This paper is about mechanisms and models, and how they interact. In part, it is a response to recent discussion in philosophy of biology regarding whether natural selection is a mechanism. We suggest that this debate is indicative of a more general problem that occurs when scientists produce mechanistic models of populations and their behaviour. We can make sense of claims that there are mechanisms that drive population-level phenomena such as macroeconomics, natural selection, ecology, and epidemiology. But talk of mechanisms (...) and mechanistic explanation evokes objects with well-defined and localisable parts which interact in discrete ways, while models of populations include parts and interactions that are neither local nor discrete in any actual populations. This apparent tension can be resolved by carefully distinguishing between the properties of a model and those of the system it represents. To this end, we provide an analysis that recognises the flexible relationship between a mechanistic model and its target system. In turn, this reveals a surprising feature of mechanistic representation and explanation: it can occur even when there is a mismatch between the mechanism of the model and that of its target. Our analysis reframes the debate, providing an alternative way to interpret scientists’ mechanism-talk , which initially motivated the issue. We suggest that the relevant question is not whether any population-level phenomenon such as natural selection is a mechanism, but whether it can be usefully modelled as though it were a particular type of mechanism. (shrink)

In this paper, I examine the comparatively neglected intuition of production regarding causality. I begin by examining the weaknesses of current production accounts of causality. I then distinguish between giving a good production account of causality and a good account of production. I argue that an account of production is needed to make sense of vital practices in causal inference. Finally, I offer an information transmission account of production based on John Collier’s work that solves the primary weaknesses of current (...) production accounts: applicability and absences. (shrink)

Epigenetics investigates the dynamics of gene expression in various cells, and the signals from the internal and external environment affecting these dynamics. Neuroepigenetics extends this research into neurons and glia cells. Environmental-induced changes in gene expression are not only associated with the emerging structure and function of the nervous system during ontogeny, but are also fundamental to the wiring of neural circuitries responsible for learning and memory. Yet philosophers of science and neuroscience have so far paid little attention to these (...) findings. In this article, we describe some recent experimental work on the neuroepigenetics of fear and stress responses in rodents, its ingenious experimental translation into humans, and how this work seems not to be accurately described by popular “mechanist” accounts. Our final goal is to motivate broader philosophical attention to neuroepigenetics practices and findings, especially for how it considers environmentally driven and developmental plasticity in psychological explanations. (shrink)

The Russo Williamson thesis (RWT) states that a causal claim can be established only if it can be established that there is a difference-making relationship between the cause and the effect, and that there is a mechanism linking the cause and the effect that is responsible for such a difference-making relationship (Russo & Williamson, 2007). The applicability of Russo and Williamson’s idea was hugely debated in relation to biomedical research, and recently it has been applied to the social sciences (Shan (...) & Williamson, 2021). While many philosophers and social scientists have advocated the use of different kinds of evidence for causal discoveries, others have criticised this approach. With this paper, I aim to defend RWT from criticisms and to show its importance in the social sciences. The paper is structured as follows. After a brief introduction, in Sect. 2, I will summarise RWT, and in Sect. 3 I will describe how this approach can be applied to the social sciences. In Sect. 4, I will reconstruct two main criticisms of this thesis proposed in the philosophy of the social sciences literature: namely (i) RWT is not used in the social sciences, (ii) RWT does not work. For each criticism I will provide a defence of RWT. My defence will be based on two general considerations: (i) RWT appears perfectly in line with the research methods used in the social sciences and (ii) RWT can be applied successfully to establish causal claims. In Sect. 5, moreover, I will examine the causal accounts that have motivated such criticisms and I will argue that they should be rejected to endorse RWT and a causal account able to accommodate the current use of mechanistic and difference-making evidence in the social sciences. Section 6 will conclude with a note on the relevance of RWT in both its descriptive and normative form. (shrink)

Alexander Gebharter has recently proposed to use Bayesian network causal discovery methods to identify the constitutive dependencies that underwrite mechanistic explanations. The proposal depends on using the assumptions of the causal Bayesian network framework to implicitly define mechanistic constitution as a kind of deterministic direct causal dependence. The aim of this paper is twofold. In the first half, we argue that Gebharter’s proposal incurs severe conceptual problems. In the second half, we present an alternative way to bring Bayesian network tools (...) to bear on the issue of understanding mechanistic constitution. More precisely, our proposal interprets constitution as the relation explaining why a target phenomenon has its characteristic causal role in terms of the causal roles of some of its spatiotemporal parts---where the notion of causal role is probabilistically understood. (shrink)

