Existing research suggests that people's judgments of actual causation can be influenced by the degree to which they regard certain events as normal. We develop an explanation for this phenomenon that draws on standard tools from the literature on graphical causal models and, in particular, on the idea of probabilistic sampling. Using these tools, we propose a new measure of actual causal strength. This measure accurately captures three effects of normality on causal judgment that have been (...) observed in existing studies. More importantly, the measure predicts a new effect ("abnormal deflation"). Two studies show that people's judgments do, in fact, show this new effect. Taken together, the patterns of people's causal judgments thereby provide support for the proposed explanation. (shrink)

The statistical technique of analysis of variance is often used by biologists as a measure of causal factors’ relative strength or importance. I argue that it is a tool ill suited to this purpose, on several grounds. I suggest a superior alternative, and outline some implications. I finish with a diagnosis of the source of error – an unwitting inheritance of bad philosophy that now requires the remedy of better philosophy.

Reasons for action is a widely employed methodology in practical philosophy, and especially in moral philosophy. Reasons are facts that explain and justify actions. But, conceptually, if reasons were causes, incontinent actions would be impossible. When an agent ranks an evaluation about what to do as his best judgement, it entails that he has a reason for acting as that judgement prescribes. But when an agent acts incontinently, he acts in accordance to an intention that is not aligned with his (...) best evaluative judgement. Yet, if the agent’s best evaluative judgement provides him a reason for action, this reason should also be his strongest reason, and therefore, the strongest cause. How then can it be possible that an agent incontinently acts according to a reason of inferior causal strength? In this paper, I analyze how Davidson’s argument for the possibility of incontinent actions interacts with his causal theory of actions. I argue that Davidson’s proposal does not fully respect the two principles of intentional rationality, that he himself claims to be compelling. Lastly, I sketch some initial steps that might be helpful to drawing more precise conceptual distinctions in terms of the rationality of incontinent actions. (shrink)

Is the thought that having a reason for action can also be the cause of the action for which it is the reason coherent? This is an attempt to say exactly what is involved in such a thought, with special reference to the case of con-reasons, reasons that count against the action the agent eventually choses.

The chapter explores whether, or to what extent, recent work in experimental philosophy puts pressure on the idea that the concept of causation is ‘egalitarian’. Causal selection – where experimental subjects tend to rate the causal strength of (for example) a norm-violator more strongly than a non-norm-violator – is a well established phenomenon, and is in prima facie tension with an egalitarian conception of causation; it also, indirectly, puts prima facie pressure on the idea that causation is (...) a worldly phenomenon whose obtaining is independent of facts about norms. The chapter explores both the various psychological mechanisms and the broadly pragmatic approaches to explaining causal selection. It argues that the answer to the question whether or not the concept of causation is egalitarian is currently significantly empirically underdetermined, and suggests some avenues for further investigation. (shrink)

I present a new definition of verisimilitude, framed in terms of causes. Roughly speaking, according to it a scientific model is approximately true if it captures accurately the strengths of the causes present in any given situation. Against much of the literature, I argue that any satisfactory account of verisimilitude must inevitably restrict its judgments to context-specific models rather than general theories. We may still endorse—and only need—a relativized notion of scientific progress, understood now not as global advance but rather (...) as the mastering of particular problems. This also sheds new light on longstanding difficulties surrounding language-dependence and models committed to false ontologies. (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)

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)

The famous Cartesian Nicolas Malebranche (1638-1715) espoused the occasionalist doctrine that ‘there is only one true cause because there is only one true God; that the nature or power of each thing is nothing but the will of God; that all natural causes are not true causes but only occasional causes’ (LO, 448, original italics). One of Malebranche’s well-known arguments for occasionalism, known as, the ‘no necessary connection’ argument (or, NNC ) stems from the principle that ‘a true cause… is (...) one such that the mind perceives a necessary connection between it and its effect’ (LO, 450). The outline of this paper is as follows. I explicitly layout NNC and articulate some of its prima facie strengths (§1). I then critically discuss, what I take to be, the two main arguments against NNC of the Lee-Pyle interpretation (§2). The main conclusion from (§2) is that Malebranche did not abandon NNC in his later works given textual evidence from the Dialogues, contrary to the Lee-Pyle interpretation. In (§3) I discuss in what ways Suárez, Leibniz, Régis and Spinoza all accepted the main premise of NNC. Then, I rebut Steven Nadler’s influential and unchallenged criticism that Malebranche conflated causal and logical necessity, and provide a more accurate interpretation of Malebranche that only commits him to a partial reduction of causal to logical necessity (§4). (shrink)

