This paper analyses the similarities and connections between philosophy of science and causal layered analysis. The paper points out that philosophy of science can be understood as a kind of causal layered analysis of science. These similarities and connections mean that the insights in philosophy of science can be used to investigate the important but neglected topic of possible futures of science. The connections make it possible (i) to open up the present and past (...) to create alternative futures of science, and (ii) to reveal deep worldview commitments behind surface phenomena in science-related discourses. (shrink)

Contemporary analytical philosophy has not provided historians with an adequate account of their causal reasoning. Attempts to apply the laws of scientific explanation to history have occasioned an artificial split between historical interpretation and historical explanation. The lawlike generalizations of the natural sciences are both perfectly universal and perfectly delimited, whereas the typical generalizations of the historian are imperfectly universal and imperfectly delimited. In historical analysis, a particular development is hypothetically posited as the ordinary course of events, or (...) as the established "trend," and an intervening process or set of conditions is identified as the cause of some alteration in the expected outcome. It is important to differentiate between historical events and the actions of historical figures. The analysis of historical actions requires attention to a second layer of interpretation, that of intention. In a good narrative, everything "important" for the actual outcome will be clearly displayed and cogently ordered in a network of interacting causal sequences; for that is what the historian means when he proposes to "tell the whole story.". (shrink)

This article offers a reading of Eriugena’s thought that is inspired by Heidegger’s claim according to which being is constituted in a dialectical interplay of revelation and concealment. Beginning with an analysis of how “causality as concealing revelation” works on the level of God’s inner-Trinitarian life, the piece moves on to a consideration of the way in which the human soul reveals itself in successive stages of exteriorization that culminate in the creation of the body, its “image.” The body, (...) however, conceals as much as it reveals true human nature. Moreover, it is shown that for Eriugena all of reality, as theophany, possesses this character of concealing its fundamental truth. These insights lead Eriugena to a recognition of radical human finitude, as genuine wisdom requires an acknowledgement of our fundamental ignorance. (shrink)

This study highlights deficits in current leadership concepts; and offers new perspectives through the application of a critical realist analysis. Whilst today’s business world is changing and needs effective leadership to survive, nevertheless, leadership is poorly understood, and current leadership research lacks a unified theory or framework. Such a unified framework is suggested here, based on a layered ontology of leadership. It argues that the causal configuration of leadership – the multiple interacting causes that result in its (...) emergence – is best understood as the interplay between the key mechanism of power, along with human agency and collaborative agency, within specific structural and contextual conditions. This explanation requires a critical realist design of a layered ontology; it would not be possible from the perspectives of either positivism or constructivism. (shrink)

As the demand for explainable deep learning grows in the evaluation of language technologies, the value of a principled grounding for those explanations grows as well. Here we study the state-of-the-art in explanation for neural models for natural-language processing (NLP) tasks from the viewpoint of philosophy of science. We focus on recent evaluation work that finds brittleness in explanations obtained through attention mechanisms.We harness philosophical accounts of explanation to suggest broader conclusions from these studies. From this analysis, we assert (...) the impossibility of causal explanations from attention layers over text data. We then introduce NLP researchers to contemporary philosophy of science theories that allow robust yet non-causal reasoning in explanation, giving computer scientists a vocabulary for future research. (shrink)

We wonder what the role of researchers interested in the imaginary can be in the perspective of futurology. Futurology implements multiple methods to think about the future and, among these various approaches, using two examples, we develop the idea that layered causal analysis has a link with the imaginary, through of the fourth layer devoted to metaphor and myth. We thus show that research on the imaginary has its place in understanding analyzes relating to the future.