Phyllis Illari and Jon Williamson propose a formulation for a general mechanistic account, the purpose of which is to capture the similarities across mechanistic accounts in the sciences. Illari and Williamson extract insight from mechanisms in astrophysics—which are notably different from the typical biological mechanisms discussed in the literature on mechanisms—to show how their general mechanistic account accommodates mechanisms across various sciences. We present argumentation that demonstrates why an amendment is necessary to the ontology referred to by the general mechanistic (...) account provided by Illari and Williamson. The amendment is required due to the variability of some components in computing mechanisms: the very same component serves as either entity or activity, both between levels and within the same level of the explanatory hierarchy. We argue that the proper ontological account of these mechanistic components involves disambiguation via explicitly indexing them as entities or activities. (shrink)

In this article, I develop an account of the use of intentional predicates in cognitive neuroscience explanations. As pointed out by Maxwell Bennett and Peter Hacker, intentional language abounds in neuroscience theories. According to Bennett and Hacker, the subpersonal use of intentional predicates results in conceptual confusion. I argue against this overly strong conclusion by evaluating the contested language use in light of its explanatory function. By employing conceptual resources from the contemporary philosophy of science, I show that although the (...) use of intentional predicates in mechanistic explanations sometimes leads to explanatorily inert claims, intentional predicates can also successfully feature in mechanistic explanations as tools for the functional analysis of the explanandum phenomenon. Despite the similarities between my account and Daniel Dennett's intentional-stance approach, I argue that intentional stance should not be understood as a theory of subpersonal causal explanation, and therefore cannot be used to assess the explanatory role of intentional predicates in neuroscience. Finally, I outline a general strategy for answering the question of what kind of language can be employed in mechanistic explanations. (shrink)

It is a widespread assumption in philosophy of science that data is what is explained by theory—that data itself is not explanatory. I draw on instances of representational and explanatory practice from mammalian chronobiology to suggest that this assumption is unsustainable. In many instances, biologists employ representations of data in explanatory ways that are not reducible to constraints on or evidence for representations of mechanisms. Data graphs are used to exemplify relationships between quantities in the mechanism, and often these representations (...) are necessary for explaining particular aspects of the phenomena under study. I argue that this kind of representation is distinct from representing laws or generalizations, and its primary purpose is to convey particular types or patterns of quantitative relationships. The benefit of the analysis is two-fold. First, it provides a more accurate account of explanatory practice in broadly mechanistic analysis in biology. Second, it suggests that there is not an explanatory “fundamental” type of representation in biology. Rather, the practice of explanation consists in the construction of different types of representations and their employment for distinct explanatory purposes. (shrink)

I propose a cautionary assessment of the recent debate concerning the impact of the dynamical approach on philosophical accounts of scientific explanation in the cognitive sciences and, particularly, the cognitive neurosciences. I criticize the dominant mechanistic philosophy of explanation, pointing out a number of its negative consequences: In particular, that it doesn’t do justice to the field’s diversity and stage of development, and that it fosters misguided interpretations of dynamical models’ contribution. In order to support these arguments, I analyze a (...) case study in computational neuroethology and show why it should not be understood through a mechanistic lens; I specially focus on Zednik’s mechanistic interpretation of the case study. In addition, I argue for a greater appreciation of the relation between explanation and other epistemic goals in the field, as well as an increased sensitivity towards the associated contextual factors. (shrink)

Volume 32, Issue 1, March 2019, Page 69-72.

Se critican dos tesis de Nancy Cartwright. Por un lado, se examina el enfoque de las “capacidades” en el campo de lo económico para argumentar que estas responden a la lógica de los “árboles de posibilidades” o resultados de final abierto; por el otro, se ofrece una alternativa al problema de “sobre-restricción” de los modelos económicos para mostrar cómo el gran número de supuestos auxiliares acota las posibilidades de extrapolar las conclusiones obtenidas en el modelo a condiciones distintas de las (...) explicitadas en él. Se muestra la utilidad del análisis de robustez para descubrir las condiciones esenciales que cierran el árbol de posibilidades. (shrink)

