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Chapter 1 introduces evolution theory and evolutionary explanation for studies of East Asian international relations and lays out the design of the whole book
Hegel’s Philosophy of Nature is integrated into the fabric of his system. We absorb into our thinking the concepts and relationships that have survived the successes and failures of experience (Phenomenology). Through disciplined thought we articulate the internal logic of those concepts (Logic). By working out what the world beyond thought would be like, seeing how the world instantiates those expectations, and then building those discoveries into our next ventures, we develop a systematic picture of the stages of natural complexity and human functioning (Philosophies of Nature and Spirit). Since Hegel’s time, however, we have discovered that nature has a history; time and space are no longer absolutes; the discoveries of science have expanded in both breadth and detail; and our comprehensive explanations for the way the world functions are continually being falsified by the discovery of new facts. A philosophy of nature, then, needs to reshape the way reason functions. Adopting the strategies we use to solve problems and that science uses to develop and test hypotheses, we broaden our perspective to cover multiple domains in nature and search for patterns that show how and why they fit together as they do.
The chapter begins with the observation that global history has an ambivalent attitude towards explanation. In many cases, the mere presentation of sources and voices from many different parts of the world seems sufficient to justify a global approach. The need for explanation is ignored or even denied. In other cases, global explanation is eagerly pursued, but often at the expense of more complex explanatory models that incorporate factors at different scales. In this perspective, global explanations are claimed to be inherently superior and a privileged way of explaining historical phenomena. After a cursory survey of current positions on causality and explanation in general methodology and ‘formal’ historical theory, the chapter proposes a brief typology of explanatory strategies. It goes on to discuss the peculiarities of explanation within a framework of connections across great distances and cultural boundaries. The much-exclaimed concept of narrative explanation is found to be of limited value, as it underestimates the difficulties of producing coherent narratives on a global scale. Concepts offered in the social science literature, such as the analysis of mechanisms and temporal sequences, could be helpful in refining purely narrative approaches to explanation.
Bas van Fraassen has argued that explanatory reasoning does not provide confirmation for explanatory hypotheses because explanatory reasoning increases information and increasing information does not provide confirmation. We compare this argument with a skeptical argument that one should never add any beliefs because adding beliefs increases information and increasing information does not provide confirmation. We discuss the similarities between these two arguments and identify several problems with van Fraassen’s argument.
The chapter delves into the specific kind of understanding aimed at in medicine, starting from the Understanding Thesis. Drawing on recent work by Broadbent (2019), debates in the epistemology of understanding (Kvanvig 2009; Grimm 2012; Khalifa 2017), and scholarship on the aims of inquiry, the chapter unpacks what it means to understand something, differentiating types of understanding, and using the history of scurvy to explore understanding a disease in medicine. The hypothesis is that biomedical understanding of a disease requires grasping a mechanistic explanation of the disease. This understanding of causal and constitutive relationships draws on an influential account of causation (Woodward 2003; 2010; 2015) and work on mechanistic explanations in biological sciences and neuroscience (Thagard 2003; 2005; Craver 2007; Nervi 2010; Kaplan and Craver 2011; Darrason 2018). However, it argues that biomedical understanding is necessary but not sufficient for clinical understanding, which combines biomedical understanding of a disease with personal understanding of an illness. This chapter revisits the distinction between "understanding" and "explanation" from debates in the field.
Despite its apparent complexity, our world seems to be governed by simple laws of physics. This volume provides a philosophical introduction to such laws. I explain how they are connected to some of the central issues in philosophy, such as ontology, possibility, explanation, induction, counterfactuals, time, determinism, and fundamentality. I suggest that laws are fundamental facts that govern the world by constraining its physical possibilities. I examine three hallmarks of laws-simplicity, exactness, and objectivity-and discuss whether and how they may be associated with laws of physics.
The Apostle Paul defined the moral values of love, joy, peace, patience, and kindness as 'the fruit of God's Spirit.' Paul Moser here argues that such values are character traits of an intentional God. When directly experienced, they can serve as evidence for the reality and goodness of such a God. Moser shows how moral conscience plays a key role in presenting intentional divine action in human moral experience. He explores this insight in chapters focusing on various facets of moral experience – regarding human persons, God, and theological inquiry, among other topics. His volume enables a responsible assessment of divine reality and goodness, without reliance on controversial arguments of natural theology. Clarifying how attention to moral experience can contribute to a limited theodicy for God and evil, Moser's study also acknowledges that the reality of severe evil does not settle the issue of God's existence and goodness.
