Even though the evidence‐based medicine movement (EBM) labels mechanisms a low quality form of evidence, consideration of the mechanisms on which medicine relies, and the distinct roles that mechanisms might play in clinical practice, offers a number of insights into EBM itself. In this paper, I examine the connections between EBM and mechanisms from several angles. I diagnose what went wrong in two examples where mechanistic reasoning failed to generate accurate predictions for how a dysfunctional mechanism would respond to intervention. (...) I then use these examples to explain why we should expect this kind of mechanistic reasoning to fail in systematic ways, by situating these failures in terms of evolved complexity of the causal system(s) in question. I argue that there is still a different role in which mechanisms continue to figure as evidence in EBM: namely, in guiding the application of population‐level recommendations to individual patients. Thus, even though the evidence‐based movement rejects one role in which mechanistic reasoning serves as evidence, there are other evidentiary roles for mechanistic reasoning. This renders plausible the claims of some critics of evidencebased medicine who point to the ineliminable role of clinical experience. Clearly specifying the ways in which mechanisms and mechanistic reasoning can be involved in clinical practice frames the discussion about EBM and clinical experience in more fruitful terms. (shrink)

The reduction of grounding to causation, or each to a more general relation of which they are species, has sometimes been justified by the impressive inferential capacity of structural equation modelling, causal Bayes nets, and interventionist causal modelling. Many criticisms of this assimilation focus on how causation is inadequate for grounding. Here, I examine the other direction: how treating grounding in the image of causation makes the resulting view worse for causation. The distinctive features of causal modelling that make this (...) connection appealing are distorted beyond use by forcing them to fit onto grounding. The very inferential strength that makes causation attractive is only possible because of a narrow construal of what counts as a causal relation; as soon as that broadens, the inferential capacity markedly diminishes. Making causation suitable for application to grounding spoils what was appealing about causation for this task in the first place. However, grounding need not appeal to causation: causal modelling does not have exclusive claim to structural equation modeling or other formal techniques of modelling structure. I offer a case in favour of a different kind of metaphysical frugality, which tend towards narrow, more restrictive construals of relations like causation or grounding, because then each relation behaves more homogenously. This more homogenous behavior delivers stronger inferential power per relation even though there may be more relations to which one is committed. (shrink)

In this field guide, I distinguish five separate senses with which the term ‘mechanism’ is used in contemporary philosophy of science. Many of these senses have overlapping areas of application but involve distinct philosophical claims and characterize the target mechanisms in relevantly different ways. This field guide will clarify the key features of each sense and introduce some main debates, distinguishing those that transpire within a given sense from those that are best understood as concerning distinct senses. The ‘new mechanisms’ (...) sense is at the center of most of these contemporary debates and will be treated at greater length; subsequent senses of mechanism will be primarily distinguished from this one. In part I of this paper, I distinguish two senses of the term ‘mechanism’, both of which are explicitly hierarchical and nested in character, such that any given mechanism is comprised of smaller sub-mechanisms, in turn comprised of yet smaller sub-sub-mechanisms and so on. While both of the senses discussed here are anti-reductive, they differ in their focus on scientific practice versus metaphysics, in the degree of regularity they attribute to mechanisms, and in terms of their relationships to the discussions of mechanisms in the history of philosophy and science. (shrink)

A finer-grained delineation of a given explanandum reveals a nexus of closely related causal and non- causal explanations, complementing one another in ways that yield further explanatory traction on the phenomenon in question. By taking a narrower construal of what counts as a causal explanation, a new class of distinctively mathematical explanations pops into focus; Lange’s characterization of distinctively mathematical explanations can be extended to cover these. This new class of distinctively mathematical explanations is illustrated with the Lotka-Volterra equations. There (...) are at least two distinct ways those equations might hold of a system, one of which yields straightforwardly causal explanations, but the other of which yields explanations that are distinctively mathematical in terms of nomological strength. In the first, one first picks out a system or class of systems, finds that the equations hold in a causal -explanatory way; in the second, one starts with the equations and explanations that must apply to any system of which the equations hold, and only then turns to the world to see of what, if any, systems it does in fact hold. Using this new way in which a model might hold of a system, I highlight four specific avenues by which causal and non- causal explanations can complement one another. (shrink)