In the recent philosophical literature, two questions have arisen concerning the status of natural selection: (1) Is it a population-level phenomenon, or is it an organism-level phenomenon? (2) Is it a causal process, or is it a purely statistical summary of lower-level processes? In an earlier work (Millstein, Br J Philos Sci, 57(4):627–653, 2006), I argue that natural selection should be understood as a population-level causal process, rather than a purely statistical population-level summation of lower-level processes or as an organism-level (...) causal process. In a 2009 essay entitled “Productivity, relevance, and natural selection,” Stuart Glennan argues in reply that natural selection is produced by causal pro- cesses operating at the level of individual organisms, but he maintains that there is no causal productivity at the population level. However, there are, he claims, many population-level properties that are causally relevant to the dynamics of evolution- ary processes. Glennan’s claims rely on a causal pluralism that holds that there are two types of causes: causal production and causal relevance. Without calling into question Glennan’s causal pluralism or his claims concerning the causal relevance of natural selection, I argue that natural selection does in fact exhibit causal production at the population level. It is true that natural selection does not fit with accounts of mechanisms that involve decomposition of wholes into parts, such as Glennan’s own. However, it does fit with causal production accounts that do not require decomposition, such as Salmon’s Mark Transmission account, given the extent to which populations act as interacting “objects” in the process of natural selection. (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 the increasing body of metatheoretical literature on "causal mechanisms," definitions of "mechanism" proliferate, and these increasingly divergent definitions reproduce older theoretical and methodological oppositions. The reason for this proliferation is the incompatibility of the various metatheoretical expectations directed to them: (1) to serve as an alternative to the scientific theory of individual behavior (for some social theorists, most notably Jon Elster); (2) to provide solutions for causal inference problems in the quantitative social sciences, in social history, and in the (...) (3) qualitative research context; and (4) to serve as an alternative for narratives (Charles Tilly). Mechanisms can do (1) only as under-specified law-like regularities, deliver (2) as robust generative processes represented by models, and accomplish (3) as fragile generative processes (stories), but these are not all compatible. (edited). (shrink)

Gebharter has proposed using one of the best known Bayesian network causal discovery algorithms, PC, to identify the constitutive dependencies underwriting mechanistic explanations. His proposal assumes that mechanistic constitution behaves like deterministic direct causation, such that PC is directly applicable to mixed variable sets featuring both causal and constitutive dependencies. Gebharter claims that such mixed sets, under certain restrictions, comply with PC’s background assumptions. The aim of this article is to show that Gebharter’s proposal incurs severe problems, ultimately rooted in (...) the widespread non-compliance of mechanistic systems with PC’s assumptions. This casts severe doubts on the attempt to implicitly define constitution as a form of deterministic direct causation complying with PC’s assumptions. (shrink)

There is a perennial philosophical dream of a certain natural order for the natural kinds. The name of this dream is ‘the hierarchy requirement’. According to this postulate, proper natural kinds form a taxonomy which is both unique and traditional. Here I demonstrate that complex scientific objects exist: objects which generate different systems of scientific classification, produce myriad legitimate alternatives amongst the nonetheless still natural kinds, and make the hierarchical dream impossible to realize, except at absurdly great cost. Philosophical hopes (...) for a certain order in nature cannot be fulfilled. Natural kinds crosscut one another, ubiquitously so, and this crosscutting spells the end of the hierarchical dream. (shrink)

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

Las corrientes manipulabilistas tradicionales consideran que una implementación de política efectiva debe estar fundamentada en un conocimiento invariante. Este modo de pensamiento está basado en el supuesto ontológico de que existen factores causales estables tanto en las ciencias naturales como en las sociales. También asumen que un sólo tipo de intervención ex-ante es pertinente para una implementación efectiva. En el presente artículo se realizará una crítica a estos enfoques. En particular, se mostrará que los procesos sociales responden a una lógica (...) de “árboles de posibilidades” o “resultados de final abierto”. Sobre la base de esta variante ontológica se argumentará que más que un conocimiento de factores invariantes, el sustento de una buena política debe buscarse en los condicionamientos explicitados dentro de un anteproyecto y en la factibilidad de que los mismos se satisfagan en el sistema objetivo. Asimismo, se mostrará cómo las típicas intervenciones ex-ante no son adecuadas en el reino de lo social. Contrario a ellos, las intervenciones deberán ser sistemáticas. (shrink)

Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...) clarify how functionalism and computationalism may or may not legitimately come together. (shrink)

