COVID-19 has substantially affected our lives during 2020. Since its beginning, several epidemiological models have been developed to investigate the specific dynamics of the disease. Early COVID-19 epidemiological models were purely statistical, based on a curve-fitting approach, and did not include causal knowledge about the disease. Yet, these models had predictive capacity; thus they were used to ground important political decisions, in virtue of the understanding of the dynamics of the pandemic that they offered. This raises a philosophical question about (...) how purely statistical models can yield understanding, and if so, what the relationship between prediction and understanding in these models is. Drawing on the model that was developed by the Institute of Health Metrics and Evaluation, we argue that early epidemiological models yielded a modality of understanding that we call descriptive understanding, which contrasts with the so-called explanatory understanding which is assumed to be the main form of scientific understanding. We spell out the exact details of how descriptive understanding works, and efficiently yields understanding of the phenomena. Finally, we vindicate the necessity of studying other modalities of understanding that go beyond the conventionally assumed explanatory understanding. (shrink)

The US Food and Drug Administration (FDA) is fraught with controversies over the role of values and politics in regulatory science, especially with drugs in the realm of reproductive health. Philosophers and science studies scholars have investigated the ways in which social context shapes medical knowledge through value judgments, and feminist scholars and activists have criticized sexism and injustice in reproductive medicine. Nonetheless, there has been no systematic study of values and gender norms in FDA drug regulation. I focus on (...) three questions about values in regulatory science. First, how have societal values and gender norms shaped the way that the FDA regulates drugs in the realm of reproductive health, specifically with drug labels? Second, what are the ethical, epistemic, and social consequences of these influences on regulation for women and other marginalized groups? Third, which societal values and gender norms ought to influence drug regulation about reproductive health, and how ought this happen? Integrating philosophical analysis with historical archival research and in-depth interviews, I conduct three case studies of drug labeling about reproductive health: (1) the “drug fact” about the mechanism of the morning-after pill; (2) the package inserts for patients about the health risks of oral contraceptives; and (3) the special physician labels made for prescribing drugs to pregnant women. I identify three challenges for the FDA and suggest ways to reduce the influence of sexist values and facilitate feminist alternatives. First, across these cases, I have found that there are many ways in which other concerns in reproductive medicine (such as zygotic life, fetal health, and population control) have devalued women’s health. Second, both knowledge and ignorance xvi about their reproductive health have contributed to women’s oppression, especially poor women and women of color. Finally, by avoiding the epistemic dimensions of ethics, powerful, mostly male parties in medicine (such as doctors, pharmaceutical companies, and religious institutions) have misused “informed consent,” “religious freedom,” and “paternalism” for unethical purposes. For improvement, I suggest extracting sexist values and gender norms from regulatory science that cause epistemic injustices, and I point to success stories for reforming sexism with feminism at the FDA. (shrink)

In this paper, I draw a parallel between the stability of physical systems and that of economic ones, such as the US financial system. I argue that the use of equilibrium assumptions is central to the analysis of dynamic behavior for both kinds of systems, and that we ought to interpret such idealizing strategies as footholds for causal exploration and explanation. Our considerations suggest multi-scale modeling as a natural home for such reasoning strategies, which can provide a backdrop for the (...) assessment and prevention of financial crises. Equilibrium assumptions are critical elements of the epistemic scaffolding that make up multi-scale models, which we should understand as a means of constructing explanations of dynamic behavior. (shrink)

In the recent literature on explanation in biology, increasing attention is being paid to the connection between design explanation and mechanistic explanation, viz. the role of design principles and heuristics for mechanism discovery and mechanistic explanation. In this paper we extend the connection between design explanation and mechanism discovery by prizing apart two different types of design explanation and by elaborating novel heuristics that one specific type offers for mechanism discovery across species. We illustrate our claims in terms of two (...) lines of biological research on the biological advantages of organismal traits, one on the eye-size of giant squid, the other on foraging habits of specific bat species. We argue that this research illustrates useful heuristics for mechanism discovery across species, viz. reasoning strategies to infer likely mechanisms for a certain biological role based on assessments of the environmental conditions in which the role is performed efficiently and less or in-efficiently. We bring out the novel features of our analysis in terms of a comparison with mechanistic approaches to mechanism discovery, amongst which graph-theoretical ones, and by comparing the different types of design explanation and the discovery heuristics they support. (shrink)

