This work addresses biological explanations and aims to provide a philosophical account which brings together logical-procedural and historical-processual aspects when considering molecular pathways. It is argued that, having molecular features as explananda, a particular non-classical logical language – Zsyntax – can be used to formally represent, in terms of logical theorems, types of molecular processes, and to grasp how we get from one molecular interaction to another, hence explaining why a given outcome occurs. Expressing types of molecular biology processes in (...) terms of the Zsyntax language allows us to represent causal interactions by taking into account their context-sensitivity, and amounts to partly reviving the spirit of the so-called received view of explanation – which aimed to capture scientific explanatory accounts in terms of their logical structure and their appealing to nomological relations. Such a partial revival is pursued by invoking here non-classical deductions and empirical generalisations, which are called to provide the epistemic norms to explain the behavior of molecular pathways. (shrink)

El lenguaje incorporado desde y para la cognición incorporada fundamenta el origen del lenguaje en la evolución de la especie humana y en los contornos de la estructura cerebral actual del hombre. En el cerebro hay continuidad: las áreas sensoriales reciben estímulos, a los que se pone la voz, propio de la especie, y se produce el lenguaje conceptual; sobre esta base se abstrae los términos y se llega a niveles de alta abstracción. Así se da razón que la dimensión (...) lingüística es la facultad que articula lo sustancial de la facultad fonética humana, con los elementos del ambiente. Por lo tanto, se rechaza las explicaciones lingüísticas tanto del internalismo como las del externalismo, que absolutizan sea la facultad o la periferia respectivamente. (shrink)

This paper explores multiple experimental interventions in molecular biology. By “multiple,” we mean that molecular biologists often use different modes of experimental interventions in a series of experiments for one and the same subject. In performing such a series of experiment, scientists may use different modes of interventions to realize plural goals such as testing given hypotheses and exploring novel phenomena. In order to illustrate this claim, we develop a framework of multiple modes of experimental interventions to analyze a series (...) of experiments for a single subject. Our argument begins with a brief characterization of Craver and Darden’s taxonomy of experiments, because the taxonomy they have made implies various modes of interventions. We propose to extract two interventional directions and two interventional effects from their taxonomy as the basis of classification. The vertical or inter-level direction means that an intervention is performed between different levels of organization and the horizontal or inter-stage direction means that an intervention is performed between different stages of a mechanism. Interventions may produce an excitatory or an inhibitory effect. As a consequence, we can classify modes of interventions according to different directions and effects. We illustrate our claims by doing a case study of the PaJaMo experiment, which is a series of experiments for a single subject. The final goal in this paper is to provide a taxonomy of characteristics of experimentation in which the PaJaMo experiment is adequately located. (shrink)

Scientific explanation is an important goal of scientific practise. Philosophers have proposed a striking diversity of seemingly incompatible accounts of explanation, from deductive-nomological to statistical relevance, unification, pragmatic, causal-mechanical, mechanistic, causal intervention, asymptotic, and model-based accounts. In this dissertation I apply two novel methods to reexamine our evidence about scientific explanation in practise and thereby address the fragmentation of philosophical accounts. I start by collecting a data set of 781 articles from one year of the journal Science. Using automated text (...) mining techniques I measure the frequency and distribution of several groups of philosophically interesting words, such as "explain", "cause", "evidence", "theory", "law", "mechanism", and "model". I show that "explain" words are much more common in scientific writing than in other genres, occurring in roughly half of all articles, and that their use is very often qualified or negated. These results about the use of words complement traditional conceptual analysis. Next I use random samples from the data set to develop a large number of small case studies across a wide range of scientific disciplines. I use a sample of "explain" sentences to develop and defend a new general philosophical account of scientific explanation, and then test my account against a larger set of randomly sampled sentences and abstracts. Five coarse categories can classify the explanans and explananda of my cases: data, entities, kinds, models, and theories. The pair of the categories of the explanans and explanandum indicates the "form" of an explanation. The explain-relation supports counterfactual reasoning about the dependence of qualities of the explanandum on qualities of the explanans. But for each form there is a different "core relation" between explanans and explanandum that supports the explain-relation. Causation, modelling, and argument are the core relations for different forms of scientific explanation between different categories of explanans and explananda. This flexibility allows me to resolve some of the fragmentation in the philosophical literature. I provide empirical evidence to show that my general philosophical account successfully describes a wide range of scientific practise across a large number of scientific disciplines. (shrink)