What are scientific theories and how should they be represented? In this article, I propose a causal–structural account, according to which scientific theories are to be represented as sets of interrelated causal and credal nets. In contrast with other accounts of scientific theories (such as Sneedian structuralism, Kitcher’s unificationist view, and Darden’s theory of theoretical components), this leaves room for causality to play a substantial role. As a result, an interesting account of explanation is provided, which sheds light on explanatory (...) unification within a causalist framework. The theory of classical genetics is used as a case study. 1 Introduction2 The Theory of Classical Genetics3 Three Philosophical Accounts of the Theory of Classical Genetics3.1 The structuralist account3.2 Kitcher’s unificationism3.3 Darden and theory change in science4 A Common Lacuna: Where is Causality?5 Woodward’s Interventionist Account of Causation6 Causal Bayes Nets and Their Interrelations6.1 Causal Bayes nets6.2 Relations among causal nets6.3 Credal nets and their interrelations7 The Theory of the Gene and its Causal Graph8 A First Exemplar: Stem Length in Pea Plants8.1 Three crosses on stem length in pea plants8.2 The causal graph for stem length in pea plants8.3 Morgan’s explanatory principles and the credal net for stem length in pea plants9 Explaining Mendel’s Crosses: A Causal–Structural Account10 Monohybrid Crosses with Complete Dominance11 Exemplars,Explanatory Patterns, Generic Credal Nets, and Mechanism Schemas12 Incomplete Dominance13 Anomalies14 Multi-hybrid Crosses with Independent Assortment15 Multi-hybrid Crosses with Linkage and Crossing-Over16 Double Crossing-Over and the Linear Order of the Gene17 Causal–Structural Explanation18 Explanatory Unification19 Concluding Remarks. (shrink)

Understanding the role mechanistic constraints play in shaping evolution can relieve the tension between the generally accepted intuition that there are no strict laws in biology and empirical findings showing that evolutionary processes are biased toward preferred outcomes. Mechanistic constraints explain why some evolutionary outcomes are more probable than others and allow for predictions in specific lineages. At the same time, mechanistic constraints are neither necessary nor universal in the way laws are traditionally characterized: they remain contingent on the past (...) evolution of the biological mechanisms underpinning them and only constrain the future evolution of the organisms possessing them. (shrink)

In this paper we argue that in recent literature on mechanistic explanations, authors tend to conflate two distinct features that mechanistic models can have or fail to have: plausibility and richness. By plausibility, we mean the probability that a model is correct in the assertions it makes regarding the parts and operations of the mechanism, i.e., that the model is correct as a description of the actual mechanism. By richness, we mean the amount of detail the model gives about the (...) actual mechanism. First, we argue that there is at least a conceptual reason to keep these two features distinct, since they can vary independently from each other: models can be highly plausible while providing almost no details, while they can also be highly detailed but plainly wrong. Next, focusing on Craver's continuum of ?how-possibly,? to ?how-plausibly,? to ?how-actually? models, we argue that the conflation of plausibility and richness is harmful to the discussion because it leads to the view that both are necessary for a model to have explanatory power, while in fact, richness is only so with respect to a mechanism's activities, not its entities. This point is illustrated with two examples of functional models. (shrink)

Mechanisms are a way of explaining how biological phenomena work rather than why single elements of biological systems are there. However, mechanisms are usually described as physiological entities, and little or no attention is paid to malfunction as an independent theoretical concept. On the other hand, malfunction is the main focus of interest of applied sciences such as medicine. In this paper I argue that malfunctions are parts of pathological mechanisms, which should be considered separate theoretical entities, conceptually having a (...) priority over physiological sequences. While pathological mechanisms can be described in terms of a Cummins-like mechanistic explanation, they show some unnoticed peculiarities when compared to physiological ones. Some features of pathological mechanisms are considered, such as outcome variability, ambivalence and dependence on a range. (shrink)

Most philosophical accounts of causation take causal relations to obtain between individuals and events in virtue of nomological relations between properties of these individuals and events. Such views fail to take into account the consequences of the fact that in general the properties of individuals and events will depend upon mechanisms that realize those properties. In this paper I attempt to rectify this failure, and in so doing to provide an account of the causal relevance of higher-level properties. I do (...) this by critiquing one prominent model of higher-level properties—Kim’s functional model of reduction—and contrasting it with a mechanistic approach to higher-level properties and causation. (shrink)

Among philosophers of science, there is now a widespread agreement that the DN model of explanation is poorly equipped to account for explanations in biology. Rather than identifying laws, so the consensus goes, researchers explain biological capacities by constructing a model of the underlying mechanism.We think that the dichotomy between DN explanations and mechanistic explanations is misleading. In this article, we argue that there are cases in which biological capacities are explained without constructing a model of the underlying mechanism. Although (...) these explanations do not conform to Hempel’s DN model, they do invoke more or less stable generalisations. Because they invoke generalisations and have the form of an argument, we call them inferential explanations. We support this claim by considering two examples of explanations of biological capacities: pigeon navigation and photoperiodism. Next, we will argue that these non-mechanistic explanations are crucial to biology in three ways: sometimes, they are the only thing we have, they are heuristically useful, and they provide genuine understanding and so are interesting in their own right.In the last sections we discuss the relation between types of explanations and types of experiments and situate our views within some relevant debates on explanatory power and explanatory virtues. (shrink)

