positing a functionally distinct episodic memory system. However, with the emergence of a new generation of theories, positing wider memory systems for remembering and imagination, the question of the relation between episodic memory and autonoetic consciousness has been reopened. This creates a pressing need for de-idealization, triggering a new search for crucial data. (shrink)

I examine error diagnosis (model-model disagreement) in climate model intercomparisons including its difficulties, fruitful examples, and prospects for streamlining error diagnosis. I suggest that features of climate model intercomparisons pose a more significant challenge for error diagnosis than do features of individual model construction and complexity. Such features of intercomparisons include, e.g., the number of models involved, how models from different institutions interrelate, and what scientists know about each model. By considering numerous examples in the climate modeling literature, I distill (...) general strategies (e.g., employing physical reasoning and using dimension reduction techniques) used to diagnose model error. Based on these examples, I argue that an error repertoire could be beneficial for improving error diagnosis in climate modeling, although constructing one faces several difficulties. Finally, I suggest that the practice of error diagnosis demonstrates that scientists have a tacit-yet-working understanding of their models which has been under-appreciated by some philosophers. (shrink)

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

The recent literature on causality has seen the introduction of several distinctions within causality, which are thought to be important for understanding the widespread scientific practice of focusing causal explanations on a subset of the factors that are causally relevant for a phenomenon. Concepts used to draw such distinctions include, among others, stability, specificity, proportionality, or actual-difference making. In this contribution, I propose a new distinction that picks out an explanatorily salient class of causes in biological systems. Some select causes (...) in complex biological systems, I argue, have the property of enabling coherent causal control of these systems. Examples of such control variables include hormones and other signaling molecules, e.g., TOR (target of rapamycin), morphogens or the products of homeotic selector genes in embryonic pattern formation. I propose an analysis of this notion based on concepts borrowed from causal graph theory. (shrink)

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