Much contemporary debate on the nature of mechanisms centers on the issue of modulating negative causes. One type of negative causability, which I refer to as “causation by absence,” appears difficult to incorporate into modern accounts of mechanistic explanation. This paper argues that a recent attempt to resolve this problem, proposed by Benjamin Barros, requires improvement as it overlooks the fact that not all absences qualify as sources of mechanism failure. I suggest that there are a number of additional types (...) of effects caused by absences that need to be incorporated to account for the diversity of causal connections in the biological sciences. Furthermore, it is argued that recognizing natural variability in mechanisms, such as attenuation, leads to some interesting line-drawing issues for contemporary philosophy of mechanisms. (shrink)

In addition to theorizing about the role and value of mechanisms in scientific explanation or the causal structure of the world, there is a fundamental task of getting straight what a ‘mechanism’ is in the first place. Broadly, this paper is about the challenge of application: the challenge of aligning one's philosophical account of a scientific concept with the manner in which that concept is actually used in scientific practice. This paper considers a case study of the challenge of application (...) as it pertains to the concept of a mechanism: the debate about whether natural selection is a mechanism. By making clear what is and is not at stake in this debate, this paper considers various strategies for dealing with the challenge of application and makes a case for definitional pluralism about mechanism concepts. (shrink)

I distinguish three theses associated with the new mechanistic philosophy – concerning causation, explanation and scientific methodology. Advocates of each thesis are identified and relationships among them are outlined. I then look at some recent work on natural selection and mechanisms. There, attention to different kinds of New Mechanism significantly affects of what is at stake.

Advocates of the New Mechanicism in philosophy of science argue that scientific explanation often consists in describing mechanisms responsible for natural phenomena. Despite its successes, one might think that this approach does not square with the ontological strictures of quantum mechanics. New Mechanists suppose that mechanisms are composed of objects with definite properties, which are interconnected via local causal interactions. Quantum mechanics calls these suppositions into question. Since mechanisms are hierarchical it appears that even macroscopic mechanisms must supervene on a (...) set of “objects” that behave non-classically. In this paper we argue, in part by appeal to the theory of quantum decoherence, that the universal validity of quantum mechanics does not undermine neo-mechanistic ontological and explanatory claims as they occur within in classical domains. Additionally, we argue that by relaxation of certain classical assumptions, mechanistic explanatory strategies can sometimes be carried over into the quantum domain. (shrink)

The relationship between topological explanation and mechanistic explanation is unclear. Most philosophers agree that at least some topological explanations are mechanistic explanations. The crucial question is how to make sense of this claim. Zednik (Philos Psychol 32(1):23–51, 2019) argues that topological explanations are mechanistic if they (i) describe mechanism sketches that (ii) pick out organizational properties of mechanisms. While we agree with Zednik’s conclusion, we critically discuss Zednik’s account and show that it fails as a general account of how and (...) when topological explanations are mechanistic. First, if topological explanations were just mechanism sketches, this implies that they could be enriched by replacing topological terms with mechanistic detail. This, however, conflicts how topological explanations are used in scientific practice. Second, Zednik’s account fails to show how topological properties can be organizational properties of mechanisms that have a place in mechanistic explanation. The core issue is that Zednik’s account ignores that topological properties often are _global_ properties while mechanistic explanantia refer to _local_ properties. We demonstrate how these problems can be solved by a recent account of mechanistic completeness (Craver and Kaplan in Br J Philos Sci 71(1):287–319, 2020; Kohár and Krickel in Calzavarini and Viola (eds) Neural mechanisms—new challenges in the philosophy of neuroscience, Springer, New York, 2021) and use a multilayer network model of Alzheimer’s Disease to illustrate this. (shrink)