Although the analogy between macroscopic machines and biological molecular devices plays an important role in the conceptual framework of both neo-mechanistic accounts and nanotechnology, it has recently been claimed that certain complex molecular devices cannot be considered machines since they are subject to physicochemical forces that are different from those of macroscopic machines. However, the structural and physicochemical conditions that allow both macroscopic machines and microscopic devices to work and perform new functions, through a combination of elemental functional parts, have (...) not yet been examined. In order to fill this void, this paper has a threefold aim: first, to clarify the structural and organisational conditions of macroscopic machines and microscopic devices; second, to determine whether the machine-like analogy fits nanoscale devices; and third, to assess whether the machine-like analogy is appropriate for describing the behaviour of some biological macromolecules. Finally, the paper gives an account of ‘machine’ which, while acknowledging the physicochemical and organisational differences between man-made machines and biological microscopic devices, nevertheless identifies a common conceptual core that allows us to consider the latter ‘machines’. (shrink)

When cognitive scientists are looking for the neural basis of consciousness or the computational processes underlying vision, what are they looking to find? I argue for a new account of this explanatory project in cognitive science (and the special sciences more generally) on which it is best understood on close analogy with causal explanation in the special sciences. Causal explanations cite causal difference-makers: they explain how certain events causally depend on other events. Generative explanations cite generative difference-makers: they explain how (...) certain events obtain in virtue of (and so are generated by) other events. I show how that this generative difference-making account (GDM) extends well regarded developments in philosophical work on causal explanation, helps to usefully clarify and expands the hypothesis space of a key project in cognitive science – that of understanding how underlying nonmental processes give rise to the mental, including consciousness. In section 2, I develop GDM by close analogy with causal explanation, and locate both of them as species of a more general project in the special sciences: that of discovering what makes a difference to what. In section 3, I motivate GDM by contrasting it with other rival accounts, including correlationist, identity, and grounding accounts, as well as Carl Craver’s constitutive relevance account. In section 4, I tie all of the strands of the preceding discussion together to show how GDM provides a new and compelling response to the so-called hard problem of consciousness. (shrink)

Explanations of biological phenomena such as cell division, protein synthesis or circadian rhythms commonly take the form of models of the responsible mechanisms. Recently philosophers of science have attempted to analyze this practice, presenting mechanisms as organized collections of parts performing operations that together produce the phenomenon. But in some cases what researchers seek to explain is not a general phenomenon, but a specific feature of a more fine-grained phenomenon. In some of these cases, it is not the model of (...) the mechanism that performs the explanatory work. I consider a case in which the investigator offered an abstract representation of a fine-grained phenomenon to show why in had the feature in question. I consider a second case in which a researcher abstracted from the mechanism to identify a design principle that explains why the functioning mechanism exhibits a specific feature. (shrink)

We address the question of whether and to what extent explanatory and modelling strategies in systems biology are mechanistic. After showing how dynamic mathematical models are actually required for mechanistic explanations of complex systems, we caution readers against expecting all systems biology to be about mechanistic explanations. Instead, the aim may be to generate topological explanations that are not standardly mechanistic, or to arrive at design principles that explain system organization and behaviour in general, but not specific mechanisms. These abstraction (...) strategies serve various aims, including prediction and control, that are central to understanding the epistemic diversity of systems biology. (shrink)

This paper describes a pattern of explanation prevalent in the biological sciences that I call a ‘lineage explanation’. The aim of these explanations is to make plausible certain trajectories of change through phenotypic space. They do this by laying out a series of stages, where each stage shows how some mechanism worked, and the differences between each adjacent stage demonstrates how one mechanism, through minor modifications, could be changed into another. These explanations are important, for though it is widely accepted (...) that there is an ‘incremental constraint’ on evolutionary change, in an important class of cases it is difficult to see how to satisfy this constraint. I show that lineage explanations answer important questions about evolutionary change, but do so by demonstrating differences between individuals rather than invoking population processes, such as natural selection.1. Introduction2. Turning a ‘Scale’ into a ‘Plume’3. Lineage Explanations in Biology3.1. The evolution of eyes3.2. The evolution of feathers4. The Two Dimensions of a Lineage Explanation4.1. The production dimension4.2. The continuity dimension4.3. The dual role of the parts5. Constraining the Explanations6. Operational and Generative Lineages7. Explaining Change Without Populations8. Conclusion. (shrink)

