Reinach’s thesis that there is a legal a priori is as bold as it is interesting. It is bold because it excludes all sources of positive law and claims that certain legal propositions can be known independent of all actual legal systems. The thesis is especially interesting as it does not rely on natural law but rather on immediate insight into a priori legal propositions. Given the great variety of possible a priori propositions, the chapter focuses on necessary, essential, and nonpositive ones. All of them do not reveal a legal a priori, which casts the existence of a legal a priori into doubt. However, the phenomenon of self-evident propositions remains important. One just needs to analyse them differently with the help of nonpositive legal reasons.

The chapter introduces Vico’s praxis epistemology and situates it within the maker’s knowledge tradition. It shows how Vico transformed the tradition into an ambitious philosophical anthropology, a philosophy of history, culture, and existence, which informs human epistemic possibilities, strengths, and limits. It is argued that this philosophy supposes and outlines an alternative, non-Cartesian version of modernity – a version based on the practical certainty that we are makers of our history and symbolic world.

This chapter begins by acknowledging the value of the classical model of scientific discovery with its commitment to isolating variables and cancelling out noise to give us a sense of significance in the numerical results produced. But the 20 chapters in this book amply demonstrate that in the real world of discovery things are messy, unpredictable, and highly differentiated within and across disciplines. Such enduring principles of discovery, emerging from the work of scientists and scholars, are identified not only for their intellectual value but also for their practical guidance for those engaged in advanced research.

This chapter analyses the legal framework for the use of facial recognition technology (FRT) in the public sector in Germany, with a particular emphasis on the pertinent German data protection and police laws. Under German law, a legal basis is required for these real-world applications of FRT. The article discusses whether the pertinent laws provide such legal basis and what limits they impose.

Science is distinguished from other endeavors by the scientific method, which starts with curiosity and leads sequentially from hypothesis to experimental testing to hypothesis revision, and finally, to knowledge. This chapter traces the development of the scientific method from ancient Egypt, Greece, the Islamic world, Europe (beginning in the Middle Ages), and the modern world (eighteenth to twenty-first century). It shows how the method became increasingly rigorous and precise through codification of its practice and the use of statistics in data analysis. The contributions of philosophy to the method and its possible senescence, in the light of data-driven science, also are discussed.

The Council of Trent addressed the topics of original sin and justification in two decrees, developed in succession. The Decree on Original Sin reaffirms a broadly Augustinian understanding of original sin, its effects, and its remedy in baptism. What remains after baptism is not sin in the strict sense. The Decree on Justification lays out the path from sin to grace to glory. Emphasis lies on both the constant and decisive role of grace and on the way grace engages rather than nullifies the agency of the justified. The Decree on Justification in particular not only rejected errors, but expounded Catholic teaching.

The Court of Chancery required ‘three certainties’ in order to recognise a valid private express trust. These are: certainty of intention to create a trust, certainty of subject matter of a trust (trust property), and certainty of object (those who are or may be entitled to trust property). Each of the certainties is crucial, for varying reasons. Unless the certainty requirements can be satisfied, an enforceable trust will not have been created. Each of the three certainties will be considered separately.

Commercial contracts frequently contain mediation clauses requiring parties to mediate as part of a sequence of dispute resolution methods, where they progress from consensus to evaluative methods until resolution is reached. Careful drafting is required to ensure such clauses are effective and enforceable. The primary issues relevant to the enforceability of mediation clauses include severability, certainty, completeness, attempts to oust the court’s jurisdiction, additional policy considerations, certainty, waiver and remedies for breach of mediation clauses. While compliance with mediation clauses is not easy to determine, only the narrowest of requirements has proven workable in practice. Regional and international instruments covering mediation tend not to provide for the enforcement of mediation clauses. There is an international trend towards obligating legal advisors to discuss with their clients whether their commercial disputes are suitable for mediation, and policy in many jurisdictions is moving towards penalising parties where mediation is not given due consideration. Similar to mediation clauses, agreements to mediate require careful drafting to ensure enforceability.