Causal mediation analysis is complicated with multiple effect definitions that require different sets of assumptions for identification. This article provides a systematic explanation of such assumptions. We define five potential outcome types whose means are involved in various effect definitions. We tackle their mean/distribution’s identification, starting with the one that requires the weakest assumptions and gradually building up to the one that requires the strongest assumptions. This presentation shows clearly why an assumption is required for one estimand and (...) not another, and provides a succinct table from which an applied researcher could pick out the assumptions required for identifying the causal effects they target. Using a running example, the article illustrates the assembling and consideration of identifying assumptions for a range of causal contrasts. For several that are commonly encountered in the literature, this exercise clarifies that identification requires weaker assumptions than those often stated in the literature. This attention to the details also draws attention to the differences in the positivity assumption for different estimands, with practical implications. Clarity on the identifying assumptions of these various estimands will help researchers conduct appropriate mediation analyses and interpret the results with appropriate caution given the plausibility of the assumptions. (shrink)

Research in evolutionary biology and philosophy of biology and cognition strongly suggests that human organisms modify their environment through active processes of niche construction. Recently, proponents of the free-energy principle and variational active inference have argued that their approach can deepen our understanding of the reciprocal causal relationship between organisms and their niche on various scales. This paper examines the feasibility and scope of variational formalisations and conceptualisations of the organism-niche nexus with a particular focus on the extended active (...) inference account. I will draw a conceptual distinction between selective niche construction, developmental niche construction, and organism-niche coordination dynamics and argue that these notions capture different causal patterns, each of which with a distinct scope. Against this background, I will analyse and discuss the extended active inference account and its strategy to integrate variational active inference with work on extended cognition. The proponents of extended active inference assume that their account can provide an explanation of selective niche construction, developmental niche construction, and organism-niche coordination dynamics. However, my key claim will be that this account has the potential to elucidate the workings of organism-niche coordination dynamics, but does not adequately capture the causal patterns of selective niche construction and developmental niche construction. (shrink)

Estimating the effect of a randomized treatment and the effect that is transmitted through a mediator is often complicated by treatment noncompliance. In literature, an instrumental variable (IV)-based method has been developed to study causal mediation effects in the presence of treatment noncompliance. Existing studies based on the IV-based method focus on identifying the mediated portion of the intention-to-treat effect, which relies on several identification assumptions. However, little attention has been given to assessing the sensitivity of the identification assumptions (...) or mitigating the impact of violating these assumptions. This study proposes a two-stage joint modeling method for conducting causal mediation analysis in the presence of treatment noncompliance, in which modeling assumptions can be employed to decrease the sensitivity to violation of some identification assumptions. The use of a joint modeling method is also conducive to conducting sensitivity analyses to the violation of identification assumptions. We demonstrate our approach using the Jobs II data, in which the effect of job training on job seekers’ mental health is examined. (shrink)

The present paper, taking as a point of departure Aristotle’s dispute with the ancient physicalists in Physics II.8-9 about the role of the final cause in nature, examines the context of the problem, his theory of the causes. Aristotle assumes an analogy between nature and craft and takes the production of artifacts to be paradigmatic. With these assumptions as guiding principles, the paper attempts to motivate his causal theory and propose what may be called a “logic” of the causes. (...) It examines artefactual coming-to-be more closely, focusing on the aspects of Aristotle’s account that are highlighted in his explanation of natural coming-to-be: the basic character of the causes, the peculiar distinction between the causes and the accompanying the deeper coincidence among three of them, the complementarity between the final and moving causes, the nature and role of desire in coming-to-be, and the primacy of form. It introduces the notion of a trans-temporal objective whole and shows the need to consider the full whole — which includes the entire process of coming-to-be together with its source — as the proper context for a full understanding of coming-to-be. It also points out the importance of the distinction between the objective and subjective perspectives, especially useful in understanding final causality. (shrink)

