Traditionally, mechanistic reasoning has been assigned a negligible role in standard EBM literature, although some recent authors have argued for an upgrade. Even so, the mechanistic reasoning that has received attention has almost exclusively been positive—both in an epistemic sense of claiming that there is a mechanistic chain and in a health-related sense of there being claimed benefits for the patient. Negative mechanistic reasoning has been neglected, both in the epistemic and in the (...) health-related sense. I distinguish three main types of negative mechanistic reasoning and subsume them under a new definition of mechanistic reasoning in the context of assessing medical interventions. This definition is wider than a previous suggestion in the literature. Each negative type corresponds to a range of evidential strengths, and it is argued that there are differences with respect to typical evidential strengths. The variety of negative mechanistic reasoning should be acknowledged in EBM, and it presents a serious challenge to proponents of so-called medical hierarchies of evidence. (shrink)

A strong case has been made for the role and value of mechanistic reasoning in process-oriented sciences, such as molecular biology and neuroscience. This paper shifts focus to assess the role of mechanistic reasoning in an area where it is neither obvious nor expected: population genetics. Population geneticists abstract away from the causal-mechanical details of individual organisms and, instead, use mathematics to describe population-level, statistical phenomena. This paper, first, develops a framework for the identification of (...) class='Hi'>mechanistic reasoning where it is not obvious: mathematical and mechanistic styles of scientific reasoning. Second, it applies this framework to demonstrate that both styles are integrated in modern investigations of evolutionary biology. Characteristic of the former, applied population genetic techniques provide statistical evidence for associations between genotype, phenotype, and fitness. Characteristic of the latter, experimental interventions provide causal-mechanical evidence for associations between the very same relationships, often in the same model organisms. The upshot is a richer perspective of how evolutionary biologists build evidence for hypotheses regarding adaptive evolution and a general framework for assessing the scope of mechanistic reasoning across the sciences. (shrink)

At least historically, it was common for medical practitioners to believe causal hypotheses on the basis of standalone mechanistic reasoning. However, it is now widely acknowledged that standalone mechanistic reasoning is insufficient for appropriately believing a causal hypothesis in medicine, thanks in part to the so-called problem of masking. But standalone mechanistic reasoning is not the only type of mechanistic reasoning. When exactly then is it appropriate to believe a causal hypothesis on (...) the basis of mechanistic reasoning? In this paper, I argue that it has proved difficult to provide a satisfying answer to this question. I also argue that this difficulty is predicted by recent work in knowledge-first epistemology. I think this shows that recent work in epistemology has important implications for practice in the philosophy of science. It is therefore worth paying closer attention in the philosophy of science to this recent work in knowledge-first epistemology. (shrink)

Evidence‐based medicine (EBM) proponents have argued that mechanistic evidence concerning medical treatments should be considered secondary to evidence derived from randomized controlled trials (RCTs). One common criticism of RCTs is that they often do not yield results that are generalizable to clinical practice, and that for clinical practice application, mechanistic evidence is needed. However, proponents of EBM have argued that mechanistic reasoning is often unreliable and thus not very useful. Here we suggest an important role of (...) mechanistic explanation that has been left out of this discussion entirely, namely, its importance in a patient’s decision of whether or not to take certain drugs. We argue that in certain cases, knowing how a treatment works is just as important for the patient as knowing whether it does. In this paper, we explore how and why giving patients mechanistic information can be an important factor in obtaining informed consent for medical treatment, focusing on the example case of hormonal contraceptives. (shrink)

Philosophers of science have insisted that evidence of underlying mechanisms is required to support claims about the effects of medical interventions. Yet evidence about mechanisms does not feature on dominant evidence-based medicine “hierarchies.” After arguing that only inferences from mechanisms (“mechanistic reasoning”)—not mechanisms themselves—count as evidence, I argue for a middle ground. Mechanistic reasoning is not required to establish causation when we have high-quality controlled studies; moreover, mechanistic reasoning is more problematic than has been (...) assumed. Yet where the problems can be overcome, mechanistic reasoning can and should be used as evidence. (shrink)

In his 1951 Gibbs Lecture Gödel formulates the central implication of the incompleteness theorems as a disjunction: either the human mind infinitely surpasses the powers of any finite machine or there exist absolutely unsolvable diophantine problems (of a certain type). In his later writings in particular Gödel favors the view that the human mind does infinitely surpass the powers of any finite machine and there are no absolutely unsolvable diophantine problems. I consider how one might defend such a view in (...) light of Gödel's remark that one can turn to ideas in Husserlian transcendental phenomenology to show that the human mind ‘contains an element totally different from a finite combinatorial mechanism’. (shrink)