This paper examines the adequacy of causal graph theory as a tool for modeling biological phenomena and formalizing biological explanations. I point out that the causal graph approach reaches it limits when it comes to modeling biological phenomena that involve complex spatial and structural relations. Using a case study from molecular biology, DNA-binding and -recognition of proteins, I argue that causal graph models fail to adequately represent and explain causal phenomena in this field. The inadequacy of these models is due (...) to their failure to include relevant spatial and structural information in a way that does not render the model non-explanatory, unmanageable, or inconsistent with basic assumptions of causal graph theory. (shrink)

One task of historians is to construct causal ascription of singular historicals between eminent historical events. For instance, the controversy resulting from the confusing butterfly ballot of Florida’s year 2000 presidential election cost Gore his presidency. However, to research into these matters is inevitably to appeal to counterfactual deliberation in an epistemic fashion because the past is fixed. One standard idea is Max Weber’s, Weber causation: “f was a cause of φ” is assertable iff “¬f □→ ¬φ” is assertable. Reiss (...) gives an exceptionally good analysis of this topic and outlines historians’ reasoning, claiming that backtracking analyses of counterfactual conditionals employed in historical thought experiments is the signature of historical study of causal ascription of singular historicals. Nevertheless, he concludes that it is very difficult to reach an uncontroversial ascription for this sort in most cases. For this reason, he proposes to find difference-making relations that will suffice. The objective of this paper is to provide a more fine-grained, intervention-based, backtracking analysis of counterfactual conditionals upon which a more satisfactory account of causal ascription of singular historicals can be given. Reiss’ account of difference-making relation will be shown to be unsatisfactory. Moreover, a formal ground of the epistemology of historical thought experiments can be given, along with the constraints of this account resultant from the semantic features of non-transitivity and strong centering of counterfactual conditionals. Finally, some epistemological points of causal ascription of singular historicals and historical thought experiments will be given. (shrink)

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

It is widely assumed that mechanistic explanations are causal explanations. Many prominent new mechanists endorse interventionism as the correct analysis of explanatory causal models in biology and other fields. This article argues that interventionism is not entirely satisfactory in this regard. A case study of Jacob and Monod’s operon model shows that at least some important mechanistic explanations in biology present significant contrasts with the interventionist account. This result motivates a more inclusive approach to mechanistic explanation, allowing for noncausal aspects.

Inference to the Best Explanation is usually employed in the Scientific Realism debates. As far as particular scientific theories are concerned, its most ready usage seems to be that of a theory of confirmation. There are however more uses of IBE, namely as an epistemological theory of testimony and as a means of categorising and justifying the sources of evidence. In this paper, I will present, develop and exemplify IBE as a theory of the quality of evidence - taking examples (...) from medicine and showing that IBE can thereby provide the epistemological underpinning and justify the criteria of grading quality of mechanistic evidence that have been recently provided in the Clarke et al. paper on how evidence of medical mechanisms is to be construed alongside population studies. (shrink)

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

The purpose of this article is to examine two important issues concerning the agency theory of causality: the charge of anthropomorphism and the relation of simultaneous causation. After a brief outline of the agency theory, sections 2–4 contain the refutation of the three main forms in which the charge of anthropomorphism is to be found in the literature. It will appear that it is necessary to distinguish between the subjective and the objective aspect of the concept of causation. This will (...) lead, in section 5, to contrast two kinds of anthropomorphism, one which has been rightly rejected by modern science and one which is fully compatible with the objective reality of the causal processes. Finally, section 6 will apply the preceding considerations to simultaneous causation. On the one hand, in a basic sense, there can be no simultaneous causal relations. On the other hand, simultaneous causation arises when we consider the natural change by abstracting from the agent and from her/his projects of interven.. (shrink)

Much recent work on explanation in the interventionist tradition emphasizes the explanatory value of stable causal generalizations—i.e., causal generalizations that remain true in a wide range of background circumstances. We argue that two separate explanatory virtues are lumped together under the heading of `stability’. We call these two virtues breadth and guidance respectively. In our view, these two virtues are importantly distinct, but this fact is neglected or at least under-appreciated in the literature on stability. We argue that an adequate (...) theory of explanatory goodness should recognize breadth and guidance as distinct virtues, as breadth and guidance track different ideals of explanation, satisfy different cognitive and pragmatic ends, and play different theoretical roles in helping us understand the explanatory value of mechanisms. Thus keeping track of the distinction between these two forms of stability yields a more accurate and perspicuous picture of the role that stability considerations play in explanation. (shrink)