Chronobiology, especially the study of circadian rhythms, provides a model scientific field in which philosophers can study how investigators from a variety of disciplines working at different levels of organization are each contributing to a multi-level account of the responsible mechanism. I focus on how the framework of mechanistic explanation integrates research designed to decompose the mechanism with efforts directed at recomposition that relies especially on computation models. I also examine how recently the integration has extended beyond basic research to (...) the processes through which the disruption of circadian rhythms contributes to disease, including various forms of cancer. Understanding these linkages has been facilitated by discoveries about how circadian mechanisms interact with mechanisms involved in other physiological processes, including the cell cycle and the immune system. (shrink)

According to the Russo-Williamson Thesis, causal claims in the health sciences need to be supported by both difference-making and mechanistic evidence. In this article, we attempt to determine whether Evidence-based Medicine can be improved through the consideration of mechanistic evidence. We discuss the practical composition and function of each RWT evidence type and propose that exposure-outcome evidence provides associations that can be explained through a hypothesis of causation, while mechanistic evidence provides finer-grained associations and knowledge of entities that ultimately explains (...) a causal hypothesis. We suggest that mechanistic evidence holds untapped potential to add value to the assessment of evidence quality in EBM and propose initial recommendations for the integration of mechanistic and exposure-outcome evidence to improve EBM by robustly leveraging available evidence in support of good medical decisions. (shrink)

Causal claims in biomedical contexts are ubiquitous albeit they are not always made explicit. This paper addresses the question of what causal claims mean in the context of disease. It is argued that in medical contexts causality ought to be interpreted according to the epistemic theory. The epistemic theory offers an alternative to traditional accounts that cash out causation either in terms of “difference-making” relations or in terms of mechanisms. According to the epistemic approach, causal claims tell us about which (...) inferences (e.g., diagnoses and prognoses) are appropriate, rather than about the presence of some physical causal relation analogous to distance or gravitational attraction. It is shown that the epistemic theory has important consequences for medical practice, in particular with regard to evidence-based causal assessment. (shrink)

In this article I tackle the question of how the hierarchical order of mechanisms can be represented within a causal graph framework. I illustrate an answer to this question proposed by Casini, Illari, Russo, and Williamson and provide an example that their formalism does not support two important features of nested mechanisms: (i) a mechanism’s submechanisms are typically causally interacting with other parts of said mechanism, and (ii) intervening in some of a mechanism’s parts should have some influence on the (...) phenomena the mechanism brings about. Finally, I sketch an alternative approach taking (i) and (ii) into account. (shrink)

Research on computational models of scientific discovery investigates both the induction of descriptive laws and the construction of explanatory models. Although the work in law discovery centers on knowledge‐lean approaches to searching a problem space, research on deeper modeling tasks emphasizes the pivotal role of domain knowledge. As an example, our own research on inductive process modeling uses information about candidate processes to explain why variables change over time. However, our experience with IPM, an artificial intelligence system that implements this (...) approach, suggests that process knowledge is insufficient to avoid consideration of implausible models. To this end, the discovery system needs additional knowledge that constrains the model structures. We report on an extended system, SC‐IPM, that uses such information to reduce its search through the space of candidates and to produce models that human scientists find more plausible. We also argue that although people carry out less extensive search than SC‐IPM, they rely on the same forms of knowledge—processes and constraints—when constructing explanatory models. (shrink)

Mechanistic philosophy of science views a large part of scientific activity as engaged in modelling mechanisms. While science textbooks tend to offer qualitative models of mechanisms, there is increasing demand for models from which one can draw quantitative predictions and explanations. Casini et al. (Theoria 26(1):5–33, 2011) put forward the Recursive Bayesian Networks (RBN) formalism as well suited to this end. The RBN formalism is an extension of the standard Bayesian net formalism, an extension that allows for modelling the hierarchical (...) nature of mechanisms. Like the standard Bayesian net formalism, it models causal relationships using directed acyclic graphs. Given this appeal to acyclicity, causal cycles pose a prima facie problem for the RBN approach. This paper argues that the problem is a significant one given the ubiquity of causal cycles in mechanisms, but that the problem can be solved by combining two sorts of solution strategy in a judicious way. (shrink)