In this paper, I investigate the study of causal mechanisms in the social sciences. I argue that unless one adopts a clear notion of causation, such as Woodward's manipulability theory of causation, one does not find evidence for causal claims. I show that adopting Woodward’s theory entails that a researcher must take into account both the observable implications of the mechanisms, and possible interventions on those mechanisms. In a backlash against the pervasiveness of statistical methods, in the last decade or (...) so social scientists have become more focused on finding the causal mechanisms behind observed correlations. To provide evidence for such causal claims, researchers often rely on process-tracing, a method which involves contrasting the observable implications of several alternative mechanisms. Although process-tracing has gained prominence as a technique, researchers do not share a fundamental framework of what causation is. I will show what process-tracers’ reasoning would look like if they were to commit to Woodward’s manipulability theory. This theory tells us that any successful explanation of an effect must refer to causal factors that could be manipulated to change the phenomenon under study. Specifically, a variable X is a cause of another variable Y if there exists some ‘intervention variable’ I. I is an intervention variable if we can use I to change X, which will then in turn change Y without any interference of other variables linked to Y. In other words, using I we will be able to ascertain that it was X that made the change in Y happen. I will argue that if a process-tracing researcher were to adopt the manipulability notion of causation, she would not only have to find observable implications of the alternative mechanisms under study, but also information regarding an intervention variable for each link of the causal chain. (shrink)

Evidence-based medicine (EBM), the dominant approach to assessing the effectiveness of clinical and public health interventions, focuses on the results of association studies. EBM+ is a development of EBM that systematically considers mechanistic studies alongside association studies. In this paper we provide several examples of the importance of mechanistic evidence to coronavirus research. (i) Assessment of combination therapy for MERS highlights the need for systematic assessment of mechanistic evidence. (ii) That hypertension is a risk factor for severe (...) disease in the case of SARS-CoV-2 suggests that altering hypertension treatment might alleviate disease, but the mechanisms are complex, and it is essential to consider and evaluate multiple mechanistic hypotheses. (iii) To be confident that public health interventions will be effective requires a detailed assessment of social and psychological components of the mechanisms of their action, in addition to mechanisms of disease. (iv) In particular, if vaccination programmes are to be effective, they must be carefully tailored to the social context; again, mechanistic evidence is crucial. We conclude that coronavirus research is best situated within the EBM+ evaluation framework. (shrink)

In this paper, I explicate and discuss performance-similarity reasoning as a strategy for mechanism schema evaluation, understood in Lindley Darden’s sense. This strategy involves inferring hypotheses about the mechanism responsible for cognitive capacities from premises describing the performance of those capacities; performance-similarity reasoning is a type of Inference to the Best Explanation, or IBE. Two types of such inferences are distinguished: one in which the performance of two systems is compared, and another when the performance of two systems (...) under intervention is compared. Both types of inferences are illustrated with examples taken from cognitive science. I conclude that performance-similarity reasoning is an important strategy for evaluating mechanistic hypotheses. (shrink)

ABSTRACT Proponents of mechanistic explanation have recently suggested that all explanation in the cognitive sciences is mechanistic, even functional explanation. This last claim is surprising, for functional explanation has traditionally been conceived as autonomous from the structural details that mechanistic explanations emphasize. I argue that functional explanation remains autonomous from mechanistic explanation, but not for reasons commonly associated with the phenomenon of multiple realizability. 1Introduction 2Mechanistic Explanation: A Quick Primer 3Functional Explanation: An Example 4Autonomy as Lack (...) of Constraint 5The Price of Autonomy 6Another Argument against Autonomy 7Conclusion: Autonomy and Multiple Realization. (shrink)

Some philosophers have argued that evidence of underlying mechanisms does not provide evidence for the effectiveness of a medical intervention. One such argument appeals to the unreliability of mechanistic reasoning. However, mechanistic reasoning is not the only way that evidence of mechanisms might provide evidence of effectiveness. A more reliable type of reasoning may be distinguished by appealing to recent work on evidential pluralism in the epistemology of medicine. A case study from virology provides an (...) example of this so‐called reinforced reasoning in medicine. It is argued that in this case study, the available evidence of underlying mechanisms did in fact play a role in providing evidence in favour of a medical intervention. This paper therefore adds a novel and recent case study to the literature in support of evidential pluralism in medicine. (shrink)