We live in an information society where the usage, creation, distribution, manipulation, and integration of information is a significant activity. Computations allow us to process information from various sources in various forms and use the derived knowledge in improving efficiency and resilience in our interactions with each other and with our environment. The general theory of information tells us that information to knowledge is as energy is to matter. Energy has the potential to create or modify material structures and information (...) has the potential to create or modify knowledge structures. In this paper, we analyze computations as a vital technological phenomenon of contemporary society which allows us to process and use information. This analysis allows building classifications of computations based on their characteristics and explication of new types of computations. As a result, we extend the existing typologies of computations by delineating novel forms of information representations. While the traditional approach deals only with two dimensions of computation—symbolic and sub-symbolic, here we describe additional dimensions, namely, super-symbolic computation, hybrid computation, fused computation, blended computation, and symbiotic computation. (shrink)

We live in an information society where the usage, creation, distribution, manipulation, and integration of information is a significant activity. Computations allow us to process information from various sources in various forms and use the derived knowledge in improving efficiency and resilience in our interactions with each other and with our environment. The general theory of information tells us that information to knowledge is as energy is to matter. Energy has the potential to create or modify material structures and information (...) has the potential to create or modify knowledge structures. In this paper, we analyze computations as a vital technological phenomenon of contemporary society which allows us to process and use information. This analysis allows building classifications of computations based on their characteristics and explication of new types of computations. As a result, we extend the existing typologies of computations by delineating novel forms of information representations. While the traditional approach deals only with two dimensions of computation—symbolic and sub-symbolic, here we describe additional dimensions, namely, super-symbolic computation, hybrid computation, fused computation, blended computation, and symbiotic computation. (shrink)

Even though potential impacts of political and legal environments of business on ethical behavior of firms (EBOF) have been conceptually recognized, not much evidence (i.e., empirical work) has been produced to clarify their role. In this paper, using Bayesian causal maps (BCMs) methodology, relationships between legal and political environments of business and EBOF are investigated. The unique design of our study allows us to analyze these relationships based on the stages of development in 92 countries around the world. The (...) EBOF models structured through BCMs are used to explain how EBOF in a given country group are shaped by how managers perceive political, legislative, and protective environments of business in these countries. The results suggest that irregular payments and bribes are the most influential factors affecting managers’ perceptions of business ethics in relatively more advanced economies, whereas intellectual property protection is the most influential factor affecting managers’ perceptions of business ethics in less-advanced economies. The results also suggest that regardless of where the business is conducted in the world, judicial independence is the driving force behind managers’ perceptions of business ethics. In addition, the results of this study provide further support for scholars who argue that business ethics is likely to vary among countries based on their socio-economic factors. In addition to its managerial implications, the study provides directions for policy makers to improve the ethical conduct of businesses in their respective countries. (shrink)

One of Stuart Glennan's most prominent contributions to the new mechanist debate consists in his reductive analysis of higher-level causation in terms of mechanisms (Glennan, 1996). In this paper I employ the causal Bayes net framework to reconstruct his analysis. This allows for specifying general assumptions which have to be satis ed to get Glennan's approach working. I show that once these assumptions are in place, they imply (against the background of the causal Bayes net machinery) (...) that higher-level causation indeed reduces to interactions between component parts of mechanisms. I also briefly discuss the plausibility of these assumptions and some consequences for the mechanism debate. (shrink)

The causal impacts of genes and environment on any one biological trait are inextricably entangled, and consequently it is widely accepted that it makes no sense in singleton cases to privilege either factor for particular credit. On the other hand, at a population level it may well be the case that one of the factors is responsible for more variation than the other. Standard methodological practice in biology uses the statistical technique of analysis of variance to measure this (...) latter kind of causal efficacy. In this paper, I argue that: 1) analysis of variance is in fact badly suited to this role; and. (shrink)

In this paper we develop an analysis of dispositions by means of causal Bayes nets. In particular, we analyze dispositions as cause-effect structures that increase the probability of the manifestation when the stimulus is brought about by intervention in certain circumstances. We then highlight several advantages of our analysis and how it can handle problems arising for classical analyses of dispositions such as masks, mimickers, and finks.