When we compare the influences of two causes on an outcome, if the conclusion from every group is against that from the conflation, we think there is Simpson’s Paradox. The Existing Causal Inference Theory (ECIT) can make the overall conclusion consistent with the grouping conclusion by removing the confounder’s influence to eliminate the paradox. The ECIT uses relative risk difference Pd = max(0, (R − 1)/R) (R denotes the risk ratio) as the probability of causation. In contrast, Philosopher Fitelson (...) uses confirmation measure D (posterior probability minus prior probability) to measure the strength of causation. Fitelson concludes that from the perspective of Bayesian confirmation, we should directly accept the overall conclusion without considering the paradox. The author proposed a Bayesian confirmation measure b* similar to Pd before. To overcome the contradiction between the ECIT and Bayesian confirmation, the author uses the semantic information method with the minimum cross-entropy criterion to deduce causal confirmation measure Cc = (R − 1)/max(R, 1). Cc is like Pd but has normalizing property (between −1 and 1) and cause symmetry. It especially fits cases where a cause restrains an outcome, such as the COVID-19 vaccine controlling the infection. Some examples (about kidney stone treatments and COVID-19) reveal that Pd and Cc are more reasonable than D; Cc is more useful than Pd. (shrink)

When we compare the influences of two causes on an outcome, if the conclusion from every group is against that from the conflation, we think there is Simpson’s Paradox. The Existing Causal Inference Theory (ECIT) can make the overall conclusion consistent with the grouping conclusion by removing the confounder’s influence to eliminate the paradox. The ECIT uses relative risk difference Pd = max(0, (R − 1)/R) (R denotes the risk ratio) as the probability of causation. In contrast, Philosopher Fitelson (...) uses confirmation measure D (posterior probability minus prior probability) to measure the strength of causation. Fitelson concludes that from the perspective of Bayesian confirmation, we should directly accept the overall conclusion without considering the paradox. The author proposed a Bayesian confirmation measure b* similar to Pd before. To overcome the contradiction between the ECIT and Bayesian confirmation, the author uses the semantic information method with the minimum cross-entropy criterion to deduce causal confirmation measure Cc = (R − 1)/max(R, 1). Cc is like Pd but has normalizing property (between −1 and 1) and cause symmetry. It especially fits cases where a cause restrains an outcome, such as the COVID-19 vaccine controlling the infection. Some examples (about kidney stone treatments and COVID-19) reveal that Pd and Cc are more reasonable than D; Cc is more useful than Pd. (shrink)

Transcranial magnetic stimulation is used to make inferences about relationships between brain areas and their functions because, in contrast to neuroimaging tools, it modulates neuronal activity. The central aim of this article is to critically evaluate to what extent it is possible to draw causal inferences from repetitive TMS data. To that end, we describe the logical limitations of inferences based on rTMS experiments. The presented analysis suggests that rTMS alone does not provide the sort of premises that are (...) sufficient to warrant strong inferences about the direct causal properties of targeted brain structures. Overcoming these limitations demands a close look at the designs of rTMS studies, especially the methodological and theoretical conditions which are necessary for the functional decomposition of the relations between brain areas and cognitive functions. The main points of this article are that TMS-based inferences are limited in that stimulation-related causal effects are not equivalent to structure-related causal effects due to TMS side effects, the electric field distribution, and the sensitivity of neuroimaging and behavioral methods in detecting structure-related effects and disentangling them from confounds. Moreover, the postulated causal effects can be based on indirect effects. A few suggestions on how to manage some of these limitations are presented. We discuss the benefits of combining rTMS with neuroimaging in experimental reasoning and we address the restrictions and requirements of rTMS control conditions. The use of neuroimaging and control conditions allows stronger inferences to be gained, but the strength of the inferences that can be drawn depends on the individual experiment’s designs. Moreover, in some cases, TMS might not be an appropriate method of answering causality-related questions or the hypotheses have to account for the limitations of this technique. We hope this summary and formalization of the reasoning behind rTMS research can be of use not only for scientists and clinicians who intend to interpret rTMS results causally but also for philosophers interested in causal inferences based on brain stimulation research. (shrink)

