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.

Theories of change propose how intervention resources and activities might lead to the generation of outcomes. They are sometimes presented diagrammatically as logic models. Realist evaluators and others have suggested that interventions should be theorised in terms of how intervention mechanisms interact with context to generate outcomes. Our own trial of the Learning Together whole-school intervention to prevent bullying set out to define, refine and test such theories in the form of context–mechanism–outcome configurations (CMOCs). We drew on several sources to define our starting CMOCs. These included existing middle range theory. This is scientific theory about the general mechanisms (i.e. not necessarily concerning an intervention) that generate outcomes. This should be analytically general enough to apply to a range of settings, populations and/or outcomes, but specific enough to be useful in a given application. We also used previous research and public consultation to inform our CMOCs.

Why does the science of brain development have such compelling influence on our thinking about children’s development? This question is explored in relation to an important Supreme Court decision concerning adolescent responsibility in which the findings of developmental neuroscience were influential but misleading. In considering this case, the chapter explores the concepts of neurorealism (i.e., brain images provide “visual proof” of the brain’s influence on mental processes) and neuroessentialism (i.e., brain processes are the material basis for mental processes). Then the chapter describes why we are – but should not be – neurodeterminists by showing how the brain and mind are mutually influential in development and that both are affected by experience. The chapter also describes the difficulties of attributing specific mental processes to particular areas of the brain, and considers the importance of context and culture in the development of brain and mind. The chapter shows that without due consideration of the multiple influences on the developing brain and mind, and careful examination of the contexts in which they develop, mistaken applications of developmental brain science are more likely. The clear and accurate communication of the science is thus crucial to public understanding and responsible policy applications.

With Kant’s conception of organisms as “natural ends” nature and freedom are represented as harmoniously cohering with each other thereby giving us a special reassurance of reason’s causal efficacy in nature. For Kant, in order to make organic formations intelligible, we must represent the rule of their organization as reciprocal causality. I contend that this rule of reciprocal causality serves as a schema-analogue of reason’s Idea of absolute freedom. Moreover, I proceed to show that the antinomial conflict of teleological judgment is a conflict between two perspectives on nature: theoretical (scientific) in the thesis and practical in the antithesis. Therefore, the solution to the antinomy does not merely offer a justification for the explanatory compatibility of mechanical and teleological explanation in our representation of a single organic formation but also leads to a view of the world according to which the theoretical and the practical representations of nature “must cohere.”

The Hippocratic treatise Diseases 4 is well known for explaining corporeal processes through vivid analogies with plants, cupping glasses, bronze vessels, swirling wine sediment, coagulating cheese, and blocked oil flasks. Scholars have often applied a heuristic dichotomy to these arguments, evaluating whether they are “mechanistic” (i.e., rely solely on recognizable physical forces) or “vitalistic” (i.e., attribute special capacities to living tissues and parts). Comparisons to implements tend to line up on the former side, while plant analogies support the latter. Rather than focus on delineating these two types of explanations, this chapter emphasizes that the author draws both sets of comparative objects from the therapies, implements, and techniques that a physician would have either administered to the body or encountered in the more general practice of medicine. Whether comparing the attractive capacity of the four inner “springs” (head, heart, gallbladder, spleen) to medicinal plants drawing up particular nutriment from the soil, or likening these same springs to bronze vessels, Diseases 4 amalgamates medical tools and the bodies that they treat. Its view of corporeality therefore emerges at the physical and conceptual interface between flesh and the therapeutic technologies that affect it, as the body absorbs and enfolds medical tools and substances.

Social and behavioral researchers often draw on archival data – data collected by an entity other than the research team – to conduct scientific inquiry. Researchers typically seek to make claims about measured variables that extend beyond the measures themselves, such as interpreting a measure as representing an unobservable theoretical construct. Though researchers using archival data encounter many issues, this chapter focuses on two that have received less attention. The first concerns how researchers should justify the interpretations and uses they attach to archival measures. The second concerns how to justify generalizing findings. This chapter provides a framework to help researchers address these issues by drawing on contemporary validity theory in education and psychology as well as theory regarding causal mechanisms from philosophy and sociology. These concepts are illustrated using multiple examples from published studies.

we have a moral code that meshes with Christianity, why then are we so often non-social and why do we so blatantly disobey the dictates of Jesus Christ? “Love your enemies, bless them that curse you, do good to them that hate you, and pray for them which despitefully use you, and persecute you” (Matthew 5:43–4). Think about it. The Great War (later called the First World War), 1914–1918, between (depending how you count) 20 and 40 million dead. The Second World War, 1939–1945, 60 to 80 million dead. The Russian Civil War, 1917–1922, 5 to 10 million dead. The Chinese Civil War, 1927–1949, 10 million dead. And so it goes. We are not yet at the pogroms, from the Turks killing Armenians, Stalin and the Kulaks, Hitler and the Jews, down to Rwanda and the killing of the Tutsis, not to mention half a million women raped as a preliminary to grotesque mutilation of genitals.