As autonomous systems rapidly become ubiquitous, there is a growing need for a legal and regulatory framework to address when and how such a system harms someone. There have been several attempts within the philosophy literature to define harm, but none of them has proven capable of dealing with with the many examples that have been presented, leading some to suggest that the notion of harm should be abandoned and "replaced by more well-behaved notions". As harm is generally something that (...) is caused, most of these definitions have involved causality at some level. Yet surprisingly, none of them makes use of causal models and the definitions of actual causality that they can express. In this paper we formally define a qualitative notion of harm that uses causal models and is based on a well-known definition of actual causality (Halpern, 2016). The key novelty of our definition is that it is based on contrastive causation and uses a default utility to which the utility of actual outcomes is compared. We show that our definition is able to handle the examples from the literature, and illustrate its importance for reasoning about situations involving autonomous systems. (shrink)

We aim to devise a Ramsey test analysis of actual causation. Our method is to define a strengthened Ramsey test for causal models. Unlike the accounts of Halpern and Pearl ([2005]) and Halpern ([2015]), the resulting analysis deals satisfactorily with both over- determination and conjunctive scenarios.

This paper distinguishes between causal isolation robustness analysis and independent determination robustness analysis and suggests that the triangulation of the results of different epistemic means or activities serves different functions in them. Circadian clock research is presented as a case of causal isolation robustness analysis: in this field researchers made use of the notion of robustness to isolate the assumed mechanism behind the circadian rhythm. However, in contrast to the earlier philosophical case studies on (...) class='Hi'>causal isolation robustness analysis (Weisberg and Reisman in Philos Sci 75:106–131, 2008 ; Kuorikoski et al. in Br J Philos Sci 61:541–567, 2010 ), robustness analysis in the circadian clock research did not remain in the level of mathematical modeling, but it combined it with experimentation on model organisms and a new type of model, a synthetic model. (shrink)

Simmias' famous epiphenomenalist analogy of the soul-body relation to the harmony and strings of a lyre leads to Socrates' initial refutation and subsequent prolonged defense of soul's immortality in the Phaedo. It also yields in late antiquity significant treatments of the harmony relation by Plotinus and Porphyry that present a larger context for viewing the nature of harmony in the soul and the psycho-somatic compound. But perhaps the most detailed treatment of the musical analogy, and certainly the most radical, is (...) to be found in Gregory of Nyssa's De Hominis Opificio. Gregory's remarkable development of the musical instrument analogy provides a multi-layered analysis of interrelated causality on the mechanistic, physiological, psycho-somatic and intellectual/spiritual planes. Gregory not only sees mind/soul and body as radically equal and yet multilayered in their mutual development; he also refuses to restrict mind to the brain alone, for all physiological systems, in his view, are holistically and individually expressive of mind's activity. Gregory's theory is more innovative than Augustine's view of the mind/soul-body relation and, in my view, the most important account between Plotinus and Aquinas. (shrink)

In the last 20 years, a stream of research emerged under the label of „complex problem solving“ (CPS). This research was intended to describe the way people deal with complex, dynamic, and intransparent situations. Complex computer-simulated scenarios were as stimulus material in psychological experiments. This line of research lead to subtle insights into the way how people deal with complexity and uncertainty. Besides these knowledge-rich, realistic, intransparent, complex, dynamic scenarios with many variables, a second line of research used more simple, (...) knowledge-lean scenarios with a low number of variables („minimal complex systems“, MCS) that have been proposed recently in problem-solving research for the purpose of educational assessment. In both cases, the idea behind the use of microworlds is to increase validity of problem solving tasks by presenting interactive environments that can be explored and controlled by participants while pursuing certain action goals. The main argument presented here is: both types of systems - CPS and MCS – can only be dealt with successfully if causal dependencies between input and output variables are identified and used for system control. System knowledge is necessary for control and intervention. But CPS and MCS differ in their way of how causal dependencies are identified and how the mental model is constructed; therefore, they cannot be compared directly to each other with respect to the cognitive processes that are necessary for solving the tasks. Knowledge-poor MCS tasks address only a small fraction of the cognitive processes and structures needed for knowledge-rich CPS situations. (shrink)