Unlike any other monograph on legal liability, Michael S. Moore’s book CAUSATION AND RESPONSIBILITY contains a well-informed and in-depth discussion of the metaphysics of causation. Moore does not share the widespread view that legal scholars should not enter into metaphysical debates about causation. He shows respect for the subtleties of philosophical debates on causal relata, identity conditions for events, the ontological distinctions between events, states of affairs, facts and tropes, and the counterfactual analysis of event causation, and he considers (...) all these issues relevant to law. In this contribution, I defend an amended version of the COUNTERFACTUAL theory of event causation both against Moore’s criticism and against some traits of Lewis’s version of the theory. On a number of counts, I simply defend Lewis against Moore’s misdirected criticism. Moore’s unreasonable demand that all the commonplaces about causation have to FOLLOW from the counterfactual analysis rests on his mistaken claim that the counterfactual theory IDENTIFIES causation with counterfactual dependence. In other respects, I part company with Lewis in order to highlight some underrated strengths of the counterfactual approach. The common denominator of my revisions is that they make the counterfactual theory unambiguously singularist. The suggested revisions comprise: performing the counterfactual analysis with Davidsonian rather than with Lewisian events, taking seriously the ex post-character of singular causal statements, making explicit the indexical ceteris paribus clause that fixes the actual circumstances of the causing event, abandoning the alleged transitivity of causation, and, last but not least, doing everything in the correct order. The correct order is to start with bedrock intuitions about the nature of causality rather than with a general possible world semantics, and then to turn these intuitions into constraints for the class of counterfactuals that a counterfactual analysis of causation has to consider. (shrink)

Standard statistical measures of strength of association, although pioneered by Pearson deliberately to be acausal, nowadays are routinely used to measure causal efficacy. But their acausal origins have left them ill suited to this latter purpose. I distinguish between two different conceptions of causal efficacy, and argue that: 1) Both conceptions can be useful 2) The statistical measures only attempt to capture the first of them 3) They are not fully successful even at this 4) An alternative (...) definition more squarely based on causal thinking not only captures the second conception, it can also capture the first one better too. (shrink)

Data from medical research are typically summarized with various types of outcome measures. We present three arguments in favor of absolute over relative outcome measures. The first argument is from cognitive bias: relative measures promote the reference class fallacy and the overestimation of treatment effectiveness. The second argument is decision-theoretic: absolute measures are superior to relative measures for making a decision between interventions. The third argument is causal: interpreted as measures of causal strength, absolute measures satisfy a (...) set of desirable properties, but relative measures do not. Absolute outcome measures outperform relative measures on all counts. (shrink)

Libertarianism appears to be incoherent, because free will appears to be incompatible with indeterminism. In support of this claim, van Inwagen offered an argument that is now known as the “rollback argument”. In a recent reply, Lara Buchak has argued that the underlying thought experiment fails to support the first of two key premises. On her view, this points to an unexplored alternative in the free will debate, which she calls “chance-incompatibilism”. I will argue that the rollback thought experiment does (...) support the second key premise of the argument, and, more importantly, that libertarianism is committed to the first premise for independent reasons concerning the relationship between the normative and causal strength of the agent’s reasons. The upshot will be that chance-incompatibilism is not a promising new alternative in the free will debate, and we will see that the debate around those issues can benefit from more attention to the role of the agent’s reasons for action. (shrink)

The first purpose of this series of articles is to introduce case studies on how current AI models can be used in the development of a possible theory of quantum gravity, their limitations, and the role the researcher has in steering the development in the right direction, even highlighting the errors, weaknesses and strengths of the whole process. -/- The second is to introduce the new Presentist Fragmentalist ontology as a framework and use it for developing theories of quantum gravity (...) and speculate on achieving a TOE. We emphasize it is necessary for the researcher to check everything in these articles for themselves. While there are many good ideas in this series of papers, the AI is known to make even arithmetic and algebraic mistakes. -/- To select just five apparently good ideas, there is a causal interaction tensor Cαβγδ(F1, F2) that encodes the causal relationship and the strength of the (possibly non-local) interaction between two fragments of reality (formed by each quantum system). There is a quantitative prediction for a testable table-top experiment. There is an explanation of how spacetime emerges from the fragments and their interactions. There is an explicit account of the double-slit experiment. And there is an explanation how this theory accommodates dark matter and dark energy simultaneously. -/- We explore ideas, equations they lead to, concrete calculations, and give corrections along the way. While these are generally morally right within this framework they must be checked by the researcher. Given this caveat, we believe we have made significant progress with the PF interpretation in developing a theory of quantum gravity and pointing out a possible path to a TOE. (shrink)

In temporal binding, the temporal interval between one event and another, occurring some time later, is subjectively compressed. We discuss two ways in which temporal binding has been conceptualized. In studies showing temporal binding between a voluntary action and its causal consequences, such binding is typically interpreted as providing a measure of an implicit or pre-reflective “sense of agency”. However, temporal binding has also been observed in contexts not involving voluntary action, but only the passive observation of a cause-effect (...) sequence. In those contexts, it has been interpreted as a top-down effect on perception reflecting a belief in causality. These two views need not be in conflict with one another, if one thinks of them as concerning two separate mechanisms through which temporal binding can occur. In this paper, we explore an alternative possibility: that there is a unitary way of explaining temporal binding both within and outside the context of voluntary action as a top-down effect on perception reflecting a belief in causality. Any such explanation needs to account for ways in which agency, and factors connected with agency, have been shown to affect the strength of temporal binding. We show that principles of causal inference and causal selection already familiar from the literature on causal learning have the potential to explain why the strength of people’s causal beliefs can be affected by the extent to which they are themselves actively involved in bringing about events, thus in turn affecting binding. (shrink)

