We introduce the subjects beginning with the early works of Hegel, followed by a description of the emphases provided by Levins and Lewontin in their volume. Then we elaborate on the particularities that become involved in the application to the issues of food and agriculture more generally, and specifically to agroecology. We end the chapter with a discussion of the meaning of agroecology as both a field of intellectual inquiry and a platform for political action.

Beginning with some historical issues associated with knowledge and its relationship to the food system, we engage in a discussion of traditional versus scientific knowledge, exploring how each is envisioned and their interpenetration, and arguing that both, as currently generally used, are legitimate and should be part of a dialog of knowledges (dialogo de saberes).

The economics used by governments is based on ideas from the 1870s, when economists adopted the language of science, but not the method. To make the maths easy to solve, they assumed the economy was simple, predictable, and static. Nobody believes these assumptions are true, but they still shape analysis that informs policy. When the economy is complex, uncertain, and changing, this kind of analysis can lead us to bad decisions.

This chapter offers a thorough guide to the techniques and instruments used to understand how the brain develops in humans. It covers key learning goals, such as examining how behaviors change as people grow, how studying typical and atypical development inform each other, and what we can and cant learn about brain structure using non-invasive brain scans. It also explains the two main ways we measure brain function. Starting with some back history on methodological tools, this chapter sets the stage for deeper insights into brain development and its impact on our abilities. It highlights the dynamic nature of the field, influenced by both animal studies and rapidly evolving and improving analytical tools and methods. With a focus on methods for studying children, we explore more advanced techniques used in different age groups. Furthermore, this chapter stresses the importance of a scientific mindset and adaptability when new evidence comes to light. It serves as a vital reference for understanding the tools and approaches in developmental cognitive neuroscience.

We tend to think of scientific knowledge as the paradigm case of what knowledge should look like. But the dominant image of science does not reflect what actually goes on in the making of scientific knowledge. Real scientific knowledge relies heavily on human judgment. And it relies heavily on communities.

In The Guide to the Perplexed III.37, Moses Maimonides attacks pagan ‘medical’ practices which give a sheen of efficacy but are ultimately dependent on magic and astrology. Nonetheless, he allows certain exceptions found in late antique rabbinic literature which have been proven through experience – even if they are not ‘prescribed by reason’. His preference for empiricism over principles or causes is noteworthy. In this, Maimonides follows others such as al-Ghazālī who prized Galen’s medical empiricism over medical theory. In this chapter I examine these exceptional cases in light of the literature of antiquity in order to discuss their efficacy. I also reveal how Maimonides’ begrudging acceptance of experience over theory also underpins his ‘proof’ of the creation of the world – which also ultimately turns to Galen. Thus, I reflect on the importance of Maimonides’ loyalty to Galen’s experimental method for both physics and metaphysics, showing methodological continuities across different domains.

This chapter reflects on how both Soviet and neoclassical economic doctrines impose a practice of ‘organised forgetting’: the omission and rejection of knowledge that does conform to the presumed ontology. In adopting the language of science, both Soviet and neoliberal ideologies would attack their political opponents as primitives, unschooled in their singular methods of reasoning. Neoliberalism, in particular, is neverthless more accurately understood as working against the scientific method, depending as it does on argument from abstract, de-historicized assumption, as distinct from evidence-based justification, theoretical review and adaptation. The chapter traces how neoclassical theory was translated into a political agenda for the New Right through the 1970s. It closes by introducing the neoliberal governmental toolkit of the New Public Management, and explains why, following the isomorphism in their forms of reasoning, NPM would recreate the Stalinist toolkit of quantification, output planning, targets and managerial ‘correct lines’, only now in capitalist form. The analytical foundations are thus set for the policy chapters that follow.

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 central message of the introduction is one must understand science if one wants to do science well. This requires a holistic educational approach, one that not only teaches the whats and hows of science, but most critically, it's whys. Why is the sky blue? Why do normal cells turn into cancer cells? Why do we use the scientific method and from where did it come? Why would one want to be a scientist in the first place? Why is science done in the way it is, that is, what is the gestalt of science? The whats and whys of science are practical in nature. The whys, in contrast, encompass theoretical, philosophical, historical, and social underpinnings of science. The whys are particularly important now when the probity and veracity of science are being attacked, and people seek to replace actual facts with "alternative facts" (falsehoods) for political, religious, or economic purposes or out of plain ignorance.