Abstract In this paper I consider an easier-to-read and improved to a certain extent version of the causal chance-based analysis of counterfactuals that I proposed and argued for in my A Theory of Counterfactuals. Sections 2, 3 and 4 form Part I: In it, I survey the analysis of the core counterfactuals (in which, very roughly, the antecedent is compatible with history prior to it). In section 2 I go through the three main aspects of this (...) class='Hi'>analysis, which are the following. First, it is a causal analysis, in that it requires that intermediate events to which the antecedent event is not a cause be preserved in the main truth-condition schema. Second, it highlights the central notion to the semantics of counterfactuals on the account presented here -- the notion of the counterfactual probability of a given counterfactual, which is the probability of the consequent given the following: the antecedent, the prior history, and the preserved intermediate events. Third, it considers the truth conditions for counterfactuals of this sort as consisting in this counterfactual probability being higher than a threshold. In section 3, I re-formulate the analysis of preservational counterfactuals in terms of the notion of being a cause, which ends up being quite compact. In section 4 I illustrate this analysis by showing how it handles two examples that have been considered puzzling – Morgenbesser's counterfactual and Edgington's counterfactual. Sections 5 and on constitute Part II: Its main initial thrust is provided in section 5, where I present the main lines of the extension of the theory from the core counterfactuals (analyzed in part I) to counterfactuals (roughly) whose antecedents are not compatible with their prior history. In this part II, I elaborate on counterfactuals that don't belong to the core, and more specifically on so-called reconstructional counterfactuals (as opposed to the preservational counterfactuals, which constitute the core counterfactual-type). The heart of the analysis is formulated in terms of processes leading to the antecedent (event/state), and more specifically in terms of processes likely to have led to the antecedent, a notion which is analyzed entirely in terms of chance. It covers so-called reconstructional counterfactuals as opposed to the core, so-called preservational counterfactuals, which are analyzed in sections 2 and 3 of part I. The counterfactual probability of such reconstructional counterfactuals is determined via the probability of possible processes leading to the antecedent weighed, primarily and roughly, by the conditional probability of the antecedent given such process: The counterfactual probability is thus, very roughly, a weighted sum for all processes most likely to have led to the antecedent, diverging at a fixed time. In section 6 I explain and elaborate further on the main points in section 5. In section 7 I illustrate the reconstructional analysis. I specify counterfactuals which are so-called process-pointers, since their consequent specifies stages in processes likely to have led to their antecedent. I argue that so-called backtracking counterfactuals are process-pointers counterfactuals, which fit into the reconstructional analysis, and do not call for a separate reading. I then illustrate cases where a speaker unwittingly employs a certain counterfactual while charitably construable as intending to assert (or ‘having in mind’) another. Here I also cover the issue of how to construe what one can take as back-tracking counterfactuals, or counterfactuals of the reconstructional sort, and more specifically, which divergence point they should be taken as alluding to (prior to which the history is held fixed). Some such cases also give rise to what one can take as a dual reading of a counterfactual between preservational and reconstructional readings. Such cases may yield an ambiguity, where in many cases one construal is dominant. In section 8 I illustrate the analysis by applying it to the famous Bizet-Verdi counterfactuals. This detailed analysis of counterfactuals (designed for the indeterministic case) has three main distinctive elements: its being chance-based, its causal aspect, and the use it makes of processes most likely to have led to the antecedent-event. This analysis is couched in a very different conceptual base from, and is an alternative account to, analyses in terms of the standard notion of closeness or distance of possible worlds, which is the main feature of the Stalnaker-Lewis-type analyses of counterfactuals. This notion of closeness or distance plays no role whatsoever in the analysis presented here. (This notion of closeness has been left open by Stalnaker, and to significant extent also by Lewis's second account.) . (shrink)