Although it is helpful to appreciate the general nature of explanations, we might reasonably want more than this. As this book is part of the Understanding Life series, we may expect to delve into details about kinds of explanations that are specific to the life sciences.

It is widely held that science is a (if not the) primary source of our knowledge of the world around us. Further, most accept that scientific knowledge is the best confirmed and well-supported kind of knowledge that we have of the world. But, how do scientific explanations lead to scientific knowledge? The short answer is that they do so via a method known as “inference to the best explanation” (IBE), sometimes called “abduction.” Before we get into the details of IBE, let’s take a quick look at an obvious way that scientific explanations give us scientific knowledge.

A general way of appreciating some of the main ideas of the previous chapter is to recognize that explanations aim at providing understanding. Scientists and philosophers agree that understanding is a (if not the) primary epistemic goal of scientific inquiry. Both explanation and prediction tend to be closely related to understanding. We want explanations in science because we want to understand why the world is as it is and how things happen. And, once we understand various phenomena, we can make accurate predictions about them. One simple, and widely accepted, way of assessing the quality of a given explanation is to look at the understanding it provides. Roughly, the better an explanation, the more understanding that explanation (if true) would provide. As philosopher Peter Lipton explained, the explanation that is the best is simply the explanation that, if true, would provide the deepest understanding of the phenomena being explained. That being said, some worry because it seems that we might misjudge how well we understand something.

In this chapter we’re looking at the relation between scientific explanations and predictions. It is tempting to think that the only difference between explanations and predictions is that one looks back and tells us how or why things happened as they did, and the other looks forward and tells us how or why certain things will (or are likely to) happen. This thought can seem particularly plausible when we consider that in many cases a good scientific hypothesis will both explain phenomena and allow us to make accurate predictions. Despite its initial plausibility, the idea that explanation and prediction are symmetrical is mistaken. The way to see this is to take a look at a particular theory of scientific explanation that entails this relationship between explanation and prediction. The particular theory of scientific explanation in question, the covering law model, which we discussed in Chapter 2, is false. One of the reasons that this theory of explanation fails helps illustrate the fact that explanation and prediction are not symmetrical.

Explanation is central to our lives, in general. We seem to have an innate (or nearly so) drive to explain and seek explanations. When our favorite app is not working, we want to know why, and we want to know how to fix it. When trying to understand why people engage in an odd behavior – refusing to wear masks during the COVID-19 pandemic, say – we want an explanation. What reasons do they have for doing something that seems so clearly misguided? Why are they resistant to expert advice on the issue? Ultimately, we seek explanations to help us understand and navigate the world around us.

While it isn’t necessary to do so, it’s often good to start a book by saying something that is clearly true. So, let’s do that. Science has had (and continues to have) a significant impact upon our lives. This fact is undeniable. Science has revealed to us how different species arise, the causes of our world’s changing climate, many of the microphysical particles that constitute all matter, among many other things. Science has made possible technology that has put computing power that was almost unimaginable a few decades ago literally in the palms of our hands. A common smartphone today has more computing power than the computers that NASA used to put astronauts on the Moon in 1969! There are, of course, many additional ways in which science has solved various problems and penetrated previously mysterious phenomena. A natural question to ask at this point is: why discuss this? While we all (or at least the vast majority of us!) appreciate science and what it has accomplished for modern society, there remain – especially among portions of the general public – confusions about science, how it works and what it aims to achieve. The primary goal of this book is to help address some specific confusions about one key aspect of science: how it explains the world.

In the previous chapter we discussed the importance of accurate explanations. Without explanations that are in fact accurate we cannot have genuine understanding. In this chapter we will explore whether false scientific theories can be used to generate accurate scientific explanations. Before jumping into this, let’s first briefly recall the relationship between scientific theories and scientific explanations. Scientific theories consist of laws, models, and principles. Together these components of scientific theories offer broad generalizations about the nature of the world.