An important strategy in the discovery of biological mechanisms involves the piecing together of experimental results from interventions. However, if mechanisms are investigated by means of ideal interventions, as defined by James Woodward and others, then the kind of information revealed is insufficient to discriminate between modular and non-modular causal contributions. Ideal interventions suffice for constructing webs of causal dependencies that can be used to make some predictions about experimental outcomes, but tell us little about how causally relevant factors are (...) organized together and how they interact with each other in order to produce a phenomenon. I argue that lab research relies on more elaborated types of interventions targeting in a controlled fashion multiple variables at the same time in order to probe the temporal organization of causally-relevant factors along distinct causal pathways and to test for non-modular interaction effects, thus providing crucial spatial-temporal constraints guiding the formulation of more detailed mechanistic explanations. (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)

The emphasis on the organization of entities and their activities and interactions has been labeled one of the most distinct contributions of mechanistic philosophy. In this paper I discuss the manner in which the organization of entities and their activities and interactions participates in bringing about phenomena. I present a well-known example from molecular biology—the functioning of the genetic switch in phage lambda—and discuss Marco J. Nathan’s notion of causation by concentration. Nathan introduces causation by concentration to account for the (...) irreducible causal role that the concentration ratio between two kinds of proteins possesses in the genetic switch mechanism in phage lambda. I discuss what the irreducibility of this causal role amounts to and provide a mechanistic interpretation of Nathan’s causation by concentration; that is, I explain this irreducible causal role as one organizational feature of this mechanism. The paper concludes that biological mechanisms need a causal pluralist framework [similar to Glennan’s account in (2009), (2010) and (2017) but slightly modified] where organizational features such as the concentration ratio have a causally relevant role, yet all the causally productive relations occur at the level of entities or individuals. (shrink)

Engineering failure investigations seek to reconstruct the actual causes of major engineering failures. The investigators need to establish the existence of certain past events and the actual causal relationships that these events bear to the failures in question. In this paper, I examine one method for reconstructing the actual causes of failure events, which I call "feature dependence". The basic idea of feature dependence is that some features of an event are informative about the features of its causes; therefore, the (...) investigators can use the features of a known failure event to reconstruct details of its causes. I make explicit the structure of feature dependence and the evidential basis of its key premises, and show how feature dependence works in the investigation of the American Airlines Flight 191 accident. (shrink)

In this book, I defend the present-centered approach in historiography of science (i.e. study of the history of science), build an account for causal explanations in historiography of science, and show the fruitfulness of the approach and account in when we attempt to understand science. -/- The present-centered approach defines historiography of science as a field that studies the developments that led to the present science. I argue that the choice of the targets of studies in historiography of science should (...) be directly connected to our values and preferences in an intersubjective process. The main advantage of this approach is that it gives a clear motivation for historiography of science and avoids or solves stubborn conceptual and practical problems within the field. -/- The account of causal explanations is built on the notions of counterfactual scenarios and contrastive question-answer pairs. I argue that if and only if we track down patterns of counterfactual dependencies, can we understand history. Moreover, I define the notions of historical explanation, explanatory competition, explanatory depth, and explanatory resources. -/- Finally, I analyze the existing historiography of science with the framework built in the previous chapter, and I show that this framework clarifies many first-order (i.e. concerning the history of science) and meta-level issues (i.e. concerning the nature of science in general) that historians and philosophers tackle. As an illustration of the philosophical power of the framework, I explicate the notion of local explanation and analyze the question of whether the developments of science were necessary or contingent. (shrink)