A remarkable number of Nietzsche's substantive moral psychological views have been borne out by evidence from the empirical sciences. Moral judgments are products of affects on Nietzsche's view, but the latter are in turn causally dependent upon more fundamental features of the individual. Nietzsche accepts a doctrine of types. The path is short from the acceptance of the Doctrine of Types to the acceptance of epiphenomenalism, as Leiter, and more recently, Riccardi argue. This chapter explains Nietzsche's phenomenological account of willing, (...) which serves as independent motivation for the view that Nietzsche denies the causal efficacy of conscious acts of willing. It also explores that in spite of an absence of volitional freedom, self‐control can be usefully understood on a strength‐model of motivational resources. The chapter concludes with a brief discussion of how Nietzsche, without employing the contemporary methods of empirical psychology, could nonetheless be such a prescient moral psychologist. (shrink)

The influence of historical-causal theories of reference developed in the late sixties and early seventies by Donnellan, Kripke, Putnam and Devitt has been so strong that any semantic theory that has the consequence of assigning disjunctive representational content to the mental states of twins (e.g. [H2O or XYZ]) has been thereby taken to refute itself. Similarly, despite the strength of pre-theoretical intuitions that exact physical replicas like Davidson's Swampman have representational mental states, people have routinely denied that they (...) have any intentional/representational states. I want to focus on a particular brand of causal theory that is not historical, the so-called pure informational or nomic covariance theories, and examine how they propose to handle twin cases and replicas like Swampman. In particular, I will take up Fodor. (shrink)

The first purpose of this series of articles is to introduce case studies on how current AI models can be used in the development of a possible theory of quantum gravity, their limitations, and the role the researcher has in steering the development in the right direction, even highlighting the errors, weaknesses and strengths of the whole process. The second is to introduce the new Presentist Fragmentalist ontology as a framework and use it for developing theories of quantum gravity and (...) speculate on achieving a TOE. We emphasize it is necessary for the researcher to check everything in these articles for themselves. While there are many good ideas in this series of papers, the AI is known to make even arithmetic and algebraic mistakes. To select just five apparently good ideas, there is a causal interaction tensor Cαβγδ(F1, F2) that encodes the causal relationship and the strength of the (possibly non-local) interaction between two fragments of reality (formed by each quantum system). There is a quantitative prediction for a testable table-top experiment. There is an explanation of how spacetime emerges from the fragments and their interactions. There is an explicit account of the double-slit experiment. And there is an explanation how this theory accommodates dark matter and dark energy simultaneously. We explore ideas, equations they lead to, concrete calculations, and give corrections along the way. While these are generally morally right within this framework they must be checked by the researcher. Given this caveat, we believe we have made significant progress with the PF interpretation in developing a theory of quantum gravity and pointing out a possible path to a TOE. (shrink)

There is good reason to believe that scientific realism requires a commitment to the objective modal structure of the physical world. Causality, equilibrium, laws of nature, and probability all feature prominently in scientific theory and explanation, and each one is a modal notion. If we are committed to the content of our best scientific theories, we must accept the modal nature of the physical world. But what does the scientific realist’s commitment to physical modality require? We consider whether scientific realism (...) is compatible with Humeanism about the laws of nature, and we conclude that it is not. We specifically identify three major problems for the best-systems account of lawhood: its central concept of strength cannot be formulated non-circularly, it cannot offer a satisfactory account of the laws of the special sciences, and it can offer no explanation of the success of inductive inference. In addition, Humeanism fails to be naturalistically motivated. For these reasons, we conclude that the scientific realist must embrace natural necessity. (shrink)

A comprehensive introduction to the Language of Though Hypothesis (LOTH) accessible to general audiences. LOTH is an empirical thesis about thought and thinking. For their explication, it postulates a physically realized system of representations that have a combinatorial syntax (and semantics) such that operations on representations are causally sensitive only to the syntactic properties of representations. According to LOTH, thought is, roughly, the tokening of a representation that has a syntactic (constituent) structure with an appropriate semantics. Thinking thus consists in (...) syntactic operations defined over representations. Most of the arguments for LOTH derive their strength from their ability to explain certain empirical phenomena like productivity, systematicity of thought and thinking. (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)