Medical explanations have often been thought on the model of biological ones and are frequently defined as mechanistic explanations of a biological dysfunction. In this paper, I argue that topological explanations, which have been described in ecology or in cognitive sciences, can also be found in medicine and I discuss the relationships between mechanistic and topological explanations in medicine, through the example of network medicine and medical genetics. Network medicine is a recent discipline that relies on the analysis (...) of various disease networks in order to find organizing principles in disease explanation. My aim is to show how topological explanations in network medicine can help solving the conceptual issues that pure mechanistic explanations of the genetics of disease are currently facing, namely the crisis of the concept of genetic disease, the progressive geneticization of diseases and the dissolution of the distinction between monogenic and polygenic diseases. However, I will also argue that topological explanations should not be considered as independent and radically different from mechanistic explanations for at least two reasons. First, in network medicine, topological explanations depend on and use mechanistic information. Second, they leave out some missing gaps in disease explanation that require, in turn, the development of new mechanistic explanations. Finally, I will insist on the specific contribution of topological explanations in medicine: they push us to develop an explanation of disease in general, instead of focusing on single explanations of individual diseases. This last point may have major consequences for biomedical research. (shrink)

The M + 1 Rule, that at equilibrium there should be only one more candidate running than seats available, extended Duverger's Law to the cases of more than one seat per district. Both the M + 1 rule and Duverger's Law have been confirmed repeatedly, albeit always with qualification. Yet we have reached no consensus on the mechanism that produces these two empirical regularities. In this paper I use a simple simulation to test the hypothesis that the mechanism is that (...) candidates retire after some fixed number of consecutive losses. I test the results of the simulation against several different empirical results and find a reasonably good fit. I also add a mechanism for increasing the number of candidates. These results suggest that the M + 1 rule and Duverger's law may be the result not of rational calculation but of some simple set of decision rules. The analysis also illustrates the usefulness of a simulation approach to hypothesis testing. (shrink)

Reasoning in Biological Discoveries brings together a series of essays, which focus on one of the most heavily debated topics of scientific discovery. Collected together and richly illustrated, Darden's essays represent a groundbreaking foray into one of the major problems facing scientists and philosophers of science. Divided into three sections, the essays focus on broad themes, notably historical and philosophical issues at play in discussions of biological mechanism; and the problem of developing and refining reasoning strategies, including interfield (...) relations and anomaly resolution. Darden summarizes the philosophy of discovery and elaborates on the role that mechanisms play in biological discovery. Throughout the book, she uses historical case studies to extract advisory reasoning strategies for discovery. Examples in genetics, molecular biology, biochemistry, immunology, neuroscience and evolutionary biology reveal the process of discovery in action. (shrink)

The idea at the core of the New Mechanical account of explanation can be summarized in the claim that explaining means showing ‘how things work’. This simple motto hints at three basic features of Mechanistic Explanation (ME): ME is an explanation-how, that implies the description of the processes underlying the phenomenon to be explained and of the entities that engage in such processes. These three elements trace a fundamental contrast with the view inherited from Hume and later from strict (...) logical empiricism (see Creath 2017), focused on epistemic and formal features of science and according to which issues concerning the kind of entities and processes that lie within a theory’s domain are extraneous to science and belong instead to ontology or metaphysics. Philosophers belonging to the new mechanical philosophy believe that the received view of scientific explanation (Hempel 2001), pivoting on the notion of law of nature, overshadows this insight. Since its origin in the 17th century, mechanical philosophy aimed to explain natural phenomena by reducing them to mechanisms. Traditional attempts to define the concept of mechanism involved the identification of a limited set of fundamental elements as, for instance, contact action, action at a distance, inertial motion (see e.g. Hesse 2005), and, more recently, transmission of a mark, or of a conserved quantity (see Frisch, this volume). The new mechanical philosophy rejects this austere characterization of mechanisms and mechanistic explanation and aim at providing a novel, philosophically rigorous explication of the concept of mechanism and of its role in scientific explanation and practice. ME has been adopted with profit in philosophy of special sciences (for instance in biomedical sciences, e.g. in the explanation of chemical transmission at synapses ((Machamer, Darden and Craver 2000), MDC henceforth); but also in social sciences, e.g. the three kinds of social mechanisms in Coleman’s analysis of Max Weber’s account of the role of the Protestant ethic in the growth of capitalism (Hedström and Swedberg 1998)), where exceptionless regularities are rarely ever found. In physics, it is generally possible to formulate explanations in law-based form, with the result that the plurality of explanatory forms might be overlooked. This should not come as a surprise, given that physics was the main inspiration for logical empiricists, and, in particular, Newtonian physics was a template for Hempel’s formulation of the covering law model. However, this situation is unfortunate, since, we will argue, knowing how things work is often part of the explanation of physical phenomena. In this chapter, we provide an introduction to the basic features of ME, with specific focus on its application to physics (section 1). The main part of the chapter is devoted to the defence of two theses: on the one hand, some domains of physics are not compatible with mechanistic reasoning and explanation (section 2); on the other hand, a comprehensive account of explanation in physics can’t dispense with ME (section 3). (shrink)