This paper discusses methodological similarities between Collingwood's approach to causation and contemporary manipulability-based views. Firstly, I argue that on both approaches there is a preoccupation with the origin of causal concepts which further connects to the aim of establishing the priority of a certain concept/sense of causation as more fundamental. The significant difference lies in Collingwood's focus on the logical and historical priority (Collingwood's sense I) while in more recent theories the focus has been on psychology (i.e., on different philosophical (...) concepts of causation tested in psychological setting-- Woodward, Waskan, Gijsbers & de Bruin). Secondly, I argue that on both Collingwood's views and contemporary approaches (especially Menzies & Price, Price, but also Woodward) there is an important connection between causation and the agent's perspective. This can be subsumed under what Collingwood identifies as the main presupposition underlying causal thought: the relation between the agent's perceived situation and the agent's desired situation/ goal. More broadly, the recent views on causation under discussion share Collingwood's aim of elucidating the problem of causation through investigating causal knowledge and thus can be integrated with his wider project of addressing metaphysical issues through the means of epistemology. (shrink)

This thesis examines philosophical controversies surrounding the evaluation of medical treatments, with a focus on the evidential roles of randomised trials and mechanisms in Evidence-Based Medicine. Current 'best practice' usually involves excluding non-randomised trial evidence from systematic reviews in cases where randomised trials are available for inclusion in the reviews. The first paper challenges this practice and evaluates whether adding of evidence from non-randomised trials might improve the quality and precision of some systematic reviews. The second paper compares the alleged (...) methodological benefits of randomised trials over observational studies for investigating treatment benefits. It suggests that claims about the superiority of well-conducted randomised controlled trials over well-conducted observational studies are justified, especially when results from the two methods are contradictory. The third paper argues that postulating the unpredictability paradox in systematic reviews when no detectable empirical differences can be found requires further justification. The fourth paper examines the problem of absence causation in the context of explaining causal mechanisms and argues that a recent solution is incomplete and requires further justification. Solving the problem by describing absences as causes of 'mechanism failure' fails to take into account the effects of absences that lead to vacillating levels of mechanism functionality. The fifth paper criticises literature that has emphasised functioning versus 'broken' or 'non-functioning' mechanisms emphasising that many diseases result from increased or decreased mechanism function, rather than complete loss of function. Mechanistic explanations must account for differences in the effectiveness of performed functions, yet current philosophical mechanistic explanations do not achieve this. The last paper argues that the standard of evidence embodied in the ICE theory of technological function is too permissive for evaluating whether the proposed functions of medical technologies have been adequately assessed and correctly ascribed. It argues that high-quality evidence from clinical studies is necessary to justify functional ascriptions to health care technologies. (shrink)

This paper argues against the view that the standard explanation of phase transitions in statistical mechanics may be considered a causal explanation, a distortion that can nevertheless successfully represent causal relations.

This dissertation argues that cognition is a kind of natural agency. Natural agency is the capacity that certain systems have to act in accordance with their own norms. Natural agents are systems that bias their repertoires in response to affordances in the pursuit of their goals. Cognition is a special mode of this general phenomenon. Cognitive systems are agents that have the additional capacity to actively take their worlds to be certain ways, regardless of whether the world is really that (...) way. In this way, cognitive systems are desituated. Desituatedness is the root of specifically cognitive capacities for representation and abstraction. There are two main reasons why this view needs defending. First, natural agency is typically viewed as incompatible with natural science because it is committed to a teleological mode of explanation. Second, cognition is typically held to be categorically distinct from natural agency. This dissertation argues against both of these views. It argues against the incompatibility of agency and natural science by demonstrating that systems biology, general systems theory, and sciences that deal with complex systems have typically underappreciated conceptual and theoretical resources for grounding agency in the causal structure of the world. These conceptual resources do not, however, reduce agency to systems theory because the normativity inherent in agency demands descriptive resources beyond those of even the most sophisticated systems theory. It argues against the categorical difference between natural agency and cognition by pointing out that separating cognition from a richer web of situated, ecologically embedded relations between the agent and the world generates the frame problem, which is an insuperable obstacle to making cognition that is sufficiently responsive to the complexity of the world. Rooting cognition in natural agency is a more robust empirical bet for theorizing cognition and artificial intelligence. (shrink)