Two major clarifications have greatly abetted the understanding and fruitful expansion of the theory of natural selection in recent years: the acknowledgment that interactors, not replicators, constitute the causal unit of selection; and the recognition that interactors are Darwinian individuals, and that such individuals exist with potency at several levels of organization (genes, organisms, demes, and species in particular), thus engendering a rich hierarchical theory of selection in contrast with Darwin’s own emphasis on the organismic level. But a piece (...) of the argument has been missing, and individuals at levels distinct from organisms have been denied potency (although granted existence within the undeniable logic of the theory), because they do not achieve individuality with the same devices used by organisms and therefore seem weak by comparison. We show here that different features define Darwinian individuality across scales of size and time. In particular, species-individuals may develop few emergent features as direct adaptations. The interactor approach works with emergent fitnesses, not with emergent features; and species, as a consequence of their different mechanism for achieving individuality (reproductive exclusivity among subparts, that is, among organisms), express many effects from other levels. Organisms, by contrast, suppress upwardly cascading effects, because the organismic style of individuality (by functional integration of subparts) does not permit much competition or differential reproduction of parts from within. Species do not suppress the operation of lower levels; such effects therefore become available as exaptations conferring emergent fitness—a primary source of the different strength that species achieve as effective Darwinian individuals in evolution. (shrink)

, whereby some causes are deemed more important than others, are ubiquitous in historical studies. Drawing from influential recent work on causation, I develop a definition of causal-explanatory strength. This makes clear exactly which aspects of explanatory weighting are subjective and which objective. It also sheds new light on several traditional issues, showing for instance that: underlying causes need not be more important than proximate ones; several different causes can each be responsible for most of an effect; small (...) causes need not be less important than big ones; and non-additive interactive effects between causes present no particular difficulty. Key Words: causation • explanation • history • interaction • proximate • underlying. (shrink)

[This is an earlier (1997), much longer and more detailed version of my entry on LOTH in the _Stanford Encyclopedia of Philosophy_] The Language of Thought Hypothesis (LOTH) is an empirical thesis about thought and thinking. For their explication, it postulates a physically realized system of representations that have a combinatorial syntax (and semantics) such that operations on representations are causally sensitive only to the syntactic properties of representations. According to LOTH, thought is, roughly, the tokening of a representation that (...) has a syntactic (constituent) structure with an appropriate semantics. Thinking thus consists in syntactic operations defined over representations. Most of the arguments for LOTH derive their strength from their ability to explain certain empirical phenomena like productivity, systematicity of thought and thinking. (shrink)

(Longer version - work in progress) Various accounts of distinctively mathematical explanations (DMEs) of complex systems have been proposed recently which bypass the contingent causal laws and appeal primarily to mathematical necessities constraining the system. These necessities are considered to be modally exalted in that they obtain with a greater necessity than the ordinary laws of nature (Lange 2016). This paper focuses on DMEs of the number of equilibrium positions of n-tuple pendulum systems and considers several different DMEs of (...) these systems which bypass causal features. It then argues that there is a tension between the modal strength of these DMEs and their epistemic hooking, and we are forced to choose between (a) a purported DME with greater modal strength and wider applicability but poor epistemic hooking, or (b) a narrowly applicable DME with lesser modal strength but with the right kind of epistemic hooking. It also aims to show why some kind of DMEs may be unappealing for working scientists despite their strong modality, and why some DMEs fail to be modally robust because of making ill-informed assumptions about their target systems. The broader goal is to show why such tensions weaken the case for DMEs for pendulum systems in general. (shrink)

It has been suggested that certain problems may be unsolvable because of the mind's cognitive structure, but we may wonder what problems, and exactly why. The ultimate origin of the universe and the mind-body problem seem to be two such problems. As to why, Colin McGinn has argued that the mind-body problem is unsolvable because any theoretical concepts about the brain will be observation-based and unable to connect to unobservable subjective experience. McGinn's argument suggests a requirement of imagability -- an (...) observation basis -- for physical causal explanation that cannot be met for either of these problems. Acausal descriptions may be possible but not the causal analyses that provide the greatest explanatory satisfaction, a psychological phenomenon that seems tied to the strength of the underlying observation basis but is affected by other factors as well. (shrink)

Immanuel Kant mentions fate (Schicksal) in several places. Peter Thielke offers the only sustained interpretation of what Kant meant by fate. According to Thielke, fate is a “usurpatory concept” that takes the place of causality but fails to do its job. There are problems with this interpretation, relative to Kant’s philosophy and to the ordinary concept of fate. It is not clear why we only find a usurpation of causality and not the other concepts of the categories, or how a (...) usurpation of an a priori concept could occur. Thielke’s interpretation does not explain the way in which fate attributions are only made about events that have significance for human action or well-being, or fate’s teleological aspect. I outline the textual evidence that, for Kant, fate usurps providence, a postulate of practical reason, and then show how this interpretation preserves the strengths but avoids the weaknesses of its competitor. (shrink)