Analytical categories of scientific cultures have typically been used both exclusively and universally. For instance, when styles of scientific research are employed in attempts to understand and narrate science, styles alone are usually employed. This article is a thought experiment in interweaving categories. What would happen if rather than employ a single category, we instead investigated several categories simultaneously? What would we learn about the practices and theories, the agents and materials, and the political-technological impact of science if we analyzed (...) and applied styles, paradigms, and models simultaneously? I address these questions in general and for a specific case study: a brief history of systematics. (shrink)

This chapter draws an analogy between computing mechanisms and autopoietic systems, focusing on the non-representational status of both kinds of system (computational and autopoietic). It will be argued that the role played by input and output components in a computing mechanism closely resembles the relationship between an autopoietic system and its environment, and in this sense differs from the classical understanding of inputs and outputs. The analogy helps to make sense of why we should think of computing mechanisms as non-representational, (...) and might also facilitate reconciliation between computational and autopoietic/enactive approaches to the study of cognition. (shrink)

Ever since Wesley Salmon’s theory, the mechanical approach to causality has found an increasing number of supporters who have developed it in different directions. Mechanical views such as those advanced by Stuart Glennan, Jim Bogen and Peter Machamer, Lindley Darden and Carl Craver have met with broad consensus in recent years. This paper analyses the main features of these mechanical positions and some of the major problems they still face, referring to the latest debate on mechanisms, causal explanation and the (...) relationship between mechanisms and counterfactuals. I shall claim that the mechanical approach can be recognised as having a fundamental explanatory power, whereas the counterfactual approach, recently developed mainly by Jim Woodward and essentially linked to the notion of intervention, has an important heuristic role. Claiming that mechanisms are by no means to be seen as parasitic on counterfactuals or less fundamental than them – as it has been recently suggested –, and that yet counterfactuals can play a part in a conceptual analysis of causation, I shall look for hints in support of the peaceful coexistence of the two. (shrink)

In this thesis, I give a metascientific account of causality in medicine. I begin with two historical cases of causal discovery. These are the discovery of the causation of Burkitt’s lymphoma by the Epstein-Barr virus, and of the various viral causes suggested for cervical cancer. These historical cases then support a philosophical discussion of causality in medicine. This begins with an introduction to the Russo- Williamson thesis (RWT), and discussion of a range of counter-arguments against it. Despite these, I argue (...) that the RWT is historically workable, given a small number of modifications. I then expand Russo and Williamson’s account. I first develop their suggestion that causal relationships in medicine require some kind of evidence of mechanism. I begin with a number of accounts of mechanisms and produce a range of consensus features of them. I then develop this consensus position by reference to the two historical case studies with an eye to their operational competence. In particular, I suggest that it is mechanistic models and their representations which we are concerned with in medicine, rather than the mechanism as it exists in the world. -/- I then employ these mechanistic models to give an account of the sorts of evidence used in formulating and evaluating causal claims. Again, I use the two human viral oncogenesis cases to give this account. I characterise and distinguish evidence of mechanism from evidence of difference-making, and relate this to mechanistic models. I then suggest the relationship between types of evidence presents us with a means of tackling the reference-class problem. This sets the scene for the final chapter. Here, I suggest the manner in which these two different classes of evidence become integrated is also reflected in the way that developing research programmes change as their associated causal claims develop. (shrink)

The concept of mechanism in biology has three distinct meanings. It may refer to a philosophical thesis about the nature of life and biology (‘mechanicism’), to the internal workings of a machine-like structure (‘machine mechanism’), or to the causal explanation of a particular phenomenon (‘causal mechanism’). In this paper I trace the conceptual evolution of ‘mechanism’ in the history of biology, and I examine how the three meanings of this term have come to be featured in the philosophy of biology, (...) situating the new ‘mechanismic program’ in this context. I argue that the leading advocates of the mechanismic program (i.e., Craver, Darden, Bechtel, etc.) inadvertently conflate the different senses of ‘mechanism’. Specifically, they all inappropriately endow causal mechanisms with the ontic status of machine mechanisms, and this invariably results in problematic accounts of the role played by mechanism-talk in scientific practice. I suggest that for effective analyses of the concept of mechanism, causal mechanisms need to be distinguished from machine mechanisms, and the new mechanismic program in the philosophy of biology needs to be demarcated from the traditional concerns of mechanistic biology. (shrink)

This chapter provides an introduction to the study of the philosophical notions of mechanisms and causality in biology and economics. This chapter sets the stage for this volume, Mechanism and Causality in Biology and Economics, in three ways. First, it gives a broad review of the recent changes and current state of the study of mechanisms and causality in the philosophy of science. Second, consistent with a recent trend in the philosophy of science to focus on scientific practices, it in (...) turn implies the importance of studying the scientific methods employed by researchers. Finally, by way of providing an overview of each chapter in the volume, this chapter demonstrates that biology and economics are two fertile fields for the philosophy of science and shows how biological and economic mechanisms and causality can be synthesized. (shrink)