This introductory chapter presents some fundamental concepts that lay the foundation for the rest of the book. It seeks to accomplish three goals. First, it discusses the nature of war, and in particular Clausewitz’s dictum that war is politics by other means. It is stressed that the book employs a very broad concept of war, including conflicts between states, civil wars, terrorism, some forms of interpersonal violence, and others. Second, it considers the possibility that the practice and frequency of war have changed over time. It observes how some modes of warfare have changed and some have not. It also suggests that it may be premature to celebrate the end of war, or even the significant decline of war. Third, it describes the scientific approach to understanding war and peace, highlighting the importance of asking general questions, developing theoretical answers to those questions, and testing those answers with empirical data. It also defines concepts such as hypotheses, independent variables, and dependent variables, and describes different kinds of data that can be used to test war-related hypotheses.

The economics used by governments is based on ideas from the 1870s, when economists adopted the language of science, but not the method. To make the maths easy to solve, they assumed the economy was simple, predictable, and static. Nobody believes these assumptions are true, but they still shape analysis that informs policy. When the economy is complex, uncertain, and changing, this kind of analysis can lead us to bad decisions.

Chapter 2 outlines the history of DNA research and the key scientists who made the discoveries that enabled the manipulation of DNA. The scope, nature and ethos of science and the scientific method are described, with models for the scientific method and support for research. The importance of gathering and evaluating data in experimental science is outlined, and some of the key aspects and terminology are discussed.

Statistics have a philosophy, which reflects philosophy of science. Different aspects of knowledge in science, as expressed in statistics, are discussed.

This chapter introduces some of the broader ideas and themes of the book, especially the importance of the scientific method as a route to understanding the material universe. It contrasts the scientific perspective with the perspectives in other academic and non-academic disciplines (e.g. the historical, religious, and moral perspectives on human behavior). It gives examples of the value of the scientific perspective, especially the fact that it does not allow for a privileged position, and that it is a relatively democratic form of knowledge. It discusss some historical objections to science, and also reviews some misuse of science, but also the types of topics science cannot address (morality, aesthetics, etc.).

In many undergraduate psychology programs, students gain research experience through intentional scaffolded experiences throughout the undergraduate curriculum and in some cases by joining a faculty member’s research program outside of the classroom. In sustained undergraduate research experiences, students benefit from developmentally appropriate mentoring as they gradually develop and master skills, an approach often compared to an apprenticeship model. Many psychology faculty use evidence-based mentoring practices, such as the Salient Practices Framework, which was developed by an international, multi-institutional research team. Examples include setting clear and incremental expectations and supporting students as they transfer more basic skills learned in the classroom to conducting community or field-based research. There are creative and evidence-based ways to improve access for all students by being more intentional about embedding research experiences in the psychology curricula, or by further considering ways to recruit and retain UR students from historically underserved groups.

The estrangement and frequent mutual incomprehension existing between theology and the sciences today reflects chiefly cultural phenomena, arising from particular methodological determinations reached by both disciplines in early modernity that, over time, mutated into irreconcilable metaphysical visions. What had been distinct modes of inquiry within a unified intellectual pursuit of a single comprehensive transcendent truth now came to be understood as entirely unrelated bodies of factual knowledge pursuing separate ends. This change, however, involved several logically unsustainable revisions of previous categories: ‘revelation’, ‘science’, and ‘nature’, for instance, and ‘causality,‘ in particular. Yet these developments imposed limits upon both theology and the sciences that inhibited the power of either to understand many of its own claims. Lately, in physics and the life sciences especially, there has been a healthy movement away from purely mechanical models of causality. Whether theology can recover a dimension of scientifically informed natural philosophy is yet to be seen. But if the two cultures can be disencumbered of their early modern metaphysical prejudices, they might find that they naturally converge upon a shared horizon of ultimate explanation that provides each with its animating logic and reveals each to be only a limited mode of that final wisdom.

Chapter 2 starts by placing experiments in the scientific process – experiments are only useful in the context of well-motivated questions, thoughtful theories, and falsifiable hypotheses. The author then turns to sampling and measurement since careful attention to these topics, despite being often neglected by experimentalists, are imperative. The remainder of Chapter 2 offers a detailed discussion of causal inference that is used to motivate an inclusive definition of “experiments.” The author views this as more than a pedantic exercise, as careful consideration of approaches to causal inference reveals the often implicit assumptions that underlie all experiments. The chapter concludes by touching on the different goals experiments may have and the basics of analysis. The chapter serves as a reminder of the underlying logic of experimentation and the type of mindset one should have when designing experiments. A central point concerns the importance of counterfactual thinking, which pushes experimentalists to think carefully about the precise comparisons needed to test a causal claim.