SYMMETRY IN PHYSICS: FROM PROPORTION AND HARMONY TO THE TERM OF METALENGUAJE -/- Ruth Castillo Universidad Central de Venezuela -/- The revolutionary changes in physics require a careful exploration of the way in which concepts depend on the theoretical structure in which they are immerse. A historical reconstruction allows us to show how the notion of symmetry evolves from the definition as proportion and harmony to its consideration within the language of contemporary physics, as a linguistic meta-theoretical requirement in physical (...) theories. In contemporary terms, symmetry is a fundamental category of research to which the usual categories of the natural sciences can be reduce in: space, time, causality, interaction, matter, strength, etc ... Thus, symmetry is a concept with different meanings: heuristically symmetric models inspire scientists in the search for solutions to different problems. Methodologically, symmetric structures are use to make theories, laws with invariant properties. A description of nature in terms of symmetric structures and symmetry ruptures seems to be the proper way to describe the complexity of reality. (shrink)

In this work, I will support a combined notion of harm according to which there are qualitatively different harms. I will support a way in which the severity of harms could be measured. Then, I will provide three principles about the strength of the reasons against harming. The supported thesis will provide some tools to solve some problems of the general part of criminal law. In relation to the analytical stratum of statutory description of an offence, I will show (...) that the defended notion of harm could help to solve cases of hypothetical and alternative causal courses. In relation to the analytical stratum of unlawfulness (or wrongfulness), I will show that the proposed ranking of the severity of harms help us to distinguish between cases of necessity as justification and necessity as excuse. In relation to the analytical stratum of culpability, I will show that the principles regarding the strength of the reasons against harming help us to supply straightforward criteria to measure the punishment to impose for having committed some crime. -/- En este trabajo intentaré defender una noción combinada de daño de acuerdo a la cual existen dos tipos de daños cualitativamente diferentes. Asimismo, defenderé un modo en que la gravedad de los diferentes daños puede ser graduada. Derivado de lo anterior, extraeré tres principios sobre la fuerza de las razones en contra de dañar. La tesis defendida proporcionará herramientas para resolver algunos problemas de la parte general de derecho penal. En relación al tipo penal, mostraré que la noción de daño defendida puede ayudar a resolver casos de cursos causales alternativos e hipotéticos. En referencia a la antijuridicidad, mostraré que la clasificación de la gravedad de los daños propuesta ayuda a distinguir qué casos de estado de necesidad deben considerarse como justificación y cuales como excusa. En referencia a la culpabilidad, mostraré que los principios sobre la diferente fuerza de las razones en contra de dañar ayudan a aportar criterios claros para la individualización de la pena a imponer por la comisión de un delito. (shrink)

We develop a new version of the causal theory of spacetime. Whereas traditional versions of the theory seek to identify spatiotemporal relations with causal relations, the version we develop takes causal relations to be the grounds for spatiotemporal relations. Causation is thus distinct from, and more basic than, spacetime. We argue that this non-identity theory, suitably developed, avoids the challenges facing the traditional identity theory.

Causation appears to present us with an interpretative difficulty. While arguably a redundant relation given fundamental physics, it is nevertheless apparently pragmatically indispensable. This chapter revisits certain arguments made previously by the author for these claims with the benefit of hindsight, starting with the role of causal models in the human sciences, and attempting to explain why it is not possible to straightforwardly ground such models in fundamental physics. This suggests that further constraints, going beyond physics, are needed to (...) legitimate such models. These supplementary constraints could be reified, but that would seem to conflict with the completeness of physics. A response is to emphasize the practical role of causal talk, and the author suggests that a fictionalist approach might be worth exploring. After clarifying fictionalism as a general approach, they carry out in some detail the project of clarifying what a fictionalist attitude to causation would involve. (shrink)

Causal claims are context sensitive. According to the old orthodoxy (Mackie 1974, Lewis 1986, inter alia), the context sensitivity of causal claims is all due to conversational pragmatics. According to the new contextualists (Hitchcock 1996, Woodward 2003, Maslen 2004, Menzies 2004, Schaffer 2005, and Hall ms), at least some of the context sensitivity of causal claims is semantic in nature. I want to discuss the prospects for causal contextualism, by asking why causal claims are context (...) sensitive, what they are sensitive to, and where they are sensitive to it. (shrink)

In this contribution, I explore the possibility of characterizing the emergence of time in causal set theory (CST) in terms of the growing block universe (GBU) metaphysics. I show that although GBU seems to be the most intuitive time metaphysics for CST, it leaves us with a number of interpretation problems, independently of which dynamics we choose to favor for the theory —here I shall consider the Classical Sequential Growth and the Covariant model. Discrete general covariance of the CSG (...) dynamics does not allow us to individuate a single history of the universe (defined by a causal history of different causal sets), thereby making the claim that ‘the past exists’ at best problematic. In addition, because the evolution of the universe in CSG dynamics leads to an outward branching causal tree, it becomes impossible to determine a proper ‘line of becoming’, thereby blurring the presentists’ claim that only the present exists. Similarly, the covariant approach runs into the same, if not even more severe problems, since each configuration of the universe would amount to a set of possible causal sets, thereby making the individuation of a single configuration of the universe —and thus the physical interpretation of the theory— implausible. (shrink)

This paper argues that causal idealism, the view that causation is a product of mental activity, should be considered a competetitor to contemporary views that incorporate human thought and agency into the causal relation. Weighing contextualism, contrastivism, or pragmatism about causation against causal idealism results in at least a tie with respect to the virtues of these theories.