This paper sets out to analyze how causation works by focusing on biology, as represented by epidemiology and by scientific information on how the body works (“physiology”). It starts by exploring the specificity of evolved physiological systems, in which evolutionary, developmental and proximal causes all fit together, and the concept of function is meaningful; in contrast, this structure does not apply in epidemiology (or outside biology). Using these two contrasting branches of biology, I examine the role both of mechanism and (...) of difference making in causation. I find that causation necessarily involves both mechanism and difference making, and that they play complementary roles. Both are seen as ontologically necessary, even if the evidence is not always available for both. Influential monist accounts that focus on one of these, at the expense of ignoring the other, are found to be inadequate on these and on other grounds. Recent attempts to combine them are reviewed, notably that of Russo and Williamson (Int Stud Philos Sci 21:157–170, 2007), and it is argued that their epistemic view requires there to be a source of the different types of evidence that a rational agent would consider, and that this source must be ontic. I then analyze how causal relationships work in evolved physiological systems and in those studied by epidemiology, with a particular focus on how mechanism interacts with input. Finally, I consider this concept of causation from the perspective of everyday language, and of its possible generalisability outside biology. (shrink)

In this paper, I evaluate recently defended mechanistic accounts of the unity of neuroscience from a metaphysical point of view. Considering the mechanistic framework in general , I argue that explanations of this kind are essentially reductive . The reductive character of mechanistic explanations provides a sufficiency criterion, according to which the mechanism underlying a certain phenomenon is sufficient for the latter. Thus, the concept of supervenience can be used in order to describe the relation between mechanisms and phenomena . (...) Against this background, I show that the mechanistic framework is subject to the causal exclusion problem and faces the classical metaphysical options when it comes to the relations obtaining between different levels of mechanisms . Finally, an attempt to improve the metaphysics of mechanisms is made and further difficulties are pointed out. (shrink)

We contrast reactive and endogenously active perspectives on brain activity. Both have been pursued continuously in neurophysiology laboratories since the early 20thcentury, but the endogenous perspective has received relatively little attention until recently. One of the many successes of the reactive perspective was the identification, in the second half of the 20th century, of the distinctive contributions of different brain regions involved in visual processing. The recent prominence of the endogenous perspective is due to new findings of ongoing oscillatory activity (...) in the brain at a wide range of time scales, exploiting such techniques as single-cell recording, EEG, and fMRI. We recount some of the evidence pointing to ways in which this endogenous activity is relevant to cognition and behavior. Our major objective is to consider certain implications of the contrast between the reactive and endogenous perspectives. In particular, we relate these perspectives to two different characterizations of explanation in the new mechanistic philosophy of science. In a basic mechanistic explanation, the operations of a mechanism are characterized qualitatively and as functioning sequentially until a terminating condition is realized. In contrast, a dynamic mechanistic explanation allows for non-sequential organization and emphasizes quantitative modeling of the mechanisms's behavior. For example, with appropriate parameter values a set of differential equations can be used to demonstrate ongoing oscillations in a system organized with feedback loops. We conclude that the basic conception of mechanistic explanation is adequate for reactive accounts of brain activity, but dynamical accounts are required to explain sustained, endogenous activity. (shrink)

The concept of technical function is a key concept to describe technical artifacts and artifacts-to-be-designed. Engineers often give such descriptions in terms of functional decomposition models, which represent relationships between functions and sets of other functions. Despite the importance of the concept of function there is no consensus among engineers about its meaning. Models of functional decomposition are likewise conceptually divergent. Although this conceptual diversity hampers information exchange between engineers, they accept and maintain it. Engineers do not, by and large, (...) engage in a focused debate to establish commonly shared functional conceptualizations. This contrasts with science where both debates on the adequacy of key conceptualizations and convergence toward shared conceptualizations are common. This book investigates the side-by-side usage of different functional decomposition models in engineering. It explains this phenomenon by applying and extending the analysis of theory choice in terms of methodological incommensurability to engineering functional decomposition, rather than to science. This analysis shows that engineers’ usage of competing functional decomposition models is rational from a practical point of view. This book furthermore investigates the communication problems that the side-by-side usage of different models engenders and presents a strategy that supports the exchange and re-use of functional information between engineers. (shrink)