Philosophical discussions of biological classification have failed to recognise the central role of homology in the classification of biological parts and processes. One reason for this is a misunderstanding of the relationship between judgments of homology and the core explanatory theories of biology. The textbook characterisation of homology as identity by descent is commonly regarded as a definition. I suggest instead that it is one of several attempts to explain the phenomena of homology. Twenty years ago the ‘new experimentalist’ movement (...) in philosophy of science drew attention to the fact that many experimental phenomena have a ‘life of their own’: the conviction that they are real is not dependent on the theories used to characterise and explain them. I suggest that something similar can be true of descriptive phenomena, and that many homologies are phenomena of this kind. As a result the descriptive biology of form and function has a life of its own—a degree of epistemological independence from the theories that explain form and function. I also suggest that the two major ‘homology concepts’ in contemporary biology, usually seen as two competing definitions, are in reality complementary elements of the biological explanation of homology. (shrink)

Philosophers of science have often favoured reductive approaches to how-possibly explanation. This article identifies three alternative conceptions making how-possibly explanation an interesting phenomenon in its own right. The first variety approaches “how possibly X?” by showing that X is not epistemically impossible. This can sometimes be achieved by removing misunderstandings concerning the implications of one’s current belief system but involves characteristically a modification of this belief system so that acceptance of X does not result in contradiction. The second variety offers (...) a potential how-explanation of X. It is usually followed by a range of further potential how-explanations of the same phenomenon. In recent literature the factual claims implied by the second variety have been downplayed whereas the heuristic role of mapping the space of conceptual possibilities has been emphasized. I will focus especially on this truth-bracketing sense of potentiality when looking closer at the second variety in the paper. The third variety has attracted less interest. It presents a partial how-explanation of X. Typically it aims to establish the existence of a mechanism by which X could be and was generated. The third conception stands out as the natural alternative for the advocate of ontic how-possibly explanations. This article transfers Salmon’s view that explanation-concepts can be broadly divided into epistemic, modal, and ontic to the context of how-possibly explanations. Moreover, it is argued that each of the three above-mentioned varieties of how-possibly explanation occurs in science. To recognize this may be especially relevant for philosophers. We are often misled by the promises of various why-explanation accounts, and seem to have forgotten nearly everything about the diversity of how-possibly explanations. (shrink)

An increasing number of philosophers have promoted the idea that mechanism provides a fruitful framework for thinking about the explanatory contributions of computational approaches in cognitive neuroscience. For instance, Piccinini and Bahar :453–488, 2013) have recently argued that neural computation constitutes a sui generis category of physical computation which can play a genuine explanatory role in the context of investigating neural and cognitive processes. The core of their proposal is to conceive of computational explanations in cognitive neuroscience as a subspecies (...) of mechanistic explanations. This paper identifies several challenges facing their mechanistic account and sketches an alternative way of thinking about the epistemic roles of computational approaches used in the study of brain and cognition. Drawing on examples from both low-level and systems-level computational neuroscience, I argue that at least some computational explanations of neural and cognitive processes are partially independent from mechanistic constraints. (shrink)

Robots are being extensively used for the purpose of discovering and testing empirical hypotheses about biological sensorimotor mechanisms. We examine here methodological problems that have to be addressed in order to design and perform “good” experiments with these machine models. These problems notably concern the mapping of biological mechanism descriptions into robotic mechanism descriptions; the distinction between theoretically unconstrained “implementation details” and robotic features that carry a modeling weight; the role of preliminary calibration experiments; the monitoring of experimental environments for (...) disturbing factors that affect both modeling features and theoretically unconstrained implementation details of robots. Various assumptions that are gradually introduced in the process of setting up and performing these robotic experiments become integral parts of the background hypotheses that are needed to bring experimental observations to bear on biological mechanism descriptions. (shrink)

Machamer, Darden, and Craver's account of the nature and role of mechanisms in the special sciences has been very influential. Unfortunately, a confusing array of ontic, epistemic, and pragmatic distinctions is required to individuate their mechanisms, mechanism schemata, and mechanism sketches. I diagnose this as a conflation of token-level causal relations with type-level relations. I propose instead that a mechanism is an abstraction that relates entity types and activity types on the model of a directed graph. Mechanisms have an ontic (...) status distinct from the causal chains of token entities and token activities that instantiate them. (shrink)