This paper articulates an account of causation as a collection of information-theoretic relationships between patterns instantiated in the causal nexus. I draw on Dennett’s account of real patterns to characterize potential causal relata as patterns with specific identification criteria and noise tolerance levels, and actual causal relata as those patterns instantiated at some spatiotemporal location in the rich causal nexus as originally developed by Salmon. I develop a representation framework using phase space to precisely characterize causal relata, including their degree (...) of counterfactual robustness, causal profiles, causal connectivity, and privileged grain size. By doing so, I show how the philosophical notion of causation can be rendered in a format that is amenable for direct application of mathematical techniques from information theory such that the resulting informational measures are causal informational measures. This account provides a metaphysics of causation that supports interventionist semantics and causal modeling and discovery techniques. (shrink)

In this field guide, I distinguish five separate senses with which the term ‘mechanism’ is used in contemporary philosophy of science. Many of these senses have overlapping areas of application but involve distinct philosophical claims and characterize the target mechanisms in relevantly different ways. This field guide will clarify the key features of each sense and introduce some main debates, distinguishing those that transpire within a given sense from those that are best understood as concerning two distinct senses. The ‘new (...) mechanisms’ sense is the primary sense from which other senses will be distinguished. In part II of this field guide, I consider three further senses of the term that are ontologically ‘flat’ or at least not explicitly hierarchical in character: equations in structural equation models of causation, causal-physical processes, and information-theoretic constraints on states available to systems. After characterizing each sense, I clarify its ontological commitments, its methodological implications, how it figures in explanations, its implications for reduction, and the key manners in which it differs from other senses of mechanism. I conclude that there is no substantive core meaning shared by all senses, and that debates in contemporary philosophy of science can benefit from clarification regarding precisely which sense of mechanism is at stake. (shrink)

How regular do mechanisms need to be, in order to count as mechanisms? This paper addresses two arguments for dropping the requirement of regularity from the definition of a mechanism, one motivated by examples from the sciences and the other motivated by metaphysical considerations regarding causation. I defend a broadened regularity requirement on mechanisms that takes the form of a taxonomy of kinds of regularity that mechanisms may exhibit. This taxonomy allows precise explication of the degree and location of regular (...) operation within a mechanism, and highlights the role that various kinds of regularity play in scientific explanation. I defend this regularity requirement in terms of regularity’s role in individuating mechanisms against a background of other causal processes, and by prioritizing mechanisms’ ability to serve as a model of scientific explanation, rather than as a metaphysical account of causation. It is because mechanisms are regular, in the expanded sense described here, that they are capable of supporting the kinds of generalizations that figure prominently in scientific explanations. (shrink)

Leuridan (2010) argued that mechanisms cannot provide a genuine alternative to laws of nature as a model of explanation in the sciences, and advocates Mitchell’s (1997) pragmatic account of laws. I first demonstrate that Leuridan gets the order of priority wrong between mechanisms, regularity, and laws, and then make some clarifying remarks about how laws and mechanisms relate to regularities. Mechanisms are not an explanatory alternative to regularities; they are an alternative to laws. The existence of stable regularities in nature (...) is necessary for either model of explanation: regularities are what laws describe and what mechanisms explain. (shrink)

I present three reasons why philosophers of science should be more concerned about violations of causal faithfulness (CF). In complex evolved systems, mechanisms for maintaining various equilibrium states are highly likely to violate CF. Even when such systems do not precisely violate CF, they may nevertheless generate precisely the same problems for inferring causal structure from probabilistic relationships in data as do genuine CF-violations. Thus, potential CF-violations are particularly germane to experimental science when we rely on probabilistic information to uncover (...) the DAG, rather than already knowing the DAG from which we could predict the right experiments to ‘catch out’ the hidden causal relationships. (shrink)

This chapter examines the philosophical discussion concerning the relationship between time, memory, attention, and consciousness, from Locke through the Scottish Common Sense tradition, in terms of its influence on James' development of the specious present doctrine. The specious present doctrine is the view that the present moment in experience is non punctate, but instead comprises some nonzero amount of time; it contrasts with the mathematical view of the present, in which the divide between past and future is merely a point (...) or a line with no thickness. The anonymous source for the term 'specious present' is revealed as a retired businessman-turned-amateur philosopher. The more likely source for the idea itself is a little-known philosopher, Shadworth Hollway Hodgson, who was not merely a significant influence on James but also on Husserl's development of the tripartite account of internal time consciousness. I conclude by demonstrating how James' changing views on the relationship between concepts and experience meant that by the later period of his writings, including those in which he develops his own views on pragmatism, James would have not merely noted the contrast between a mathematical conception of the present and our actual experience of it, he would have taken a further step and condoned the thick experience of the present as demonstrating the inadequacy of the intellectualized mathematical characterization. (shrink)

I provide an overview and critical discussion of Causation with a Human Face, by James Woodward.