In this paper, we compare the mechanisms of protein synthesis and natural selection. We identify three core elements of mechanistic explanation: functional individuation, hierarchical nestedness or decomposition, and organization. These are now well understood elements of mechanistic explanation in fields such as protein synthesis, and widely accepted in the mechanisms literature. But Skipper and Millstein have argued that natural selection is neither decomposable nor organized. This would mean that much of the current mechanisms literature does not apply to the mechanism (...) of natural selection.We take each element of mechanistic explanation in turn. Having appreciated the importance of functional individuation, we show how decomposition and organization should be better understood in these terms. We thereby show that mechanistic explanation by protein synthesis and natural selection are more closely analogous than they appear—both possess all three of these core elements of a mechanism widely recognized in the mechanisms literature. (shrink)

This paper discusses three shortcomings of the current state of the debate regarding historical evidence against scientific realism. Attending to these issues will direct the debate away from over-generalising wholesale arguments.

Laws in the special sciences are usually regarded to be non-universal. A theory of laws in the special sciences faces two challenges. (I) According to Lange's dilemma, laws in the special sciences are either false or trivially true. (II) They have to meet the ?requirement of relevance?, which is a way to require the non-accidentality of special science laws. I argue that both challenges can be met if one distinguishes four dimensions of (non-) universality. The upshot is that I argue (...) for the following explication of special science laws: L is a special science law just if (1) L is a system law, (2) L is quasi-Newtonian, and (3) L is minimally invariant. (shrink)

The mechanistic perspective has dominated biological disciplines such as biochemistry, physiology, cell and molecular biology, and neuroscience, especially during the 20th century. The primary strategy is reductionist: organisms are to be decomposed into component parts and operations at multiple levels. Researchers adopting this perspective have generated an enormous body of information about the mechanisms of life at scales ranging from the whole organism down to genetic and other molecular operations.

Philosophers of the social sciences are increasingly convinced that macro-and micro-explanations are complementary. Whereas macro-explanations are broad, micro-explanations are deep. I distinguish between weak and strong complementarity: Strongly complementary explanations improve one another when integrated, weakly complementary explanations do not. To demonstrate the explanatory autonomy of different levels of explanation, explanatory pluralists mostly presuppose the weak form of complementarity. By scrutinizing the notions of explanatory depth and breadth, I argue that macro- and micro-accounts of the same phenomenon are more often (...) strongly complementary. This invites a revision of the pluralist position in which integration promotes explanatory progress. Key Words: explanatory pluralism • social science • explanatory depth • explanatory breadth • mechanism. (shrink)

Most contemporary philosophers of mind claim to be in search of a 'naturalistic' theory. However, when we look more closely, we find that there are a number of different and even conflicting ideas of what would count as a 'naturalization' of the mind. This article attempts to show what various naturalistic philosophies of mind have in common, and also how they differ from one another. Additionally, it explores the differences between naturalistic philosophies of mind and naturalisms found in ethics, epistemology, (...) and philosophy of science. Section 1 introduces a distinction between two types of project that have been styled 'naturalistic', which I call philosophical naturalism and empirical naturalism . Sections 2 to 6 canvass different strands of philosophical naturalism concerning the mind, followed by a much briefer discussion of attempts to provide empirical naturalizations of the mind in Section 7 . Section 8 concludes the essay with a consideration of the relations between philosophical and empirical naturalism in philosophy of mind, arguing that at least some types of philosophical naturalism are incompatible with empirical naturalism. (shrink)

From its genesis in the 1960s, the focus of inquiry in neuroscience has been on the cellular and molecular processes underlying neural activity. In this pursuit neuroscience has been enormously successful. Like any successful scientific inquiry, initial successes have raised new questions that inspire ongoing research. While there is still much that is not known about the molecular processes in brains, a great deal of very important knowledge has been secured, especially in the last 50 years. It has also attracted (...) the attention of a number of philosophers, some of whom have viewed it as evidence for a ruthlessly reductionistic program that will eventually explain how mental processes are performed in the brain in purely molecular terms. As neuroscience developed, however, there emerged a smaller group of researchers who focused on systems, behavioral, and cognitive neuroscience. These investigators have also made impressive advances in the last 50 years and they have been the focus of an even larger group of philosophers, who have appealed to systems level understanding of the brain as providing the appropriate point of connection to the information processing accounts advanced in psychology. (shrink)