Resurgent interest in both mechanistic and counterfactual theories of explanation has led to a fair amount of discussion regarding the relative merits of these two approaches. James Woodward is currently the pre-eminent counterfactual theorist, and he criticizes the mechanists on the following grounds: Unless mechanists about explanation invoke counterfactuals, they cannot make sense of claims about causal interactions between mechanism parts or of causal explanations put forward absent knowledge of productive mechanisms. He claims that these shortfalls can be offset (...) if mechanists will just borrow key tenets of his counterfactual theory of causal claims. What mechanists must bear in mind, however, is that by pursuing this course they risk both the assimilation of the mechanistic theories of explanation into Woodward’s own favored counterfactual theory, and they risk the marginalization of mechanistic explanations to a proper subset of all explanations. An outcome more favorable to mechanists might be had by pursuing an actualist-mechanist theory of the contents of causal claims. While it may not seem obvious at first blush that such an approach is workable, even in principle, recent empirical research into causal perception, causal belief, and mechanical reasoning provides some grounds for optimism. (shrink)

Using the Grounded theory, we took 15 Chinese entrepreneurs as the research objects and constructed the entrepreneurial process model of dynamic evolution of entrepreneurial motivation. The model includes seven themes, such as egoist motivation, bottleneck, altruistic motivation, TP/MTP, empathy, responsible leadership, CSR implementation and entrepreneurial performance. Through the analysis of the internal relations between these elements, we abstracts the law of the dynamic evolution process of entrepreneurial motivation of Chinese entrepreneurs, and reveals the mechanism of the dynamic evolution process of (...) entrepreneurial motivation. The theoretical contribution of this paper is mainly reflected in the following two aspects: it enriches and expands the research results in the field of entrepreneurship motivation of Chinese entrepreneurs. From the perspective of entrepreneurial motivation, this study analyzes the dynamic evolution process of Internet entrepreneurs’ entrepreneurial motivation, extracts the rules of entrepreneurial process of dynamic evolution of Internet entrepreneurs, and provides a new path for enriching and expanding the research on Internet entrepreneurs’ entrepreneurial motivation. The study of turning point that enriches and complements the dynamic evolution of entrepreneurs’ entrepreneurial motivation. Using grounded theory, this paper deeply analyzes the reasons for the dynamic evolution of entrepreneurial motivation, and provides empirical evidence for the research on the evolution of localized entrepreneurial motivation in China. (shrink)

Reasoning patterns found in Galileo’s treatise on machines, On Mechanics, are compared with patterns identified in case studies of scientifically trained experts thinking aloud, and many similarities are found. At one level the primary patterns identified are ordered analogy sequences and special diagrammatic techniques to support them. At a deeper level I develop constructs to describe patterns that can support embodied, imagistic, mental simulations as a central underlying process. Additionally, a larger hypothesized pattern of ‘progressive imagistic generalization’—Galileo’s development of (...) a model or mechanism that becomes more and more general with each machine while still being imagistically projectable into many machines—provides a way to think about his progress toward a modern explanatory model of torque. By unpacking his arguments, we gain an appreciation of his skillful ability to foster imagistic processes underlying scientific thinking. (shrink)