The main models of scientific explanation assume the need for some kind of stable knowledge for assembling a good explanatory argument. While these approaches are useful in the natural sciences, it is doubtful that they are similarly applicable in the socioeconomic realm. In this paper it is expected to show that the logic of socioeconomic processes of being "possibility trees" or "open-ended results" makes regularities the exception rather than the rule. Alternatively, a mode of explanation that focuses on contextual factors (...) and people actions is proposed. Los principales modelos de explicación científica asumen la necesidad de utilizar algún tipo de conocimiento estable para el armado de un buen argumento explicativo. Si bien estos enfoques son muy útiles en las ciencias naturales, es dudoso que sean similarmente aplicables en el reino de lo socioeconómico. En el presente trabajo se prevé mostrar que la lógica de los “árboles de posibilidades” o “resultados de final abierto” propias de los procesos socioeconómicos hace que las regularidades sean más la excepción que la regla. Como alternativa, se propone un modo de explicación que focalice en los factores contextuales y en las acciones de las personas en el momento en que aconteció el fenómeno a explicar. (shrink)

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. (shrink)

In this article, I present two conceptual problems for Craver's mutual manipulability account of constitutive relevance in mechanisms. First, constitutive relevance threatens to imply causal relevance despite Craver (and Bechtel)'s claim that they are strictly distinct. Second, if (as is intuitively appealing) parthood is defined in terms of spatio-temporal inclusion, then the mutual manipulability account is prone to counterexamples, as I show by a case of endosymbiosis. I also present a methodological problem (a case of experimental underdetermination) and formulate two (...) partial, but fallible solutions based on the notions of parthood and synchronicity. (shrink)

Causal mediation mechanisms are well supported by available experimental evidence and provide a practicable way to reductive physicalism. According to the causal mediation account of mechanistic explanation, descriptions as diverse as ‘black-box’ phenomena, mechanistic sketches and schemas mixing physically interpreted and operationalized biological, psychological and social variables, and detailed descriptions of mechanisms refer to the same causal structure circumscribed within the spatiotemporal boundaries of a replicable experimental setup. The coreference of coarser- and finer-grained descriptions of causal structures opens new possibilities (...) for testing the reductive physicalism conjecture. I discuss experimental designs supporting the causal mediation account and show how recent studies demonstrating the biological mediation of mind-mind causal processes can provide evidence for reductive physicalism. (shrink)

During the past two decades, philosophers of biology have increasingly turned their attention to mechanisms of biological phenomena. Through analyses of mechanistic proposals advanced by biologists, the goal of these philosophers is to understand what a mechanism is and how mechanisms explain. These analyses have generally focused on mechanistic proposals for phenomenon that occur at the cellular or sub-cellular level, such as synapse firing, protein synthesis, or metabolic pathway operation. Little is said about the mechanisms of the macromolecular reactions that (...) underpin these phenomena. These reactions comprise a diverse family of reaction types, and include protein folding, macromolecular complex formation, receptor-ligand interactions, and enzyme catalysis. In this paper, I develop an account of mechanism that focuses exclusively on macromolecular reactions. I begin by reviewing how mechanism is understood in enzymology, and how mechanistic concepts of enzymology apply to macromolecular reactions in general. We will see that the mechanism of a macromolecular reaction is most accurately described as a progression of reaction intermediates, where the evolution of intermediates, from one to the next, is characterized by an energetic coupling between chemistry and protein dynamics. I then make the case that this description necessitates a grounding in a process ontology. To describe the mechanism by which a macromolecular reaction occurs is to describe a process. (shrink)