The topic of mechanistic explanation in neuroscience has been a subject of recent discussion. There is a lot of interest in understanding what these explanations involve. Furthermore, there is disagreement about whether neurological mechanisms themselves should be viewed as reductionist in nature. In this paper I will explain how these two issues are related. I will, first, describe how mechanisms support a form of antireductionism. This is because the mechanisms that exist should be seen as involving part-whole relations, where the (...) behavior of a whole is more than the sum of its parts. After this, I will consider mechanistic explanations and how they can be understood. While some people think the explanations concern existing entities in the world, I will argue that we can understand the explanations by viewing them in terms of arguments. Despite the fact that it is possible to understand mechanistic explanations in this manner, the antireductionist point remains. (shrink)

I examine some behavioural and heuristic models of individual decision-making and argue that the diverse psychological mechanisms these models posit are too demanding to be implemented, either consciously or unconsciously, by actual decision makers. Accordingly, and contrary to what their advocates typically claim, behavioural and heuristic models are best understood as ‘as-if’ models. I then sketch a version of scientific antirealism that justifies the practice of as-if modelling in decision theory but goes beyond traditional instrumentalism. Finally, I relate my account (...) of decision models to the recent controversy about mentalism versus behaviourism, reject both positions, and offer an alternative view. (shrink)

The so-called integration problem concerning mechanistic and computational explanation asks how they are related to each other. One approach is that a computational explanation is a species of mechanistic explanation. According to this view, computational or mathematical descriptions are mechanism sketches or macroscopic descriptions that include computationally relevant and exclude computationally irrelevant physical properties. Some suggest that this results in a so-called single hierarchy view of physical computation, where computational or mathematical properties sit together in the same mechanistic hierarchy with (...) the implementational properties. This view can be contrasted with a separate hierarchy view, according to which computational and physical descriptions have their own hierarchies which are related to each other via a bridging implementation relation. The single hierarchy view has been criticized for downplaying the explanatory value of computational explanations and not being hospitable to multiple realization of cognitive processes. In this paper, I argue that the aforementioned criticisms fail, and there might be a deeper problem with the single hierarchy view, which is that the single hierarchy view might collapse into a separate hierarchy view. The kind of abstraction used by the single hierarchy view does not seem to grant mathematical or computational descriptions but only more stripped physical or implementational descriptions. (shrink)

Descriptive abstraction means omission of information from descriptions of phenomena. In this paper, I introduce a distinction between vertical and horizontal descriptive abstraction. Vertical abstracts away levels of mechanism or organization, while horizontal abstracts away details within one level of organization. The distinction is implicit in parts of the literature, but it has received insufficient attention and gone mainly unnoticed. I suggest that the distinction can be used to clarify how computational descriptions are formed in some variants of the mechanistic (...) account of physical computation. Furthermore, I suggest that, if this suggestion is adopted, it can be used to resolve what I call abstraction, hierarchy, and generality problems raised against mechanistic account of physical computation. According to the abstraction problem, the mechanistic account of physical computation is conceptually confused in claiming that physical systems process computational, abstract properties. An existing solution distinguishes between descriptive and metaphysical abstraction, suggesting that the abstraction problem unnecessarily postulates metaphysically abstract entities. The solution has been criticized for leading to what I call hierarchy and generality problems: it results in two separate hierarchies, one physical and one computational, making it problematic both to account for the generality of computational descriptions and to specify how the two hierarchies are related to each other. Adopting the vertical-horizontal distinction and the view that computational descriptions are achieved by horizontal abstraction allows one to account for the generality of computational descriptions, and to form a single hierarchy in which there are no separate hierarchies in need of integration. (shrink)

In this paper we investigate how inference to the best explanation (IBE) works in engineering science, focussing on the context of malfunction explanation. While IBE has gotten a lot of attention in the philosophy of science literature, few, if any, philosophical work has focussed on IBE in engineering science practice. We first show that IBE in engineering science has a similar structure as IBE in other scientific domains in the sense that in both settings IBE hinges on the weighing of (...) explanatory virtues. We then proceed to show that, due to the intimate connection between explanation and redesign in engineering science, there is a further engineering domain-specific virtue in terms of which engineering malfunction explanations are evaluated, viz. the virtue of redesign utility. This virtue entails that the explanatory information offered by a malfunction explanation should be instrumental in predicting counterfactual dependencies in redesigned systems. We illustrate and elaborate these points in terms of a number of engineering examples, focussing in particular on the 2009 crash of Air France Flight 447. Our extension of analyses of IBE and explanation to engineering science practice offers new insights by identifying a new explanatory virtue in malfunction explanation: redesign utility. (shrink)

