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To which ‘God’ do philosophers refer? In dialogue with Schellenberg and his insightful distinction between “ultimism” and “theism,” this chapter examines the limits of the natural horizon of inquiry into ultimacy. To think adequately about God the creator entails subverting the natural horizon of thought in order to understand the natural whole as a pointer or deferred ostension of its ultimate source.
Symptom network analysis is now commonly used in psychopathology research. Network analysis results in networks with symptoms represented as nodes, while edges represent conditional associations between these. Direct causal relations between symptoms will produce nonzero conditional associations, but these associations can also be produced in other ways. In this chapter, Borsboom discusses six plausible mechanisms that could produce edges in symptom networks. The first is resource competition, where the presence of a symptom depletes resources, which causes another symptom to arise. The second is evidential overlap, in which judgments central to different symptoms involve a subjective assessment of the same evidence. The third is shared mechanisms, in which symptomatology involves processes that are shared among different symptoms. The fourth are consistency drives, which arise when individuals are prone to align their cognitions, affect states, and behavior. The fifth are statistical processes involved in research design and analysis (marginalization and conditioning). The sixth is the presence of unobserved common causes that affect multiple symptoms at the same time. The author argues that, in realistic situations, the mechanisms in question are not mutually exclusive, which preempts standard scientific approaches that pit one model against another to derive critically divergent predictions. Instead, making sense of symptom networks will require more advanced theory development and modeling.
This chapter seeks to examine and further clarify the relationship between two main conceptual approaches to causality in psychiatric research: counterfactual and mechanistic. The author suggests that psychiatry may pose some relatively unique challenges for causal inference not shared with other branches of medicine. At their core, counterfactual approaches ask “what if” questions while mechanistic approaches ask “how” questions. The chapter also seeks to evaluate the Russo-Williamson Thesis for psychiatric research, which argues that causal inference requires evidence of counterfactual and mechanistic causal effects, by examining three research papers that examine causal effects on psychiatric disorders. Two of these are from epidemiological samples and employ counterfactual methods, and one is from molecular genetics and molecular neuroscience and utilizes a mechanistic approach. Kendler argues that these two methods are complementary and often mutually reinforcing. In particular, the demonstration of counterfactual evidence of causation naturally raises the question of how such an effect occurs at a mechanistic level. However, the author suggest that the Russo-Williamson Thesis is too high a threshold for psychiatry and that, in at least some cases, high-quality counterfactual evidence can be actionable.
Four load-bearing concepts delineate the specificity of wantonness in eighteenth-century Britain: motion, causality, selfhood, and form. This Introduction defines the literary sensorimotor as an array of ancient and modern theories about how words conjure vivid kinetic and proprioceptive imagery for readers. The critic John Dennis argued that powerful motor imagery depended on a reader not being able to pin down the causes of their intense and immersive reading experience. Johnson’s Dictionary defines movement that does not spring from clear causes or intentions as “wanton” motion: neither beautiful nor terrifying but nevertheless vibrant and irregular. Historically, legal wantonness fell somewhere between negligence and recklessness on the spectrum of intentionality. In opposition to the notion that deportment “discovered” a person’s true self, Landreth’s theorization of vital impersonality embraces non-normative embodiment and resists narrative norms of literary interiority. How a character or plot moves might be more important than why.
Isaiah Berlin argues that philosophy has a distinctive task, one which cannot be appropriated by the natural sciences. One of the reasons Berlin gives for holding that philosophy’s task falls outside the scope of science is that its area of reflection essentially employs normative concepts. An understanding of the human agent must, in the end, encompass an understanding, not only of meaning and intentional action but of the moral, political and aesthetic life of fully acculturated human beings. Although Berlin’s historical approach to this task was highly distinctive, his aims and his convictions concerning the relation between philosophy and science, the central place of the human agent in philosophy, and his anti-reductive, anti-positivist approach were shared with a number of his Oxford contemporaries, in particular G. E. M. Anscombe and P. F. Strawson. In this chapter, I look at how these three philosophers understand the nature of philosophy and the relation between philosophy and science, focusing particularly on their attitude to the topic of determinism.
This paper investigates the empirical implications of the broadest Divisia-type monetary aggregates. We first analyze the simple causal relationship between real economic variables and a range of monetary aggregates, then estimate both a traditional recursive VAR model and a non-recursive VAR model. By examining impulse responses and the equational forms of underlying economic shocks, we gain insights into the implications of various monetary aggregates. Our findings indicate that the broadest Divisia-type monetary aggregates exhibit strong causality with various real economic variables. Furthermore, the structural equations obtained from non-recursive VAR estimation suggest that the Money-interest rate rule, centered on money as a primary policy instrument, yields results precisely consistent with the benchmark across almost all ranges of credit-card-augmented Divisia monetary aggregates. Under this rule, the broadest credit-card-augmented Divisia monetary aggregate enhances the precision of tracking contemporary economic conditions and mitigates common anomalies, such as puzzle problems.