“Just the facts, ma’am. Just the facts!” This famous directive by Sergeant Joe Friday – apparently never actually made in this form – is from the television series Dragnet. Unfortunately, while this may be adequate for detecting and solving crime, not so elsewhere. The idea that science is simply a matter of recording empirical experience is hopelessly inadequate and misleading. Science is about empirical experience, but it is about such experience as encountered and interpreted – and with effort and good fortune – as explained by us.

Let us return to the address to the American Association for the Advancement of Science given in 1967 (later published in Science), by medieval historian Lynn White Jr. He threw down the gauntlet. The son of a Presbyterian minister and himself a lifelong active Presbyterian, White felt nevertheless that his religion had given rise to much that needed answering. “Christianity bears a huge burden of guilt.” White’s thesis is relatively straightforward. Modern science and technology – and the appalling environmental consequences – are the children of the Christian faith. But we get ahead of ourselves. Let’s plunge right into looking at some of these environmental consequences, using as our exemplar the most pressing environmental issue of them all: global warming.

Remember: “Let us make mankind in our image, in our likeness, so that they may rule over the fish in the sea and the birds in the sky, over the livestock and all the wild animals, and over all the creatures that move along the ground” (Genesis 1:26). It is there right at the beginning of the Old Testament; it is also in the New. We are unique and hence have a position superior to other animals. In the Sermon on the Mount, Jesus reaffirms this. “Behold the fowls of the air: for they sow not, neither do they reap, nor gather into barns; yet your heavenly Father feedeth them. Are ye not much better than they?” (Matthew 6:26).

Ask the basic question: Can a Christian be an organicist? And respond with the basic answer: Yes! There are Christians who welcome the idea of an organic Earth, at the least. Thomas Berry, a Catholic priest no less, had a theological vision of the world that made the organic thesis central. “The universe is not a vast smudge of matter, some jellylike substance extended indefinitely in space.

Evolution was both known and generally accepted very rapidly after the Origin. Darwinism, even. In the summer of 1860, Charles Dickens’ widely read weekly, All the Year Round, carried two anonymously published articles on the theme of the Origin (with a third early in the next year).

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.

This chapter starts with a discussion of Hume’s regularity theory of causality, which argues that the idea of necessary connection between two events (i.e., cause and effect) cannot be derived from observing the events and must be derived from an internal impression. Simply put, a causal relation is a mere constant conjunction of events. A counterfactual analysis of causation is based on Hume’s remark that if the cause did not occur, the effect would not exist. Lewis develops the analysis using the concept of possible world. In contrast to Hume’s deterministic view of causation, a probabilistic approach argues that causes raise the probability of − but do not necessarily lead to − their effects. Causal graph modeling and vector spacing modeling are two major techniques of identifying causal relations from empirical data, with the latter being more suitable for management research. A mechanism is a causal chain producing the effect of interest, and process tracing is a technique for identifying mechanisms in qualitative research.

On November 24, 1859, the English naturalist Charles Robert Darwin published On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life . In that book (Darwin 1859), he argued that all organisms, living and dead, were produced by a long, slow, natural process, from a very few original organisms. He called the process “natural selection,” later giving it the alternative name of “the survival of the fittest.” This first chapter is devoted to presenting (without critical comment) the argument of the Origin, very much with an eye to the place and role of natural selection. As a preliminary, it should be noted that the Origin, for all it is one of the landmark works in the history of science, was written in a remarkably “user-friendly” manner. It is not technical, the arguments are straightforward, the illustrative examples are relevant and easy to grasp, the mathematics is at a minimum, meaning non-existent. Do not be deceived. The Origin is also a very carefully structured piece of work (Ruse 1979a). Darwin knew exactly what he was doing when he set pen to paper.

Now we come to the elephant in the room. Darwin’s theory was incomplete. When the theory was completed, would natural selection prove to be that effective? Although he threw in a lot of assorted, presumed-relevant facts, no one, starting with Darwin, had much idea about the nature of variation – how it comes, what form it takes, how regular it is. And, without this knowledge, given that natural selection supposedly works on this variation, it is hard to make definite judgments about its effectiveness; especially since Darwin stressed that, although variation has causes, it is random in the sense of not appearing according to need. When he was not pushing the Lamarckian alternative, he was adamant that it is selection alone that is responsible for adaptation.