Resumen En el marco de la filosofía de la mente, este artículo aborda el problema de la causación mental en el proyecto naturalista biológico de John Searle. A partir de la concepción de la mente como un fenómeno emergente de procesos cerebrales, evalúo las críticas que Jaegwon Kim realiza a la eficacia causal de la consciencia, centrándome en los argumentos de sobredeterminación y violación del principio de clausura físico causal. Luego analizo el debate de la causación mental a partir de (...) los descubrimientos de Benjamin Libet respecto a la existencia de actividad neuronal pre-consciente en la conducta motora voluntaria. Dicha actividad, llamada potencial de preparación, junto a la noción de causación trabajada en neurociencia, avala la eficacia causal de los estados mentales, pero en un sentido distinto al propuesto por Searle.Within the framework of philosophy of mind, this paper addresses the problem of mental causation in John Searle's biological naturalist project. Beginning with the conception of the mind as a phenomenon emerging from cerebral processes, I evaluate the criticisms that Jaegwon Kim makes to the causal efficacy of consciousness, focusing on the arguments of overdetermination and violation of the principle of physical causal closure. Then, I analyze the debate on mental causation from the findings of Benjamin Libet regarding the existence of pre-conscious neural activity in voluntary motor behavior. This activity, called readiness potential, and the notion of causation worked in neuroscience, support the causal efficacy of mental states, but in a different sense from that proposed by Searle. (shrink)

Building on an overview of dual systems theories in behavioural economics, the paper presents a methodological assessment in terms of the mechanistic explanations framework that has gained prominence in philosophy of the neurosciences. I conclude that they fail to meet the standards of causal explanations and I suggest an alternative ‘dual functions’ view based on Marr’s methodology of computational neuroscience. Recent psychological and neuroscience research undermines the case for a categorization of brain processes in terms of properties such as relative (...) speed. I defend an interpretation of dualities as functional, without assigning them to specific neurophysiological structures. (shrink)

Marcello Barbieri has presented code biology as an alternative to the Peircean approach to biosemiotics. Some critics questioned the viability of code biology on grounds that Barbieri’s conception of science is limited. It has been argued that code biology’s mechanistic tendency is the cause of the allegedly limited conception of science. In this paper, I evaluate the scientific viability of the code model from the perspective of scientific realism in the philosophy of science. To be more precise, I draw on (...) resources of the mechanistic view in philosophy to argue that far from harbouring a limited conception of science, code biology could indeed improve the scientific prospects of biosemiotics. I show that the mechanistic and model-based tendency of the code model enhances its vigour as a full-blooded scientific approach to the study of meaning in living systems. To consolidate my claim, I draw on some recent debates in the mechanistic philosophy to argue that even relational approaches to understanding the meaning in living systems—such as an approach that is defended by Vega in a recent paper—could be underpinned by mechanistic processes at a foundational level. (shrink)

Diagrams can serve as representational models in scientific research, yet important questions remain about how they do so. I address some of these questions with a historical case study, in which diagrams were modified extensively in order to elaborate an early hypothesis of protein synthesis. The diagrams’ modelling role relied mainly on two features: diagrams were modified according to syntactic rules, which temporarily replaced physico-chemical reasoning, and diagram-to-target inferences were based on semantic interpretations. I then explore the lessons for the (...) relative roles of syntax, semantics, external marks, and mental images, for justifying diagram-to-target inferences, and for the “artefactual approach” to scientific models. (shrink)

Explanations are supposed to provide us with understanding. It is common to make a distinction between genuine, scientific understanding, and the phenomenological, or ‘aha’ notion of understanding, where the former is considered epistemically relevant, the latter irrelevant. I argue that there is a variety of phenomenological understanding that does play a positive epistemic role. This phenomenological understanding involves a similarity between bodily sensations that is used as evidence for mechanistic hypotheses. As a case study, I will consider 17th and 18th (...) century research into the mechanism behind the electric eel’s power to shock. Se supone que las explicaciones nos dotan de comprensión. Es habitual hacer una distinción entre compresión cientifica, genuina, y la noción fenomenológica, o ‘ahá’, de comprensión, donde la primera se considera epistemológicamente relevante y esta última irrelevante. Argumento que hay un tipo de compresión fenomenológica que sí juega un papel positivo epistémico. Esta comprensión epistemológica conlleva cierta semejanza con las sensaciones corporales que se usan como evidencia de algunas hipótesis mecanicistas. Como caso de estudio, consideraré la investigación en los siglos xvii y xviii del mecanismo tras la capacidad de la anguila eléctrica para provocar un shock. (shrink)