Hyperuricemia is a common metabolic disorder and has become a global health concern. This study investigated the association between DNA methylation (DNAm) and serum uric acid (SUA) by conducting an epigenomewide association study (EWAS) in Chinese monozygotic (MZ) twins. Genomewide DNAm of 50 MZ twin pairs was profiled using the Infinium MethylationEPIC v2.0 BeadChip (935K). Generalized estimating equations (GEE) were used to examine the association between DNAm and SUA. Causal relationships between DNAm and SUA were assessed using ICE FALCON approach. Associations between mRNA expression and SUA were further assessed. Finally, candidate genes identified through epigenomewide association study (EWAS), causal inference, and gene expression analyses were validated in a longitudinal twin study. We identified 70 CpGs, mapping to genes such as DOK6 and NGLY1, significantly associated with SUA (Bonferroni correction p < 5.8 × 10−8). Causal analyses revealed one CpG with a causal effect of DNAm on SUA, 22 CpGs with causal effects of SUA on DNAm, and 33 CpGs showing bidirectional causality. Eleven genes displayed expression levels associated with SUA. DOK6, NGLY1, PKM, and SLC44A1 were selected as candidate genes, all of which showed unidirectional causal effect of SUA on DNAm. In the longitudinal analysis, baseline SUA levels (2012–13) were associated with subsequent DNAm levels in DOK6 and NGLY1 genes (2023–24). In conclusion, we found that SUA levels may influence DNAm variations, particularly at CpG loci within the DOK6 and NGLY1 genes. These findings provide key clues for future investigations into the mechanisms linking SUA with its epigenetic regulatory pathways.
This chapter describes the state of the data on terrorism and isolates some of the key factors associated with the number of terror attacks using a random forest machine learning algorithm. The variables that emerge include several policy outcomes such as health expenditures, anti-government demonstrations, income inequality, democratic accountability, and strikes. Using the example of income inequality we show how model-agnostic machine learning algorithms can uncover nonlinear associations in the determinants and in doing so can improve our measurement and understanding of the nature of causality.
This chapter introduces structural equation models (SEMs). It defines SEMs and outlines their history. It also presents several widespread misunderstandings about SEMs and presents their strengths and weaknesses. Finally, the chapter provides an outline of the remaining book chapters.
This chapter focuses on the core issues concerning the doctrine of creation that were debated by early scholastic theologians. These include the view that God brought the world into being from nothing; that God created everything, all at once; and that creation occurred at the beginning of time.
If you examine the changing contexts in which the issue of ‘relevance’ has been posed in the profession, it becomes clear how earlier calls for relevance need to be reconfigured today. After reviewing arguments that show how explanatory/normative activity is intercoded, this essay explores how the accelerated pace of life, new densities of interdependence and a growing fragility of things supports the case for forging alliances between political science and recent developments in complexity theory in a number of allied fields.
The use of multimethod research is becoming increasingly widespread in the social sciences, including political science, and it is part of a broader movement that has moved beyond the single focus on either qualitative or quantitative studies. In Multimethod Research, Causal Mechanisms, and Case Studies: An Integrated Approach, Gary Goertz lays out a comprehensive approach to multimethod research and to the use of case studies. The aim is to integrate qualitative and quantitative research—for instance through case studies—and to show the advantages of combining the two. Goertz does so by bringing together causal mechanisms, cross-case causal inference and within-case causal inference into what he calls the research triad of this integrated approach to social science research. In their reviews of Goertz’ book, David Waldner, Jennifer Cyr and Kendra Koivu take issues with particular aspects of Goertz’ case for multimethod and case study research, while also addressing larger methodological issues surrounding political science research.
Social scientists often face a fundamental problem: Did I leave something causally important out of my explanation? How do I diagnose this? Where do I look for solutions to this problem? We build bridges between regression models and qualitative comparative analysis by comparing diagnostics and solutions to the problem of omitted variables and conditions. We then discuss various approaches and tackle the theoretical issues around causality which must be addressed before attending to technical fixes. In the conclusions, we reflect on the bridges built between the two traditions and draw more general lessons about the logic of social science research.