Residual confounding is a common source of bias in observational studies. In this article, we build upon a series of sensitivity analyses methods for residual confounding developed by Brumback et al. and Chiba whose sensitivity parameters are constructed to quantify deviation from conditional exchangeability, given measured confounders. These sensitivity parameters are combined with the observed data to produce a “bias-corrected” estimate of the causal effect of interest. We provide important generalizations of these sensitivity analyses, by allowing for arbitrary exposures (...) and a wide range of different causal effect measures, through the specification of the target causal effect as a parameter in a generalized linear model with the arbitrary link function. We show how our generalized sensitivity analysis can be easily implemented with standard software, and how its sensitivity parameters can be calibrated against measured confounders. We demonstrate our sensitivity analysis with an application to publicly available data from a cohort study of behavior patterns and coronary heart disease. (shrink)

Yarkoni argues that one solution is to abandon quantitative methods for qualitative ones. While we agree that qualitative methods are undervalued, we argue that both are necessary for thoroughgoing psychological research, complementing one another through the use of causal analysis. We illustrate how directed acyclic graphs can bridge qualitative and quantitative methods, thereby fostering understanding between different psychological methodologies.

The most common way of analysing the meaning of causal generalisations relies on referentialist semantics. In this article, we instead develop an analysis based on inferentialist semantics. According to this approach, the meaning of a causal generalisation is constituted by the web of inferential connections in which the generalisation participates. We distinguish and discuss five classes of inferential connections that constitute the meaning of causal generalisations produced in policy-oriented economic research. The usefulness of our account is (...) illustrated with the analysis of generalisations about unemployment put forward by the Organisation for Economic Co-operation and Development in its highly influential 1994 OECD Jobs Study. The article ends with a discussion of some crucial philosophical questions about the use of inferentialism in the analysis of causal generalisations. (shrink)

This article is focused on the theory of nature (ṭabʽ) advocated by some of the early Muʽtazilī scholars such as Muʻammar b. ʽAbbād al-Sulamī (d. 215/830), Abū Isḥāq al-Naẓẓām (d. 231/845), Abū ʽUthmān al-Jāḥiẓ (d. 255/869) and Abū al-Qāsim al-Kaʽbī (d. 319/931) and its consequences about causality and miracle. The supporters of the ṭabʽ theory argue that Allah creates all beings with innate and permanent natures and these natures determine all movements and events in universe, and that necessary causal (...) relationships based on it prevail in the universe. But this understanding was criticized and rejected by the majority of Muslim theologians. The focal point of the criticism is God’s agency and His relationship with the universe. The acceptance of such necessary causality in the universe would make it impossible for God to intervene in nature, that is to create a miracle. So, miracles will be the work of the place where it occurs like all other acts when the concept of nature is accepted. In this case, it will not be possible to prove the omnipotence of God and belief in prophethood, which forms the basis of two principles of Islamic belief. This study deals with the dimensions of compulsory causality in the thought of naturalist Muslim theologians by addressing two questions: how the issue of miracle is grounded, and whether a divine intervention in nature of entities is possible. (shrink)

In a recent paper Causal Asymmetry, Douglas Ehring has proposed an intriguing solution to the vexing problem of causal asymmetry. The aim of this paper is to show that his theory is not satisfactory. Moreover, the examples that I use in showing the defect of Ehring's theory also indicate that the counterfactual analysis of causation has a problem that cannot be remedied by Marshall Swain's suggested refinement of the counterfactual analysis of causation in Causation and Distinct (...) Events. (shrink)

In social science, one objection to causal analysis is that the assumption of the closure of the system makes the analysis too narrow in scope, that is, it considers only 'closed' and 'hermetic' systems thus neglecting many other external influences. On the contrary, system analysis deals with complex structures where every element is interrelated with everything else in the system. The question arises as to whether the two approaches can be compatible and whether causal (...) class='Hi'>analysis can be integrated into the broader framework of system analysis. This article attempts a negative answer on the grounds of fundamental differences in their assumptions and suggests using system analysis as a post-hoc comparative tool. (shrink)

