The validity of conclusions drawn from specific research studies must be evaluated in light of the purposes for which the research was undertaken. We distinguish four general types of research: description and point estimation, correlation and prediction, causal inference, and explanation. For causal and explanatory research, internal validity is critical – the extent to which a causal relationship can be inferred from the results of variation in the independent and dependent variables of an experiment. Random assignment is discussed as the key to avoiding threats to internal validity. Internal validity is distinguished from construct validity (the relationship between a theoretical construct and the methods used to operationalize that concept) and external validity (the extent to which the results of a research study can be generalized to other contexts). Construct validity is discussed in terms of multiple operations and discriminant and convergent validity assessment. External validity is discussed in terms of replicability, robustness, and relevance of specific research findings.

Hegel’s “natural philosophy” is an extension of his overall systematic project having to do with a post-Kantian philosophy that did not rely on Kant’s conception of “pure intuitions.” Instead, Hegel proposed a Logic that as an internally self-enclosed system of pure thoughts required to make sense of making sense. Famously, he concluded his Logic with some not entirely clear ideas about the need to move from it to a Naturphilosophie, a move which he somewhat puzzlingly said was not itself a further logical “transition.” Hegel also defends a non-empiricist study of nature, that is, an explanation not merely in terms of empirically determined regularities, for all such regularities, although existent, are not fully “actual” in that they are not what is doing the real work of explanation. What explains the regularities themselves are the various pure objects of the Naturphilosophie which are involved in working out what “external to pure thought” would mean: the mechanical, the physical, the chemical, and the biological fields of nature, each of which manifests a power (Potenz) that explains why the empirically found regularities in nature actually hold. This chapter suggests that the reason for the transition from Logic to Nature is that pure thought on its own is powerless, and that this has implications for how we think of Hegel’s system as a whole.

Literary historians generally explain change by narrating it. Narrative history excels at identifying individual events, authors, and works that exemplify transformations of literary culture. On the other hand, narrative often struggles to represent continuous trends. Since numbers are designed to describe differences of magnitude, quantitative methods can trace a curve and give a more nuanced picture of gradual change. As quantitative methods have become more common in literary studies, it has become clear that many important aspects of literary history are in fact gradual processes extending over relatively long timelines. But there have also, certainly, been moments of rapid change – in some cases initiated by a single book or author. More crucially, readers seem to want the kind of meaning produced by narration. Thus, quantitative methods are never likely to entirely replace a periodized narrative; they merely provide an alternative mode of description.

Every civil wrong has a number of requirements that must be satisfied before the plaintiff may obtain compensation for resulting harm. One requirement common to all wrongs is that the harm must be attributable to the defendant’s wrongful conduct. It may broadly be said that the defendant’s wrongful conduct must constitute a cause of the harm. This always involves an inquiry into whether there is a historical link in fact between the wrong and the harm, and usually also a value judgement on whether liability for the harm ought to be imposed upon the defendant.

With regard to wrongs actionable only on proof of damage (for example, negligence), the attribution of responsibility for harm is part of establishing liability rather than a matter of remedy. With regard to wrongs actionable per se, the attribution of responsibility for harm is a matter of remedy since nominal damages can be awarded in the absence of loss. In any event, it is customary to discuss attribution of responsibility in books on remedies, and this book follows that custom.

The search for the causes of disease is an obvious central step in the pursuit of better health through disease prevention. In the previous chapters we looked at how we measure health (or disease) and how we look for associations between exposure and disease. Being able to identify a relation between a potential cause of disease and the disease itself is not enough, though. If our goal is to change practice or policy in order to improve health, then we need to go one step further and decide whether the relation is causal because, if it is not, intervening will have no effect. As in previous chapters, we discuss causation mainly in the context of an exposure causing disease but, as you will see when we come to assessing causation in practice, the concepts apply equally to a consideration of whether a potential preventive measure really does improve health.

Epidemiology is about measuring disease or other aspects of health in populations, identifying the causes of ill-health and intervening to improve health, and we come back to these three fundamental components later in the chapter. But what do we mean by ‘health’? Back in 1948, the World Health Organization defined it as ‘… a state of complete physical, mental and social well-being’ (WHO, 1948). In practice, what we usually measure is physical health, and this focus is reflected in the content of most routine reports of health data and in many of the health measures that we will consider here; however, there are now methods to capture the more elusive components of mental and social well-being as well. Importantly, the WHO recognised that it is not longevity per se that we seek, but a long and healthy life. So, instead of simply measuring ‘life expectancy’, WHO introduced the concepts of ‘health-adjusted life expectancy’ (HALE) and subsequently ‘disability-adjusted life years’ (DALYs) to enable better international comparisons of the effectiveness of health systems.

The concept of ’causal crypticity’ was introduced by Richardson (2021) to describe the DOHaD field’s high tolerance for both causes and effects that are challenging to observe in nature, show small effect sizes, and are unstable across study populations and contexts. Causal crypticity can be understood in three ways: as an epistemic norm; as a boundary-delimiting signature of field culture or epistemic style; and as a promissory mode. Increasingly, causal crypticity characterises many fields of the big data-rich, postgenomic life sciences, making DOHaD science a useful index case for scholars of the history, philosophy, and social studies of science interested in the epistemic terrain and social implications of postgenomic sciences. The chapter concludes with a discussion of ethical and accountable claimsmaking in DOHaD science under conditions of causal crypticity.