In this chapter we examine the relation between mechanisms and laws/counterfactuals by revisiting the main notions of mechanism found in the literature. We distinguish between two different conceptions of ‘mechanism’: mechanisms-of underlie or constitute a causal process; mechanisms-for are complex systems that function so as to produce a certain behavior. According to some mechanists, a mechanism fulfills both of these roles simultaneously. The main argument of the chapter is that there is an asymmetrical dependence between both kinds of mechanisms and (...) laws/counterfactuals: while some laws and counterfactuals must be taken as primitive (non-mechanistic) facts of the world, all mechanisms depend on laws/counterfactuals. (shrink)

Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...) psychology. Despite the ubiquity of causal reasoning, textbooks of cognitive psychology have neglected this growing field. The goal of The Oxford Handbook of Causal Reasoning is to fill this gap. The handbook brings together the leading researchers in the field of causal reasoning and offers state-of-the-art presentations of theories and research. It provides introductions of competing theories of causal reasoning, and discusses its role in various cognitive functions and domains. The final section presents research from neighboring fields. 1. Causal Reasoning: An Introduction Michael R. Waldmann Part I: Theories of Causal Cognition 2. Associative Accounts of Causal Cognition Mike E. Le Pelley, Oren Griffiths, and Tom Beesley 3. Rules of Causal Judgment: Mapping Statistical Information Onto Causal Beliefs José C. Perales, Andrés Catena, Antonio Cándido, and Antonio Maldonado 4. The Inferential Reasoning Theory of Causal Learning: Toward a Multi- Process Propositional Account Yannick Boddez, Jan De Houwer, and Tom Beckers 5. Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World: Generalizing the Invariance of Causal Power Patricia W. Cheng and Hongjing Lu 6. The Acquisition and Use of Causal Structure Knowledge Benjamin Margolin Rottman 7. Formalizing Prior Knowledge in Causal Induction Thomas L. Griffiths 8. Causal Mechanisms Samuel G. B. Johnson and Woo-kyoung Ahn 9. Force Dynamics and Causation Phillip Wolff and Robert Thorstad 10. Mental Models and Causation P. N. Johnson- Laird and Sangeet S. Khemlani 11. Pseudocontingencies Klaus Fiedler and Florian Kutzner 12. Singular Causation David Danks 13. Cognitive Neuroscience of Causal Reasoning Joachim T. Operskalski and Aron K. Barbey Part II: Basic Cognitive Functions 14. Visual Impressions of Causality Peter White 15. Goal-Directed Actions Bernhard Hommel 16. Planning and Control Magda Osman 17. Reinforcement Learning and Causal Models Samuel J. Gershman 18. Causation and the Probability of Causal Conditionals David E. Over 19. Causal Models and Conditional Reasoning Mike Oaksford and Nick Chater 20. Concepts as Causal Models: Categorization Bob Rehder 21. Concepts as Causal Models: Induction Bob Rehder 22. Causal Explanation Tania Lombrozo and Nadya Vasilyeva 23. Diagnostic Reasoning Björn Meder and Ralf Mayrhofer 24. Inferring Causal Relations by Analogy Keith J. Holyoak and Hee-Seung Lee 25. Causal Argument Ulrike Hahn, Roland Bluhm, and Frank Zenker 26. Causality in Decision- Making York Hagmayer and Philip M. Fernbach Part III: Domains of Causal Reasoning 27. Intuitive Theories Tobias Gerstenberg and Joshua B. Tenenbaum 28. Space, Time, and Causality Marc J. Buehner 29. Causation in Legal and Moral Reasoning David A. Lagnado and Tobias Gerstenberg 30. The Role of Causal Knowledge in Reasoning About Mental Disorders Woo-kyoung Ahn, Nancy S. Kim, and Matthew S. Lebowitz 31. Causality and Causal Reasoning in Natural Language Torgrim Solstad and Oliver Bott 32. Social Attribution and Explanation Denis Hilton Part IV: Development, Phylogeny, and Culture 33. The Development of Causal Reasoning Paul Muentener and Elizabeth Bonawitz 34. Causal Reasoning in Non-Human Animals Christian Schloegl and Julia Fischer 35. Causal Cognition and Culture Andrea Bender, Sieghard Beller, and Douglas L. Medin. (shrink)