In Responsibility and Control: A Theory of Moral Responsibility John Martin Fischer and Mark Ravizza propose an account of moral responsibility according to which an agent is morally responsible for an action just when that action is the product of her own moderately reasons-responsive mechanism, where reasons-responsiveness is explained in terms of the mechanism’s regular reasons-receptivity and weak reasons-reactivity. In a review of Fischer and Ravizza’s book Mele contends that their weakly reasons-reactivity condition is inadequate, constructing a case in which, (...) according to their theory, an extreme agoraphobic is morally responsible for his staying in his home. In this paper I modify Fischer and Ravizza’s account of moral responsibility in light of Mele’s problematic example, suggesting a refinement of their weakly reasons-reactivity requirement via a distinction between weakly sufficient reasons and strongly sufficient reasons. (shrink)

Evidence-based medicine (EBM) has long deemphasized mechanistic reasoning and pathophysiological rationale in assessing the effectiveness of interventions. The EBM+ movement has challenged this stance, arguing that evidence of mechanisms and comparative studies should both be seen as necessary and complementary. Advocates of EBM+ provide a combination of theoretical arguments and examples of mechanistic reasoning in medical research. However, EBM+ proponents have not provided recent examples of how downplaying mechanistic reasoning resulted in worse medical results (...) than would have occurred otherwise. Such examples are necessary to make the case that EBM+ responds to a problem in clinical practice that urgently demands a solution. In light of this, we examine the failed rollout of efavirenz as a first-line HIV treatment in Zimbabwe as evidence of the importance of mechanistic reasoning in improving clinical practice and public health policy decisions. We suggest that this case is analogous to examples commonly given to support EBM. (shrink)

Sections 3.16 and 3.23 of Roger Penrose's Shadows of the mind (Oxford, Oxford University Press, 1994) contain a subtle and intriguing new argument against mechanism, the thesis that the human mind can be accurately modeled by a Turing machine. The argument, based on the incompleteness theorem, is designed to meet standard objections to the original Lucas-Penrose formulations. The new argument, however, seems to invoke an unrestricted truth predicate (and an unrestricted knowability predicate). If so, its premises are inconsistent. The usual (...) ways of restricting the predicates either invalidate Penrose's reasoning or require presuppositions that the mechanist can reject. (shrink)

Low reason is about coping in the world in the world's terms; but our freedom, morality, and enlightenment require the higher, more speculative faculty. Dr. Hanhijarvi (Humboldt Univ.) invites us to explore the great thinkers and re-activate the profound abilities of the human mind that so importantly out-shine today's mechanistic thinking.

& Carnegie Mellon University Abstract The rationality of human causal judgments has been the focus of a great deal of recent research. We argue against two major trends in this research, and for a quite different way of thinking about causal mechanisms and probabilistic data. Our position rejects a false dichotomy between "mechanistic" and "probabilistic" analyses of causal inference -- a dichotomy that both overlooks the nature of the evidence that supports the induction of mechanisms and misses some important (...) probabilistic implications of mechanisms. This dichotomy has obscured an alternative conception of causal learning: for discrete events, a central adaptive task is to induce causal mechanisms in the environment from probabilistic data and prior knowledge. Viewed from this perspective, it is apparent that the probabilistic norms assumed in the human causal judgment literature often do not map onto the mechanisms generating the probabilities. Our alternative conception of causal judgment is more congruent with both scientific uses of the notion of causation and observed causal judgments of untutored reasoners. We illustrate some of the relevant variables under this conception, using a framework for causal representation now widely adopted in computer science and, increasingly, in statistics. We also review the formulation and evidence for a theory of human causal induction (Cheng, 1997) that adopts this alternative conception. (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)

Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic (...) explanations are considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

ABSTRACT What characterizes human reasoning is the ability of dealing with incomplete information. Incomplete logic is developed for modeling incomplete knowledge. The most distinctive feature of incomplete logic is its semantics. This is an alternative presentation of partial semantics. In this paper, we will introduce the general notion of incomplete logic (ICL), compare it with partial logic, and give the resolution method for it. We will also show how ICL can be applied to nonmonotonic reasoning. We define nonmonotonic (...) derivation as monotonic derivation in ICL from the database and some consistent assumptions. The mechanism of ICL makes it easy to assert the consistency of an assumption without asserting the assumption itself. (shrink)

The maze and the masses -- Democracy as the rule of the dumb many? -- A selective genealogy of the epistemic argument for democracy -- First mechanism of democratic reason: inclusive deliberation -- Epistemic failures of deliberation -- Second mechanism of democratic reason: majority rule.