This chapter offers a overview of Shadworth Hodgson's account of experience as fundamentally temporal, an account that was deeply influential on thinkers such as William James and which prefigures the phenomenology of Husserl in many ways. I highlight eight key features that are characteristic of Hodgson's account, and how they hang together to provide a coherent overall picture of experience and knowledge. Hodgson's account is then compared to Husserl's, and I argue that Hodgson's account offers a better target for projects (...) such as neurophenomenology than does Husserl's. Hodgson's account is historically important as a culmination of a certain trajectory of British Empiricist thought. It offers a substantive alternative for how to think about temporality and experience in contemporary discussions, not just of the present moment but of the relationship between experience and knowledge more broadly. (shrink)

Humean accounts of laws are often contrasted with governing accounts, and recent developments have added pragmatic versions of Humeanism. This paper offers Mitchell's pragmatist, perspectival account of laws as a third option. The differences between these accounts come down to the role of modality. Mitchell's bottom-up account allows for subtle gradations of modal content to be conveyed by laws. The perspectival character of laws is not an accident or something to be eventually eliminated - it is part of how this (...) modal content is conveyed. I conclude with a discussion of the metaphysical commitments in Humeanism as requiring a perspectiveless view of the manifold from outside, and how Mitchell's situated account is better able to account for the substantive notion of possibility involved in scientific laws. (shrink)

I highlight a metaphysical concern that stands in the way of more widespread adoption of causal modeling techniques such as causal Bayes nets. Researchers in some fields may resist adoption due to concerns that they don't 'really' understand what they are saying about a system when they apply such techniques. Students in these fields are repeated exhorted to be cautious about application of statistical techniques to their data without a clear understanding of the conditions required for those techniques to yield (...) genuine insight into the data. They are acutely aware that anyone can chuck some data into a software package and get what looks like an answer, even though these tests may not be well-defined for the data on which they can apparently be run. This is thus a healthy skepticism for uptake of causal modeling methods, which points directly to the need for a metaphysical understanding of causation in order to successfully use the modeling methods. Without a clear understanding of what the methods are committing to, including what it means to say that there exists a causal relationship, researchers have limited ability to identify potentially bad output, or to independently verify results. (shrink)

A critical review of Collin Rice's book, Leveraging Distortions: Explanation, Idealization, and Universality in Science.

Given the technological constraints of long-duration space travel and planetary settlement, off-Earth humans will likely need to employ food systems very different from their terrestrial counterparts, and newly emerging food technologies are being developed that will shape novel food systems in these off-Earth contexts. Projected off-Earth food systems may therefore potentially “alienate” their users in new ways compared to Earth-based food systems. They will be susceptible to alienation in ways that are similar to such potential on Earth, where there are (...) points of overlap between off-Earth food systems and any of the multitudes of ways in which food systems on Earth are structured. They will also be susceptible to new forms of alienation, as we encounter scenarios that are genuinely structurally novel to humanity. These are especially important to consider since there are comparatively fewer analyses of these food systems where they differ from existing ones. We propose five non-exhaustive sources of value beyond nutrition our individual relationships with a food may possess: gustatory, social, cultural, epistemic, and authorial value. Using these, we offer examples of ways in which an off-Earth food system may exacerbate or alleviate alienation for humans in long-term off-Earth food systems. (shrink)

This chapter discusses several kinds of reduction that are often found in the biomedical sciences, in contrast to reduction in fields such as physics. This includes reduction as a methodological assumption for how to investigate phenomena like complex diseases, and reduction as a conceptual tool for relating distinct models of the same phenomenon. The case of Parkinson’s disease illustrates a wide variety of ways in which reductionism is an important tool in medicine.