The classic formulation of causal decision theory (CDT) appeals to counterfactuals. It says that you should aim to choose an option that would have a good outcome, were you to choose it. However, this version of CDT faces trouble if the laws of nature are deterministic. After all, the standard theory of counterfactuals says that, if the laws are deterministic, then if anything—including the choice you make—were different in the present, either the laws would be violated or the distant (...) past would be changed. And as several authors have shown, it's easy to transform this upshot of the standard theory of counterfactuals into full-blown counterexamples to CDT. In response to these counterexamples, I argue here that the problem lies, not so much with CDT's guiding idea—that it's the expected causal consequences of your actions that matter for rational decision-making—but with the fact that the classic formulation of CDT doesn't pay sufficient attention to the context-sensitivity of counterfactuals. I develop a contextualist version of CDT which better accounts for this context-sensitivity. And I show that my theory avoids the problems faced by the classic formulation of CDT in determinstic worlds. (shrink)

Many tasks in statistical and causal inference can be construed as problems of entailment in a suitable formal language. We ask whether those problems are more difficult, from a computational perspective, for causal probabilistic languages than for pure probabilistic (or “associational”) languages. Despite several senses in which causal reasoning is indeed more complex—both expressively and inferentially—we show that causal entailment (or satisfiability) problems can be systematically and robustly reduced to purely probabilistic problems. Thus there is no (...) jump in computational complexity. Along the way we answer several open problems concerning the complexity of well-known probability logics, in particular demonstrating the ${\exists \mathbb {R}}$ -completeness of a polynomial probability calculus, as well as a seemingly much simpler system, the logic of comparative conditional probability. (shrink)

We put forth an account for when to believe causal and evidential conditionals. The basic idea is to embed a causal model in an agent’s belief state. For the evaluation of conditionals seems to be relative to beliefs about both particular facts and causal relations. Unlike other attempts using causal models, we show that ours can account rather well not only for various causal but also evidential conditionals.

Causal accounts of scientific explanation are currently broadly accepted (though not universally so). My first task in this paper is to show that, even for a causal approach to explanation, significant features of explanatory practice are not determined by settling how causal facts bear on the phenomenon to be explained. I then develop a broadly causal approach to explanation that accounts for the additional features that I argue an explanation should have. This approach to explanation makes (...) sense of several aspects of actual explanatory practice, including the widespread use of equilibrium explanations, the formulation of distinct explanations for a single event, and the tight relationship between explanations of events and explanations of causal regularities. (shrink)

Our pains can be more or less intense, our mental imagery can be more or less vivid, our perceptual experiences can be more or less striking. These degrees of intensity of conscious experiences are all manifestations of a phenomenal property I call mental strength. In this article, I argue that mental strength is a domain-general phenomenal magnitude; in other words, it is a phenomenal quantity shared by all conscious experiences that explains their degree of felt intensity. Mental (...) class='Hi'>strength has been largely overlooked in favor of mental states’ type, representational contents, domain-specific phenomenology, or processes such as attention. Considering mental strength in our reflections about the mind illuminates debates about the relation of representational contents and phenomenal character, and it also helps address questions about the structure and functions of consciousness. Mental strength provides a unifying construct to model what is shared in the phenomenology of different types of conscious experiences. (shrink)

Causal theories of action, perception and knowledge are each beset by problems of so-called ‘deviant’ causal chains. For each such theory, counterexamples are formed using odd or co-incidental causal chains to establish that the theory is committed to unpalatable claims about some intentional action, about a case of veridical perception or about the acquisition of genuine knowledge. In this paper I will argue that three well-known examples of a deviant causal chain have something in common: they (...) each violate Yablos proportionality constraint on causation. I will argue that this constraint provides the key to saving causal theories from deviant chains. (shrink)

Humans often attribute the things that happen to one or another actual cause. In this chapter, we survey some recent philosophical and psychological research on causal attribution. We pay special attention to the relation between graphical causal modeling and theories of causal attribution. We think that the study of causal attribution is one place where formal and experimental techniques nicely complement one another.