In many fields of biology, both the phenomena to be explained and the mechanisms proposed to explain them are commonly presented in diagrams. Our interest is in how scientists construct such diagrams. Researchers begin with evidence, typically developed experimentally and presented in data graphs. To arrive at a robust diagram of the phenomenon or the mechanism, they must integrate a variety of data to construct a single, coherent representation. This process often begins as the researchers create a first sketch, and (...) it continues over an extended period as they revise the sketch until they arrive at a diagram they find acceptable. We illustrate this process by examining the sketches developed in the course of two research projects directed at understanding the generation of circadian rhythms in cyanobacteria. One identified a new aspect of the phenomenon itself, whereas the other aimed to develop a new mechanistic account. In both cases, the research resulted in a paper in which the conclusion was presented in a diagram that the authors deemed adequate to convey it. These diagrams violate some of the normative “cognitive design principles” advanced by cognitive scientists as constraints on successful visual communication. We suggest that scientists’ sketching is instead governed by norms of success that are broadly explanatory: conveying the phenomenon or mechanism. (shrink)

Studying astroparticle physics sheds new light on scientific explanation and on the ways in which cosmology is empirically underdetermined or not. Astroparticle physics extends the empirical domain of cosmology from purely astronomical data to “multi-messenger astrophysics”, i.e., measurements of all kinds of cosmic rays including very high energetic gamma rays, neutrinos, and charged particles. My paper investigates the ways in which these measurements contribute to cosmology and compares them with philosophical views about scientific explanation, the relation between theory and data, (...) and scientific realism. The “standard models” of cosmology and particle physics lack of unified foundations. Both are “piecemeal physics” in Cartwright's sense, but contrary to her metaphysics of a “dappled world” the work in both fields of research aims at unification. Cosmology proceeds “top-down”, from models to data and from large scale to small-scale structures of the universe. Astroparticle physics proceeds “bottom-up”, from data taking to models and from subatomic particles to large-scale structures of the universe. In order to reconstruct the causal stories of cosmic rays and the nature of their sources, several pragmatic unifying strategies are employed. Standard views about scientific explanation and scientific realism do not cope with these “bottom-up” strategies and the way in which they contribute to cosmology. In addition it has to be noted that the shift to “multi-messenger astrophysics” transforms the relation between cosmological theory and astrophysical data in a mutually holistic way. (shrink)

It is argued that once biological systems reach a certain level of complexity, mechanistic explanations provide an inadequate account of many relevant phenomena. In this article, I evaluate such claims with respect to a representative programme in systems biological research: the study of regulatory networks within single-celled organisms. I argue that these networks are amenable to mechanistic philosophy without need to appeal to some alternate form of explanation. In particular, I claim that we can understand the mathematical modelling techniques of (...) systems biologists as part of a broader practice of constructing and evaluating mechanism schemas. This argument is elaborated by considering the case of bacterial chemotactic networks, where some research has been interpreted as explaining phenomena by means of abstract design principles. (shrink)

This article examines two theses formulated by Russo and Williamson in their study of causal inference in the health sciences. The two theses are assessed against evidence from a specific case in the social sciences, i.e., research on the institutional determinants of the aggregate unemployment rate. The first Russo–Williamson Thesis is that a causal claim can only be established when it is jointly supported by difference-making and mechanistic evidence. This thesis is shown not to hold. While researchers in my case (...) study draw extensively on both types of evidence, one causal claim out of the three analyzed is established even though it is exclusively supported by mechanistic evidence. The second Russo–Williamson Thesis is that standard accounts of causality fail to handle the dualist epistemology highlighted in the first Thesis. I argue that a counterfactual-manipulationist account of causality—which is endorsed by many philosophers as well as many social scientists—can perfectly make sense of the typical strategy in my case study to draw on both difference-making and mechanistic evidence; it is just an instance of the common strategy of increasing evidential variety. (shrink)