This paper outlines some key issues that arise when agency and temporality are considered jointly, from the perspective of psychology, cognitive neuroscience, phenomenology, and action theory. I address the difference between time simpliciter and time as represented as it figures in phenomena like intentional binding, goal-oriented action plans, emulation systems, and ‘temporal agency’. An examination of Husserl’s account of time consciousness highlights difficulties in generalizing his account to include a substantive notion of agency, a weakness inherited by explanatory projects like (...) neurophenomenology. I conclude by sketching a project analogous to the projects in neurophenomenology, based on Thompson’s naïve action theory. (shrink)

Even in areas of philosophy of science that don’t involve formal treatments of truth, one’s background view of truth still centrally shapes views on other issues. I offer an informal way to think about truth as trueing, like trueing a bicycle wheel. This holist approach to truth provides a way to discuss knowledge products like models in terms of how well-trued they are to their target. Trueing emphasizes: the process by which models are brought into true; how the idealizations in (...) models are not false but rather like spokes in appropriate tension to achieve a better-trued fit to target; and that this process is not accomplished once and done forever, but instead requires upkeep and ongoing fine-tuning. I conclude by emphasizing the social importance of being a pragmatist about truth in order to accurately answer questions about science such as, “but do we really know that…”. (shrink)

This chapter examines the relationship between laws and mechanisms as approaches to characterising generalizations and explanations in science. I give an overview of recent historical discussions where laws failed to satisfy stringent logical criteria, opening the way for mechanisms to be investigated as a way to explain regularities in nature. This followed by a critical discussion of contemporary debates about the role of laws versus mechanisms in describing versus explaining regularities. I conclude by offering new arguments for two roles for (...) laws that mechanisms cannot subsume, one epistemically optimistic and one pessimistic, both broadly Humean. Do note that this piece is not primarily Hume exegesis; it is more of a riff in the key of Hume. (shrink)

Meta-laws, including conservation laws, are laws about the form of more specific, phenomenological, laws. Lange distinguishes between meta-laws as coincidences, where the meta-law happens to hold because the more specific laws hold, and meta-laws as constraints to which subsumed laws must conform. He defends this distinction as a genuine metaphysical possibility, such that metaphysics alone ought not to rule one way or another, leaving it an open question for physics. Lange’s distinction marks a genuine difference in how a given meta-law (...) can be used in explanations. Yet, I argue, it is not simply an empirical matter as to whether a given conservation law is a constraint or a coincidence. There is no set matter of fact about the world that determines this, and physics alone will not be able to return a determinate verdict on a law-by-law basis, even while there is a genuine difference between any given law as constraint and as coincidence. Rather, the difference marks different ways of treating the same law in a theoretical setting: by shifting the explanatory context, treating the same law as part of a different mathematical structure, it can be a genuine constraint and a genuine coincidence. The difference between constraint and coincidence relates to the way in which we use a law in specific theoretical and explanatory settings. Because the same law can appear in multiple contexts, it can be used in these genuinely different ways, without itself ‘‘really’’ being either one or the other as some atomistic empirical fact. Conservation laws as constraints and conservation laws as coincidences are both genuine theoretical roles that the same law can play. I conclude by considering how this pragmatist construal of constraints versus coincidences reveals how two parts of Lange’s work in this section of the book are unexpectedly independent of one another. -/- . (shrink)

The problem of mental causation in contemporary philosophy of mind concerns the possibility of holding two different views that are in apparent tension. The first is physicalism, the view that there is nothing more to the world than the physical. The second is that the mental has genuine causal efficacy in a way that does not reduce to pure physical particle-bumping. This article provides a historical background to this question, with focus on Davidson’s anomalous monism and Kim’s causal exclusion problem. (...) Responses to causal exclusion are categorized in terms of six different argumentative strategies. In conclusion, caution is advised regarding the inclination to reduce the mental to the physical and sketch a positive direction for substantively characterizing mental causation by recourse to well-confirmed accounts of causation coupled with empirical research. (shrink)

This paper brings together Thompson's naive action explanation with interventionist modeling of causal structure to show how they work together to produce causal models that go beyond current modeling capabilities, when applied to specifically selected systems. By deploying well-justified assumptions about rationalization, we can strengthen existing causal modeling techniques' inferential power in cases where we take ourselves to be modeling causal systems that also involve actions. The internal connection between means and end exhibited in naive action explanation has a modal (...) strength like that of distinctively mathematical explanation, rather than that of causal explanation. Because it is stronger than causation, it can be treated as if it were merely causal in a causal model without thereby overextending the justification it can provide for inferences. This chapter introduces and demonstrate the usage of the Rationalization condition in causal modeling, where it is apt for the system(s) being modeled, and to provide the basics for incorporating R variables into systems of variables and R arrows into DAGs. Use of the Rationalization condition supplements causal analysis with action analysis where it is apt. (shrink)

Critical Notice for: Metaphysics and the Philosophy of Science: New Essays. Edited by Matthew H. Slater and Zanja Yudell. Oxford University Press, 2017. x + 258 pp.