Violence is common and is a public health issue. Forensic psychiatrists offer treatment for the small amount of violence that is due to mental disorder. It is essential to distinguish between meaningful explanations and causes. Violence is not a unitary concept. Evidence for the specific causal associations between mental illness and violence is reviewed. Anger, anxiety, moral and amoral actions are reviewed including intoxication and withdrawal, deception, antisocial personality and psychopathy, and a range of mental illnesses and developmental disorders. Social and developmental factors are also important. Memes, media and social contagion influence the forms of violence. Court reports and treatments are considered critically in relation to violence.

Depression is a leading cause of disability in high- and middle-income countries and is of increasing relative burden in low-income countries. The Global Burden of Disease study illustrates how depression is increasing as a proportion of all the disabilities resulting from illness. This is because we know how to prevent other major causes of disability such as cardiovascular disease and infection and so their incidence is on the decline. Meanwhile, there is evidence that rates of depression are rising slightly. In order to have an impact on this major public health burden, we will need to devise preventative strategies to reduce the incidence. As depression is a continuum, much of the disability is experienced by the larger numbers of those with mild and moderate levels of depression who might not seek treatment for themselves. Therefore, effective preventative strategies applied to the whole population will have more widespread benefits than interventions simply targeted towards those at high risk. In order to develop preventative interventions, we need to know what causes depression.

Epidemiology tends to be primarily concerned with causes outside the individual or with genetic causes.

There are two core problems with private law’s causal rules in an AI context: 1) a problem of proof due to opacity, and 2) autonomy. Further, if AI is capable of being considered an intervening agent, using AI would have liability-avoiding effects. There may be particular problems with informational and decisional AI. Consideration is given to whether, in certain contexts, AI justifies a departure from the ordinary principles of causation.

Psychologists are often called in personal injury and workplace discrimination cases to help determine the extent of psychological damages (e.g., psychological trauma). We apply a rigorous five-stage temporal model to guide forensic evaluators in providing a robust, evidence-based psychological perspective on the nature and extent of the injury, how that injury arose, and the effects of that injury in the future. Functionality of the plaintiff is assessed in daily activities, in the workplace, in intimate relationships, in social and recreational activities, and in relation to their family. Systematic analysis of the functioning of the plaintiff in these areas from the period before the legally relevant event until litigation concludes allows decisions to be made about the nature and source of any impairments. This method includes consideration of alternative hypotheses, integral to decisions about causation. Psychologists’ decisions thus affect outcomes for injured parties. Future research and practice implications are discussed.

● Francis Galton helped invent a model that describes how family names can disappear from a population purely by chance; it provides a good entrée to the subject of neutral evolution. ● Strict neutrality needs to be distinguished from near neutrality. With strict neutrality, each token allele at a locus has a probability of 1/2N of eventually going to fixation if the population is diploid and contains N individuals; there is strict neutrality here because there is zero variation in fitness. ● The relationship of strict neutrality to the hypothesis of a molecular clock is clarified. ● Strict neutrality is a null hypothesis; the epistemic status of null hypotheses is discussed – are they default assumptions, to be viewed as innocent until proven guilty? ● Alternatives to the hypothesis of strict neutrality are discussed, including Tomoko Ohta’s theory of near neutrality, which says that nearly all genes are strictly neutral or slightly deleterious. ● Whether drift is a cause of evolution, and whether it is a process distinct from natural selection, are discussed, and so is the question of what it means for drift to be a stronger cause than selection in the evolution of an allele.

As we have already seen, there are three basic elements to a successful action in negligence:

1. (1) a duty to take reasonable care owed by the defendant to the plaintiff

2. (2) a breach of that duty of care by the defendant

3. (3) damage resulting to the plaintiff from that breach.

This chapter deals with the third element. This stage involves taking (yet again) three steps:

1. (1) Identify the damage having an adverse effect on the plaintiff to be recognised by law as damage for which compensation can be sought.

2. (2) Link the defendant’s conduct (act or omission) to the damage suffered by the plaintiff.

3. (3) Establish the scope of the defendant’s liability or, putting it differently, establish the extent to which the defendant should be found liable for the harm suffered by the plaintiff OR the type of harm suffered was within the scope of foreseeability.

Multilevel multicomponent complex adaptive systems are not reducible to the sum of the causal effects of independent variables. Causal inference, which has a privileged place in contemporary IR (and many other social sciences) cannot address systems effects, which arise from interdependent elements and operations (not the impact of independent variables on dependent variables). Systems effects explanations explain why by showing how. They identify mechanisms and processes of causation. They thus are able to establish causal efficacy; that is, show how processes produce – actually cause – outcomes (rather than merely identify some elements that are part of an unspecified causal process). Such an understanding leads us away from a “laws and theories” conception of science, which remains popular in Physics and Chemistry, towards a “models and mechanisms” understanding, which predominates in the life sciences (which, on their face, seem a much better model for the social sciences).