Recent philosophical studies of probabilistic causation and statistical explanation have opened up the possibility of unifying philosophical approaches with causal modeling as practiced in the social and biological sciences. This unification rests upon the statistical tools employed, the principle of common cause, the irreducibility of causation to statistics, and the idea of causal process as a suitable framework for understanding causal relationships. These four areas of contact are discussed with emphasis on the relevant aspects of causal (...) modeling. (shrink)

Randomized controlled trials are often considered the gold standard for estimating causal effect, but they may lack external validity when the population eligible to the RCT is substantially different from the target population. Having at hand a sample of the target population of interest allows us to generalize the causal effect. Identifying the treatment effect in the target population requires covariates to capture all treatment effect modifiers that are shifted between the two sets. Standard estimators then use either (...) weighting, outcome modeling, or combine the two in doubly robust approaches. However, such covariates are often not available in both sets. In this article, after proving L 1 {L}^{1} -consistency of these three estimators, we compute the expected bias induced by a missing covariate, assuming a Gaussian distribution, a continuous outcome, and a semi-parametric model. Under this setting, we perform a sensitivity analysis for each missing covariate pattern and compute the sign of the expected bias. We also show that there is no gain in linearly imputing a partially unobserved covariate. Finally, we study the substitution of a missing covariate by a proxy. We illustrate all these results on simulations, as well as semi-synthetic benchmarks using data from the Tennessee student/teacher achievement ratio, and a real-world example from critical care medicine. (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)

Recent studies on probabilistic causation and statistical explanation (Cartwright 1979; Salmon 1984), I believe, have opened up the possibility of a genuine unification between philosophical approaches and causal modeling (CM) in the social, behavioral and biological sciences (Wright 1934; Blalock 1964; Asher 1976). This unification rests on the statistical tools employed, the principle of common cause, the irreducibility of causation to probability or statistics, and the idea of causal process as a suitable framework for understanding causal relationships. (...) The aim of this paper is to draw attention to these four areas of contact by focusing on the relevant aspects of CM.Causal analysis in the social sciences is based on two fundamental notions: model and method. A causal model is an idealized picture of the causal relationships in the world. Method, on the other hand, refers to certain statistical techniques that are used to evaluate and test a causal model using data which consist of joint observations on the model variables. (shrink)

A naturalistic theory of rationalization is defended against a fundamental objection. The theory claims that: The rationalizing relation can be fully analysed in causal explanatory terms. However, is rendered problematic by the fact that: Rationalizations exhibit a higher degree of intensionality than ordinary physical causal explanations. To show that can be maintained in the face of , I develop an account of on which and may be reconciled. ;The opening chapter gives an account of the intensionality of ordinary (...) physical causal explanations by developing a counterfactual analysis of causal relevance. Chapter II examines the nature and intensionality of rationalizations. It is argued that despite , a rationalization partly involves a causal relevance relation between its explanans and explanandum. ;In Chapter III, I consider an argument which implies that is false: Davidson's argument that there can be no psychophysical laws. An attempt is made to give a clear and compelling representation of this argument. As I interpret it, the argument depends on the alleged insolubility of the problem of causal deviance in action. ;Chapter IV develops a general theory of deviance according to which any functional system may produce output in a deviant way, and applies this theory to agents. A negative consequence of the theory is that an action may be performed in a deviant way even if the agent's intention causally explains the action . A positive consequence of the theory is that an action is performed in a non-deviant way just in case there is an appropriate causal explanation of why the agent's intention causes him to act. My specific suggestion is that an agent performs an action in a non-deviant way when and only when his intention causes him to act because he "knows how" to act in that way. ;In the last chapter, it is argued that our solution to the problem of deviance can be adapted to account for in causal explanatory terms. In this way and are reconciled. (shrink)