Chapter 1 begins by introducing the quantum world as part of the physical world, not in opposition to or separate from the classical world. It then introduces the basic tools needed to work with quantum mechanics, and describes the scope and purpose of this textbook. It discusses how despite its successes, current quantum mechanics lacks adequate explanations for important observed atomic properties, suggesting an incompleteness of the theory. After a brief overview of its main interpretative issues , the chapter concludes with an introduction of the vacuum or zero-point field as the physical element that restores causality and serves to complete the quantum picture by providing a causal explanation of characteristic quantum phenomena.
This chapter reviews the main concepts of electromagnetic theory relevant for the understanding of this textbook. Based on Maxwell’s equations, we derive the wave equation and discuss homogeneous solutions, such as plane waves and evanescent waves. We derive the boundary conditions at interfaces between homogeneous media and the Fresnel reflection and transmission coefficients. We discuss energy conservation, causality, and reciprocity of electromagnetic fields. Point response functions are introduced (Green functions) in order to derive the inhomogeneous solution of the wave equation. The chapter concludes with the angular spectrum representation, a framework that allows arbitrary fields to be described as a superposition of plane and evanescent waves.
Chapter 3 concentrates on the semiotics of onomatopoeia, mainly the frequently discussed issues of iconicity, arbitrariness, and motivation. It is claimed that rather than opposing terms, arbitrariness and motivation are complementary notions. It introduces the concept of causality into the discussion of the nature of onomatopoeia as linguistic signs. The chapter discusses five basic oppositions: causality versus noncausality; arbitrariness versus nonarbitrariness; iconicity versus non-iconicity; motivation versus lexicalization; and conventionalization versus nonconventionalization. Considerable attention is paid to the views that criticize Saussure’s comprehension of onomatopoeia and his concept of arbitrariness. Arguments are presented in support of Saussure’s position. In addition, Peirce’s triad of hypo-icons (image, diagram, metaphor) is discussed in terms of their relevance to the characterization of onomatopoeias.
According to Suárez, each of Aristotle’s four causes counts as a cause because it inflows being to another, and each has a proper influx. Several scholars regard Suárez’s account of the influx of the final cause as unsatisfactory. These interpreters overlook his identification of the influx of a cause with its causality, and his view that the causality of a cause is an entity, a res or a mode. I argue that, on Suárez’s view, the influx or causality of the final cause is a component of the mode of action, and that this account satisfies the demands of his influx theory of cause. I also uncover some unfamiliar elements of Suárez’s view of final causality: that it is simultaneous with efficient causality and that, wherever an end is a real cause of some effect, its causality is an intrinsic feature of the action by which that effect is produced.
Final causation is a keenly discussed topic in early modern philosophy, and one of the most controversial quaestiones concerns the end’s causality, i.e., the way in which an end really causes. The question brought into play the status of the end as a cause and required coming to terms with an increasingly efficiency-based view of general causation. Suarez holds that the end’s causality is a metaphorical motion, as many Aristotelians before him did; however, how this motion had to be understood was open to discussion, as Suarez shows by considering several alternatives before settling on his own view of metaphorical motion as the end’s drawing of the will to itself concomitantly to the will exercising a physical motion. Aside from allowing a glimpse on Suarez’s way of navigating the philosophical landscape, Suarez’s account of the end’s causality connects to several other key features of his metaphysics.
Multivariable analysis is needed because most events, whether medical, politica, social, or personal, have multiple causes. And these causes are related to one another. Multivariable analysis enables us to determine the relative contributions of different causes to a single event or outcome.
Multivariable analysis enables us to identify and adjust for confounders. Confounders are associated with the risk factor and causally related to the outcome. Adjustment for confounders is key to distinguishing important etiologic risk factors from variables that only appear to be associated with outcomes due to their association with the true risk factor.
Stratification can also be used for identifying independent relationships between risk factors and outcomes but becomes too cumbersome when there are more than one or two possible confounders.
This chapter presents Ockham’s theory of demonstration in Summa Logicae III-2, the syllogism that produces scientific knowledge. He relies on Aristotle’s Posterior Analytics and Grosseteste’s commentary it. Grosseteste, however, founded the necessity of demonstration on necessary relations in the world. For Ockham, the main challenge is to elaborate a theory of science that addresses the singular beings in a contingent world. His theory is characterized by a conception of purely logical necessity, a semiotic conception of cause, and the requirement that subject terms must have reference in order for affirmative propositions to be true. Many propositions about the natural world are not susceptible to demonstration in the strict sense, but Ockham distinguishes different kinds of demonstration. He is not so much trying to limit the field of demonstrable natural knowledge as to relax the meaning of demonstrability so that it includes many dubitable propositions that can be made evident.