1. Those having a detailed and first-hand knowledge of Descartes’s work seem agreed that it was highly original, genuinely critical and of permanent importance in the history of thought. And though they would differ in opinion on what are the reasons best advanced in support of their estimate, a majority would seem to regard the “Cartesian revolution” as summing up what is most meritorious in Descartes’s philosophy and most lasting in his influence. They would find Professor E. Gilson speaking their (...) mind when he declares, “Sur ce qu’il y a de nouveau et de strictement original dans sa pensée, aucun doute ne saurait subsister. Descartes est la revendication personnifiée du mathématisme universel. (shrink)

The mechanistic approach in philosophy of science contributes to our understanding of experimental design. Applying the mechanistic approach to experimentation in computing is beneficial for two reasons. It connects the methodology of experimentation in computing with the methodology of experimentation in established sciences, thereby strengthening the scientific reputability of computing and the quality of experimental design therein. Furthermore, it pinpoints the idiosyncrasies of experimentation in computing: computing deals closely with both natural and engineered mechanisms. Better understanding of the (...) idiosyncrasies, which manifest in terms of a nonstandard role for experimentation, are interesting both for computer scientists and for philosophers of science. Computer scientists can think more clearly about their experimental choices. The role of experimentation elucidated by computer science merits further study from philosophers of science generally, as it highlights a role for experimentation hitherto unrecognized by philosophers: demonstration that activities exist. (shrink)

Leibniz standardly associates “mechanism” with extended material bodies and their aggregates. In this paper, I identify and analyze a further distinct sense of “mechanism” in Leibniz that extends, by analogy, beyond the domain of material bodies and applies to the operations of immaterial substances such as the monads that serve, for Leibniz, as the metaphysical foundations of physical reality. I argue that in this sense, Leibniz understands “mechanism” as an intelligible process that is capable of providing a sufficient reason for (...) a series of changes. I then apply these findings to enrich our understanding of Leibniz’s well-known mill argument in Monadology ¶17: although material machines and mechanisms cannot produce perceptions, the perceptual activity of immaterial monads is to be understood as “mechanical” according to this analogical sense. (shrink)

This paper discusses the important paper by Paul Thagard on the pathway version of mechanistic explanation that is currently used in chemical explanation. The author claims that this method of explanation has a respectable pedigree and can be traced back to the Chemical Revolution in the arguments used by the Lavoisier School in their theoretical duels with Richard Kirwan, the proponent of a revised phlogistonian theory. Kirwan believed that complex chemical reactions could be explained by recourse to affinity tables (...) that catalogued the attraction that various simple bodies possessed towards each other. To explain was in effect to make a delayed prediction, it is not enough just to show how a phenomenon fits into the discernible patterns of the world. Lavoisier, Fourcroy and their colleagues used pathway reasoning, although disguising this fact by suggesting that affinities varied when subjected to n-body situations. (shrink)

Confronted with problems or situations that do not yield toknown theories and world views, scientists and students are alike. Theyare rarely able to directly build a model or a theory thereof. Rather,they must find ways to make sense of the circumstances using theircurrent knowledge and adjusting what is recognized in the process. Thisway of thinking, using past ways of perceiving the physical world tobuild new ones does not follow a logical path and cannot be described astheory revision. Likewise, in many (...) situations it is awkward, indeedoften impossible, to resort to analogical reasoning to account for it.This paper presents a new mechanism, called `tunnel effect', that mayexplain, in part, how scientists and students reason while constructinga new conceptual domain. `Tunnel effect' is also contrasted withanalogical reasoning. (shrink)

Godel's and Tarski's theorems were inspired by paradoxes: the Richard paradox, the Liar. Godel, in the 1951 Gibbs lecture argued from his metatheoretical results for a metaphysical claim: the impossibility of reducing, both, mathematics to the knowable by the human mind and the human mind to a finite machine (e.g. the brain). So Godel reasoned indirectly from paradoxes for metaphysical theses. I present four metaphysical theses concerning mechanism, reductive physicalism and time for the only purpose of suggesting how it could (...) be argued for them directly from paradoxical sentences. (shrink)