To claim that x was the cause of y is 1) to assume that x was one of a number of things, each of which together with the others was sufficient to have brought about y, and 2) to deem x responsible for the occurrence of y. A best-explanation argument, including application to cases, is offered in defense of this analysis, which holds that claiming that something is the cause is, in part, a speech act that reflects the cause (...) selector’s values or perspectives. No proposed alternative explanation accounts for all the cases with which I am familiar, but this analysis does account for them. Thus the analysis and the defense of sole singular causal claims call for more than empirical evidence, though of course evidence is very important. (shrink)

This article illustrates Sheila Dow's notion of ‘structured pluralism’ drawing on a recent empirical body of literature in which multiple research, or ‘Q-Squared’, approaches to causal analysis of poverty analysis have been used in the Global South. It maintains that understanding linguistic differences between schools of thought is quite integral to methodologically-aware critique and to improved methodological practice. The various strands in the Q2 literature together provide a case for methodological pluralism based on claims that knowledge is (...) partial, empirical adjudication is imperfect, the world is complex and combining multiple research approaches adds value. The goals of understanding and explanation are best served if research questions dictate choice of methodological approach rather than the other way around. (shrink)

The total electron content in the ionosphere widely influences Global Navigation Satellite Systems especially for critical applications by inducing localized positional errors in the GNSS measurements. These errors can be mitigated by measuring TEC from stations located around the world at various temporal and spatial scales and using them for advanced forecasting of TEC. The TEC can be used as a tool in understanding space weather phenomena such as geomagnetic storms which cause disruptions in the ionosphere. This paper examines the (...) causal relationship between perturbations in TEC caused by geomagnetic storms. The causality between two geomagnetic indices auroral electrojet and disturbed storm index and TEC is investigated using Granger causality at two low-latitude stations, Bangalore and Hyderabad. The outcomes of this study strengthen the regional understanding and modeling of ionospheric parameters which can contribute towards the global efforts for modeling and reducing the ionospheric effects on trans-ionospheric communication and navigation. The causal inferences combined with the data-driven model can be useful in identifying the correct and informative physical quantities to improve the forecasting models. (shrink)

Considering the growing need for formal counterparts of causal nexus (AI is desperately looking for a good one!) and thus trying to construct appropriate relations within a formal framework one faces the problem that the notion of “causal connection” is by no means explained with sufficient precision. How to overcome the resulting difficulties?

The debate on empirical tests of social mechanisms suffers from a fragmented view on the relative benefit of the empirical method a researcher considers to be superior, compared to the flaws of all other methods. In this outlook. I argue that disciplinary barriers might be surmounted by a common methodological perspective on the analysis of social mechanisms. First, experimental, quantitative, qualitative, and simulation methods (agent-based modeling) are all required, but also capable to deal with the issue of causal (...) identification, respectively. Second, having established causal identification (among which I subsume strategies to deal with causal heterogeneity). each method disposes of genuine techniques to deal with the most crucial property of mechanism-based explanations: input-mechanism-output (IMO) relations. (shrink)

When people make judgments about the effects of a perturbation on populations of species in a food web, their judgments exhibit the dissipation effect: a tendency to judge that effects of the perturbation weaken or dissipate as they spread out through the food web from the locus of the perturbation. In the present research evidence for two more phenomena is reported. Terminal locations are points in the food web with just a single connection to the rest of the web. Judged (...) changes tended to be higher for species at terminal locations than for species the same distance from the perturbation but at nonterminal locations. Branches are points in the web where a route splits into two or more routes. Judged changes tended to be lower for species following branching points than for species the same distance from the perturbation but not following branching points. It is proposed that the findings can be explained as effects of a mental model employing concepts of influence and resistance. Under this model a perturbation is a change in energy level at a point in the system that acts as an influence affecting the rest of the system. The basic concepts in this model are domain‐general and on that basis it is predicted that the dissipation effect should be found in judgments of any physical system to which notions of influence and resistance can be applied. (shrink)