Communication of results of research is a critical step in science and entails all the other topics we have covered in relation to methodology. This communication usually is a written report (e.g., for a thesis or dissertation, granting agency, or journal article) or for presentation (e.g., poster session, conference presentation). In these different formats, there are common goals and requirements. In each format, the researcher’s challenge is to convey why the question that guides research is important and the way in which it has been addressed in the study is suitable. Methodology plays major roles throughout the processes of planning, conducting, interpreting, and communicating research results. Three interrelated tasks are involved in preparing a manuscript whether for a thesis, dissertation, presentation or journal article. These were described as description, explanation, and contextualization of the study. The writing we are routinely taught in science focuses on description, but the other portions are central as well and determine whether a study not only appears to be important but also in fact actually is. Recommendations were made regarding what to address and how to incorporate description, explanation, and contextualization within the different sections of a manuscript (e.g., Introduction, Method). In addition, questions were provided to direct the researcher to the types of issues reviewers are likely to ask about a manuscript.
In the recent literature on the nature of knowledge, a rivalry has emerged between modalism and explanationism. According to modalism, knowledge requires that our beliefs track the truth across some appropriate set of possible worlds. Modalists tend to focus on two modal conditions: sensitivity and safety. According to explanationism, knowledge requires only that beliefs bear the right sort of explanatory relation to the truth. In slogan form: knowledge is believing something because it's true. In this paper, we aim to vindicate explanationism from some recent objections offered by Gualtiero Piccinini, Dario Mortini, and Kenneth Boyce and Andrew Moon. Together, these authors present five purported counterexamples to the sufficiency of the explanationist analysis for knowledge. In addition, Mortini devises a clever argument that explanationism entails the violation of a plausible closure principle on knowledge. We will argue that explanationism is innocent of all these charges against it, and we hope that the strength of the defense we offer of explanationism is evidence in its favor, and a reason to investigate explanationism further as the long-elusive truth about the nature of knowledge.
This chapter details the practical, theoretical, and philosophical aspects of experimental science. It discusses how one chooses a project, performs experiments, interprets the resulting data, makes inferences, and develops and tests theories. It then asks the question, "are our theories accurate representations of the natural world, that is, do they reflect reality?" Surprisingly, this is not an easy question to answer. Scientists assume so, but are they warranted in this assumption? Realists say "yes," but anti-realists argue that realism is simply a mental representation of the world as we perceive it, that is, metaphysical in nature. Regardless of one's sense of reality, the fact remains that science has been and continues to be of tremendous practical value. It would have to be a miracle if our knowledge and manipulation of the nature were not real. Even if they were, how do we know they are true in an absolute sense, not just relative to our own experience? This is a thorny philosophical question, the answer to which depends on the context in which it is asked. The take-home message for the practicing scientist is "never assume your results are true."
In response to widespread use of automated decision-making technology, some have considered a right to explanation. In this article, I draw on insights from philosophical work on explanation to present a series of challenges to this idea, showing that the normative motivations for access to such explanations ask for something difficult, if not impossible, to extract from automated systems. I consider an alternative, outcomes-focused approach to the normative evaluation of automated decision making and recommend it as a way to pursue the goods originally associated with explainability.
In Chapter 3 I propose that a literary work “is any text produced for publication or broadcast, and in any genre or format”. This definition offers no assessment of the value or quality of that text because I do not subscribe to the notion that literary works – including in the misnamed genre known as “literary fiction” – are somehow “high brow” or of a higher quality, standard or value than works in other genres. Thus, all mention in this guide of “literary texts” should be read in reference to the full gamut of:
fiction genres – including “genre fiction”, historical fiction, contemporary fiction, young adult fiction, science fiction, fantasy, romance etc.
non-fiction genres – including creative non-fiction, memoir, auto/biography, textbooks, guidebooks, dictionaries and reference works etc.
long-form and short-form texts published electronically and online, including websites, blogs and social media.
People often overestimate their understanding of how things work. For instance, people believe that they can explain even ordinary phenomena such as the operation of zippers and speedometers in greater depth than they really can. This is called the illusion of explanatory depth. Fortunately, a person can expose the illusion by attempting to generate a causal explanation for how the phenomenon operates (e.g., how a zipper works). This might be because explanation makes salient the gaps in a person’s knowledge of that phenomenon. However, recent evidence suggests that people might be able to expose the illusion by instead explaining a different phenomenon. Across three preregistered experiments, we tested whether the process of explaining one phenomenon (e.g., how a zipper works) would lead someone to report knowing less about a completely different phenomenon (e.g., how snow forms). In each experiment, we found that attempting to explain one phenomenon led participants to report knowing less about various phenomena. For example, participants reported knowing less about how snow forms after attempting to explain how a zipper works. We discuss alternative accounts of the illusion of explanatory depth that might better fit our results. We also consider the utility of explanation as an indirect, non-confrontational debiasing method in which a person generalizes a feeling of ignorance about one phenomenon to their knowledge base more generally.
Although the inferring of explanations plays an important role in both our everyday lives and in the workings of science, I argue that inference to the best explanation as it is commonly conceived is often not the best way to capture this sort of reasoning. I suggest that a different form of reasoning – so-called immediate explanatory inference – is instead often much better suited to this task. This is a form of inference in which we are justified in believing explanations for the evidence before us purely in virtue of this evidence, and not in virtue of the evidence plus some general principle or rule of non-deductive reasoning. I defend the idea of such a notion of inference, and argue that it plays a central role in both ordinary life and science.