This article reconsiders the theoretical role of the genetic code. By drawing on published and unpublished sources from the 1950s, I analyse how the code metaphor was actually employed by the scientists who first promoted its use. The analysis shows that the term ‘code’ picked out mechanism sketches, consisting of more or less detailed descriptions of ordinary molecular components, processes, and structural properties of the mechanism of protein synthesis. The sketches provided how-possibly explanations for the ordering of amino acids by (...) nucleic acids. I argue that employing the code metaphor was justified in virtue of its descriptive-denotational and explanatory roles, and because it highlighted a similarity with conventional codes that was particularly salient at the time. 1 Introduction2 Coding Schemes in the 1950s2.1 The research problem: Determining amino acid sequences2.2 The solution: Mapping schemes or ‘codes’3 The Code Metaphor Played Descriptive and Explanatory Roles4 Theness of Codes and the Expendability of the Code Metaphor5 The Role of Arbitrariness6 Conclusions. (shrink)

What has been called the new mechanistic philosophy conceives of mechanisms as the main providers of biological explanation. We draw on the characterization of the p53 gene in molecular oncology, to show that explaining a biological phenomenon implies instead a dynamic interaction between the mechanistic level—rendered at the appropriate degree of ontological resolution—and far more general explanatory tools that perform a fundamental epistemic role in the provision of biological explanations. We call such tools “explanatory frameworks”. They are called frameworks to (...) stress their higher level of generality with respect to bare mechanisms; on the other hand, they are called explanatory because, as we show in this paper, their importance in explaining biological phenomena is not secondary with respect to mechanisms. We illustrate how explanatory frameworks establish selective and local criteria of causal relevance that drive the search for, characterisation and usage of biological mechanisms. Furthermore, we show that explanatory frameworks allow for changes of scientific perspective on the causal relevance of mechanisms going beyond the account provided by the new mechanistic philosophy. (shrink)

A critical review of Frans de Waal's book on evolution of morality (Frans de Waal, Primates and Philosophers: How Morality Evolved, Princeton, NJ: Princeton University Press, 2006).

This paper argues that the form of explanation at issue in the hard problem of consciousness is scientifically irrelevant, despite appearances to the contrary. In particular, it is argued that the 'sense of understanding' that plays a critical role in the form of explanation implicated in the hard problem provides neither a necessary nor a sufficient condition on satisfactory scientific explanation. Considerations of the actual tools and methods available to scientists are used to make the case against it being a (...) necessary condition, and work by J.D. Trout that exploits psychological research on the hindsight and overconfidence biases is used to show that it is not a sufficient condition. It is argued, however, that certain intellectual and moral concerns give us good reason to still try to meet the hard problem's explanatory challenge, despite its extrascientific nature. (shrink)

In this article, two issues regarding mechanisms are discussed. The first concerns the relationships between “mechanism description” and “mechanism explanation.” It is proposed that it is rather plausible to think of them as two distinct epistemic acts. The second deals with the different molecular biology explanatory contexts, and it is shown that some of them require physics and its laws.

This article focuses on the assessment of mechanistic relations with specific attention to medicine, where mechanistic models are widely employed. I first survey recent contributions in the philosophical literature on mechanistic causation, and then take issue with Federica Russo and Jon Williamson’s thesis that two types of evidence, probabilistic and mechanistic, are at stake in the health sciences. I argue instead that a distinction should be drawn between previously acquired knowledge of mechanisms and yet-to-be-discovered knowledge of mechanisms and that both (...) probabilistic evidence and manipulation are essential with respect to newly discovered mechanisms. (shrink)

Cybernetics promoted machine-supported investigations of adaptive sensorimotor behaviours observed in biological systems. This methodological approach receives renewed attention in contemporary robotics, cognitive ethology, and the cognitive neurosciences. Its distinctive features concern machine experiments, and their role in testing behavioural models and explanations flowing from them. Cybernetic explanations of behavioural events, regularities, and capacities rely on multiply realizable mechanism schemata, and strike a sensible balance between causal and unifying constraints. The multiple realizability of cybernetic mechanism schemata paves the way to principled (...) comparisons between biological systems and machines. Various methodological issues involved in the transition from mechanism schemata to their machine instantiations are addressed here, by reference to a simple sensorimotor coordination task. These concern the proper treatment of ceteris paribus clauses in experimental settings, the significance of running experiments with correct but incomplete machine instantiations of mechanism schemata, and the advantage of operating with real machines ??? as opposed to simulated ones ??? immersed in real environments. (shrink)

The aim of this paper is to examine the notion of social mechanisms by comparison with the notions of evolutionary and physical mechanisms. It is argued that social mechanisms are based on trends, and not lawlike regularities, so that social mechanisms are different from mechanisms in the natural sciences. Taking as an example of social causation the abolition of the slave trade, the paper argues that social mechanisms should be incorporated in Weber’s wider notion of adequate causation in order to (...) achieve their explanatory purpose. (shrink)

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2018.