Hume's negative argument about probable reasoning is sometimes called the problem of induction. The modern version of that argument is centrally concerned with the warrant of probable reasoning and the justification of the beliefs that result from such reasoning. It is argued here that Hume is more concerned with the mechanism that produces such beliefs, and that his problem is more one of explanation than justification. What does Hume mean by raising the question whether we are determined (...) by reason in making the inference from a present impression to an unobserved idea? If we were determined by reason, something, such as the idea of necessary connection or the principle of uniformity, would have to serve as the intermediary via which we get from the impression to the idea. But no such idea or principle is available to us prior to our engaging in probable reasoning. So inferences or reasonings from the observed to the unobserved are not explained by an appeal to the faculty of reason. The point about not being determined by reason does not show that such inferences, or the beliefs we thus come to hold, are unreasonable. It shows that our coming to have such beliefs is not explained by an appeal to the proper functioning of the faculty of reason. (shrink)

Review of: Stephen Gaukroger: The Collapse of Mechanism and the Rise of Sensibility: Science and the Shaping of Modernity, 1680-1760. Oxford: Clarendon, 2010, pp. ix+505. £47.00 (hb). ISBN 9780199594931. This volume is the second of a projected six-volume work on the shaping of modern cognitive values through the emergence of a scientific culture, a phenomenon that Gaukroger takes to be specific to the West. The volume ranges from Newton’s initial publications on optics to the French Enlightenment and the publication of (...) the <i>Encyclopédie</i> of Diderot and d’Alembert. During this period, the unity within natural philosophy, secured by the view that matter theory should underlie all natural philosophy, is challenged, as is the unity between natural philosophy and physico-theology, the latter unity being the primary source of the cultural legitimacy that had allowed natural philosophy to flourish. The first type of unity was sundered as Newtonian natural philosophy disavowed the requirement that mechanics be united with a microscopic corpuscularian basis. Further, during this period, scientific (or natural philosophical) values first came to dominate the cognitive values of an entire culture, largely through the <i>persona</i> of the <i>philosophe</i> as the embodiment of reason, albeit a sensibilized reason arising from the new non-mechanistic natural philosophy of the mid-eighteenth century and no longer tied to physico-theology. The book does a better job charting the trend toward disunity than it does charting the rise of sensibility. (shrink)

My dissertation defends a non-mechanistic interpretation of Kant’s philosophy of nature. Inspired by the picture of nature in the Critique of Pure Reason and Metaphysical Foundations of Natural Science, most readers align Kant with Early Modern mechanists, who claim that we can know that the internally purposive form of causality characteristic of organisms has no place in nature. To these mechanistic readers, Kant banishes internal purposiveness from nature. To moderate mechanistic interpreters, because we cannot know whether there (...) are internally purposive things in nature and we can demonstrate that mechanism applies to nature, Kant pushes us to believe that any seemingly internally purposive natural products will eventually be explained in mechanistic terms. To strong mechanistic interpreters, Kant gives us the tools to know that there is no room for the special kind of teleology organisms exhibit in nature. My non-mechanistic interpretation rejects this trend by arguing that Kant urges us to believe that the internally purposive activity characteristic of organisms exists in nature. Belief in this context is a firm, positive, and voluntary attitude that aligns with and serves a subject’s interests and ends, and that has implications for the subject’s rational action, assertion, and deliberation. Kant’s stated goal in the third Critique is to bridge the gulf between freedom and nature. My non-mechanistic interpretation offers a new account of how Kant promises to construct this bridge. (shrink)

This paper focuses on the causal pluralism that emerges from the new mechanistic discussion on causality. The reason for our choice of the New Mechanical Philosophy is twofold. Firstly, the NMP is one of the dominant approaches within the current philosophy of science and has produced very extensive literature on the problem of causation. Secondly, the intersection of the understanding of nature via mechanisms and the focus on explanatory practice across different scientific fields has brought a great renewal of (...) causal explanations within the mechanistic framework. After characterizing the four dominant approaches to causation present in the NMP, we argue that each approach gives an important insight into the philosophical discussion about causality, but at the same time presents certain limitations. The main philosophical issues and their internal problems with respect to each approach are discussed, and in the following sections, we explicate the similarities and differences between those approaches. In the final section, we address the issue of causal pluralism and argue that the new mechanical approach to causation deserves its own place in the debate on causality, since it is an interesting case of interactive pluralism with respect to causality. (shrink)