This Element answers four questions. Can any traditional theory of scientific explanation make sense of the place of mathematics in explanation? If traditional monist theories are inadequate, is there some way to develop a more flexible, but still monist, approach that will clarify how mathematics can help to explain? What sort of pluralism about explanation is best equipped to clarify how mathematics can help to explain in science and in mathematics itself? Finally, how can the mathematical elements of an explanation be integrated into the physical world? Some of the evidence for a novel scientific posit may be traced to the explanatory power that this posit would afford, were it to exist. Can a similar kind of explanatory evidence be provided for the existence of mathematical objects, and if not, why not?
Hegel intends to prove two different claims about purposive connections in his Logic: (1) that teleology is the truth of mechanism and (2) that inner purposiveness is the truth of the external reference-to-an-end. I devote this chapter to the analysis of the first of these arguments. To this end, I introduce Hegel’s concept of ‘mechanism’, whose main ingredient is the idea that mechanisms are determined as causes merely from without. This feature disqualifies mechanisms as self-sufficient explainers. I compare Hegel’s understanding of this shortcoming with Hume’s and Kant’s misgivings about the cognition of causal relations. For Hegel, mechanical causes are in themselves apparent and the relations they maintain with other causes are in themselves contingent. It is this essential contingency of the ‘necessary’ that makes Hegel judge mechanical relations to be untrue. Mechanical objects with indeterminate causal powers appear essentially as means and, hence, hypothetically subordinated to self-determining causes.
Can there be something like a “Wittgensteinian” literary criticism? If so, what could it possibly be, given that Wittgenstein sought to make us give up the craving for generality? Through an analysis of “The Avoidance of Love,” Stanley Cavell’s epochal 1969 essay on King Lear, Toril Moi shows that a reader inspired by Wittgenstein does not have to set out to apply a given theory, or to answer certain “Wittgensteinian” questions. Rather it entails a wish to acknowledge the concerns of the text, and respond to them. For Wittgensteinian critics, the text is not an object to be “approached” but action and expression. The critic sets out to answer questions that matter to her, and stakes herself in her own perceptions and judgments in the act of reading. “The problem of the critic, as of the artist,” Cavell writes, “is not to discount his subjectivity, but to include it; not to overcome it in agreement, but to master it in exemplary ways.” To do this requires training. This chapter sets out the implications of all these claims, argues against formalist views of literature and reading, and insists on the fundamental role of human judgment, and acknowledgment in the work of criticism.
Knowing what event precipitated a client's abnormal behaviors makes the client appear more normal than if the event is not known (Meehl, 1973). Does such knowledge also influence judgments of the need for psychological treatment, and if so, does it matter whether the precipitating event was inside or outside the client's control? We presented undergraduates with cases of hypothetical clients exhibiting abnormal behaviors and manipulated whether they were also told of a precipitating event explaining those behaviors. Knowing the precipitant significantly reduced perceptions of clients’ need for treatment, but only when the precipitating event was outside the client's control. These findings call into question the notion that it need always be beneficial for an outside reasoner to uncover the root cause of a client's psychological problems, particularly when the root cause is still unknown to the client. The rationality of the effect and additional implications for decision-making are discussed.
Previous work showed that people find explanations more satisfying when they contain irrelevant neuroscience information. The current studies investigate why this effect happens. In Study 1 ( N=322), subjects judged psychology explanations that did or did not contain irrelevant neuroscience information. Longer explanations were judged more satisfying, as were explanations containing neuroscience information, but these two factors made independent contributions. In Study 2 ( N=255), subjects directly compared good and bad explanations. Subjects were generally successful at selecting the good explanation except when the bad explanation contained neuroscience and the good one did not. Study 3 ( N=159) tested whether neuroscience jargon was necessary for the effect, or whether it would obtain with any reference to the brain. Responses to these two conditions did not differ. These results confirm that neuroscience information exerts a seductive effect on people’s judgments, which may explain the appeal of neuroscience information within the public sphere.
This paper reports two experiments comparing variants of multiple explanation applied in the early stages of a judgment task (a case involving employee theft) where participants are not given a menu of response options. Because prior research has focused on situations where response options are provided to judges, we identify relevant dependent variables that an intervention might affect when such options are not given. We use these variables to build a causal model of intervention that illustrates both the intended effects of multiple explanation and some potentially competing processes that it may trigger. Although multiple explanation clearly conveys some benefits (e.g., willingness to delay action to engage in information search, increased detail, quality and confidence in alternative explanations) in the present experiments, we also found evidence that it may initiate or enhance processes that attenuate its advantages (e.g., feelings that one does not need more data if one has multiple good explanations).