The experimental interventions that provide evidence of causal relations are notably similar to those that provide evidence of constitutive relevance relations. In the first two sections, I show that this similarity creates a tension: there is an inconsistent triad between Woodward’s popular interventionist theory of causation, Craver’s mutual manipulability account of constitutive relevance in mechanisms, and a variety of arguments for the incoherence of inter-level causation. I argue for an interpretation of the views in which the tension is merely apparent. (...) I propose to explain inter-level relations without inter-level causation by appealing to the notion of fat-handed interventions, and an argument against inter-level causation which dissolves the problem. (shrink)

Fundamental to Computer Science is the distinction between abstractions and implementations. When that distinction is applied to various philosophical questions it yields the following conclusions. -/- • EMERGENCE. It isn’t as mysterious as it’s made out to be; the possibility of strong emergence is not a threat to science. -/- • INTERACTIONS BETWEEN HIGHER-LEVEL ENTITIES. Physical interaction among higher-level entities is illusory. Abstract interactions are the source of emergence, new domains of knowledge, and complex systems. -/- • PHYSICS and the (...) SPECIAL SCIENCES. The new domains of knowledge derived from abstract interactions are the basis of the autonomy of the special sciences. -/- • DOWNWARD CAUSATION. It’s a zombie idea that should have a stake put through its heart and be replaced by downward entailment. (shrink)

Objects appear to causally interact with one another in virtual worlds, such as video games, virtual reality, and training simulations. Is this causation real or is it illusory? In this paper I argue that virtual causation is as real as physical causation. I achieve this in two steps: firstly, I show how virtual causation has all the important hallmarks of relations that are causal, as opposed to merely accidental, and secondly, I show how virtual causation is genuine according to one (...) influential metaphysical theory of causation: the mechanistic approach. (shrink)

I examine the adequacy of the causal graph-structural equations approach to causation for modeling biological mechanisms. I focus in particular on mechanisms with complex dynamics such as the PER biological clock mechanism in Drosophila. I show that a quantitative model of this mechanism that uses coupled differential equations – the well-known Goldbeter model – cannot be adequately represented in the standard causal graph framework, even though this framework does permit causal cycles. The reason is that the model contains dynamical information (...) about the mechanism that concerns causal properties but that does not correspond to variables that could be subject to independent interventions. Thus, a representation of the mechanisms as a causal structural model necessarily suppresses causally relevant information. (shrink)

Most philosophical debate over mental causation has been concerned with reconciling commonsense intuitions that there are causal interactions between the mental and the physical with philosophical theories of the nature of the mental that seem to suggest otherwise. My concern is with a different and more practical problem. We often confront some cognitive, affective, or bodily phenomenon, and wonder about its source – its etiology or its underlying causal basis. For instance, you might wonder whether your queasiness due to something (...) you ate, or whether it is just nervousness, or whether your aunt’s memory loss is a neurological problem or a psychological response to trauma. Such questions attempt to localize the causes of a phenomenon at some level in the complex multi-level systems that we human animals are. In this paper I will attempt to tease out the sense of level implicit in such questions, and to show how it is related to current mechanistic accounts of levels. I will argue that the explanation of our practices of level attribution is deeply pragmatic. Such attributions are often attempts to locate the causes of problems, and to identify interventions that could solve those problems. (shrink)