In this paper, I consider a novel challenge to John Martin Fischer and Mark Ravizza’s reasons-responsiveness theory of moral responsibility. According to their view, agents possess the control necessary for moral responsibility if their actions proceed from a mechanism that is moderately reasons-responsive. I argue that their account of moderate reasons-responsiveness fails to provide necessary and sufficient conditions for moral responsibility since it cannot give an adequate account of the responsibility of individuals with autism spectrum disorder. Empirical evidence suggests that (...) autistic individuals demonstrate impairments in counterfactual thinking, and these impairments, I argue, are such that they cast doubt on Fischer and Ravizza’s construal of moderate reasons-responsiveness. I then argue that modifying the view in order to accommodate individuals with ASD forces them to defend a strong reasons-responsive account despite the fact that they explicitly deny that such an account can adequately characterize what it is to be morally responsible for one’s actions. (shrink)

Reasoning, defined as the production and evaluation of reasons, is a central process in science. The dominant view of reasoning, both in the psychology of reasoning and in the psychology of science, is of a mechanism with an asocial function: bettering the beliefs of the lone reasoner. Many observations, however, are difficult to reconcile with this view of reasoning; in particular, reasoning systematically searches for reasons that support the reasoner’s initial beliefs, and it only evaluates (...) these reasons cursorily. By contrast, reasoners are well able to evaluate others’ reasons: accepting strong arguments and rejecting weak ones. The argumentative theory of reasoning accounts for these traits of reasoning by postulating that the evolved function of reasoning is to argue: to find arguments to convince others and to change one’s mind when confronted with good arguments. Scientific reasoning, however, is often described as being at odds with such an argumentative mechanisms: scientists are supposed to reason objectively on their own, and to be pigheaded when their theories are challenged, even by good arguments. In this article, we review evidence showing that scientists, when reasoning, are subject to the same biases as are lay people while being able to change their mind when confronted with good arguments. We conclude that the argumentative theory of reasoning explains well key features of scientists’ reasoning and that differences in the way scientists and laypeople reason result from the institutional framework of science. (shrink)

We propose a framework for including information‐processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into the definition of (...) rational action. Theories are specified as optimal program problems, defined by an adaptation environment, a bounded machine, and a utility function. Such theories yield different classes of explanation, depending on the extent to which they emphasize adaptation to bounds, and adaptation to some ecology that differs from the immediate local environment. We illustrate this variation with examples from three domains: visual attention in a linguistic task, manual response ordering, and reasoning. We explore the relation of this framework to existing “levels” approaches to explanation, and to other optimality‐based modeling approaches. (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)

Both in biology and psychology there has been a tendency on the part of many investigators to focus solely on the mature organism and ignore development. There are many reasons for this, but an important one is that the explanatory framework often invoked in the life sciences for understanding a given phenomenon, according to which explanation consists in identifying the mechanism that produces that phenomenon, both makes it possible to side-step the development issue and to provide inadequate resources for actually (...) explaining development. When biologists and psychologists do take up the question of development, they find themselves confronted with two polarizing positions of nativism and empiricism. However, the mechanistic framework, insofar as it emphasizes organization and recognizes the potential for self-organization, does in fact provide the resources for an account of development which avoids the nativism-empiricism dichotomy. (shrink)

In this paper, we introduce Speedith which is an interactive diagrammatic theorem prover for the well-known language of spider diagrams. Speedith provides a way to input spider diagrams, transform them via the diagrammatic inference rules, and prove diagrammatic theorems. Speedith’s inference rules are sound and complete, extending previous research by including all the classical logic connectives. In addition to being a stand-alone proof system, Speedith is also designed as a program that plugs into existing general purpose theorem provers. This allows (...) for other systems to access diagrammatic reasoning via Speedith, as well as a formal verification of diagrammatic proof steps within standard sentential proof assistants. We describe the general structure of Speedith, the diagrammatic language, the automatic mechanism that draws the diagrams when inference rules are applied on them, and how formal diagrammatic proofs are constructed. (shrink)

Animals routinely adapt to changes in the environment in order to survive. Though reinforcement learning may play a role in such adaptation, it is not clear that it is the only mechanism involved, as it is not well suited to producing rapid, relatively immediate changes in strategies in response to environmental changes. This research proposes that counterfactual reasoning might be an additional mechanism that facilitates change detection. An experiment is conducted in which a task state changes over time and (...) the participants had to detect the changes in order to perform well and gain monetary rewards. A cognitive model is constructed that incorporates reinforcement learning with counterfactual reasoning to help quickly adjust the utility of task strategies in response to changes. The results show that the model can accurately explain human data and that counterfactual reasoning is key to reproducing the various effects observed in this change detection paradigm. (shrink)