Causal exclusion arguments are taken to threaten the autonomy of the special sciences, and the causal efficacy of mental properties. A recent line of response to these arguments has appealed to “independently plausible” and “well grounded” theories of causation to rebut key premises. In this paper I consider two papers which proceed in this vein and show that they share a common feature: they both require causes to be proportional to their effects. I argue that this feature is (...) a bug, and one that generalises: any attempt to rescue the autonomy of the special sciences, or the efficacy of the mental, from exclusion worries had better not look to proportionality for help. (shrink)

When agents violate norms, they are typically judged to be more of a cause of resulting outcomes. In this paper, we suggest that norm violations also affect the causality attributed to other agents, a phenomenon we refer to as "causal superseding." We propose and test a counterfactual reasoning model of this phenomenon in four experiments. Experiments 1 and 2 provide an initial demonstration of the causal superseding effect and distinguish it from previously studied effects. Experiment 3 shows that (...) this causal superseding effect is dependent on a particular event structure, following a prediction of our counterfactual model. Experiment 4 demonstrates that causal superseding can occur with violations of non-moral norms. We propose a model of the superseding effect based on the idea of counterfactual sufficiency. (shrink)

In The Biopsychosocial Model of Health and Disease, Derek Bolton and Grant Gillett argue that a defensible updated version of the biopsychosocial model requires a metaphysically adequate account of disease causation that can accommodate biological, psychological, and social factors. This present paper offers a philosophical critique of their account of biopsychosocial causation. I argue that their account relies on claims about the normativity and the semantic content of biological information that are metaphysically contentious. Moreover, I suggest that these claims are (...) unnecessary for a defence of biopsychosocial causation, as the roles of multiple and diverse factors in disease causation can be readily accommodated by a more widely accepted and less metaphysically contentious account of causation. I then raise the more general concern that they are misdiagnosing the problem with the traditional version of the biopsychosocial model. The challenge when developing an explanatorily valuable version of the biopsychosocial model, I argue, is not so much providing an adequate account of biopsychosocial causation, but providing an adequate account of causal selection. Finally, I consider how this problem may be solved to arrive at a more explanatorily valuable and clinically useful version of the biopsychosocial model. (shrink)

According to orthodox causal decision theory, performing an action can give you information about factors outside of your control, but you should not take this information into account when deciding what to do. Causal decision theorists caution against an irrational policy of 'managing the news'. But, by providing information about factors outside of your control, performing an act can give you two, importantly different, kinds of good news. It can tell you that the world in which you find (...) yourself is good in ways you can't control, and it can also tell you that the act itself is in a position to make the world better. While the first kind of news does not speak in favor of performing an act, I believe that the second kind of news does. I present a revision of causal decision theory which advises you to manage the news about the good you stand to promote, while ignoring news about the good the world has provided for you. (shrink)

Evidential decision theory (EDT) says that the choiceworthiness of an option depends on its evidential connections to possible outcomes. Causal decision theory (CDT) holds that it depends on your beliefs about its causal connections. While Newcomb cases support CDT, Arif Ahmed has described examples that support EDT. A new account is needed to get all cases right. I argue that an option A's choiceworthiness is determined by the probability that a good outcome ensues at possible A‐worlds that match (...) actuality in the facts causally unaffected by your decision (the “unaffected facts”). Moreover, you should evaluate A on the assumption that A is compossible with the unaffected facts. This view entails that you should use EDT when evaluating A on the assumption that the unaffected facts determine your action, but use CDT when assessing A on the opposite assumption. A's choiceworthiness equals a weighted average of these conditional assessments. The weights are determined by your beliefs about whether the unaffected fact determine your action. This account gets both Newcomb and Ahmed cases right. According to an influential view, whether you take the unaffected facts to determine your action can make a difference to whether you can regard yourself as free and the action as being under your control. While my account is neutral on this issue, it entails that whether you take the unaffected facts to determine your action is important in a different way: it matters to whether you should follow EDT or CDT. (shrink)

The problem of the man who met death in Damascus appeared in the infancy of the theory of rational choice known as causal decision theory. A straightforward, unadorned version of causal decision theory is presented here and applied, along with Brian Skyrms’ deliberation dynamics, to Death in Damascus and similar problems. Decision instability is a fascinating topic, but not a source of difficulty for causal decision theory. Andy Egan’s purported counterexample to causal decision theory, Murder Lesion, (...) is considered; a simple response shows how Murder Lesion and similar examples fail to be counterexamples, and clarifies the use of the unadorned theory in problems of decision instability. I compare unadorned causal decision theory to previous treatments by Frank Arntzenius and by Jim Joyce, and recommend a well-founded heuristic that all three accounts can endorse. Whatever course deliberation takes, causal decision theory is consistently a good guide to rational action. (shrink)