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Lysenko was a powerful Soviet pseudoscientist, whose theories cost millions of lives. He died 50 years ago, but his legacy is highly salient. Anti-science and ideology come together slowly, and UK pseudoscience has had unforeseen consequences. Pseudoscience must be challenged even when this has repercussions for those who speak up.
This Element offers a fresh treatment of the two cycles of reduction-emergence debates in the sciences and their 'reductionist' and 'emergentist' positions. It suggests philosophers have neglected the compositional models/explanations, and 'endogenous' kind of metaphysics, central to these debates. It highlights how such endogenous metaphysics underpins what is termed the 'Dynamic Cycle,' by which scientists develop novel ontological concepts to underwrite new models/explanations to solve scientific problems. And it subsequently shows that the 'reductionist' and 'emergentist' views in the scientific debates follow the Dynamic Cycle. In the first cycle of debates, in the early twentieth century, the Element outlines how 'everyday reductionism' pioneered a novel family of compositional models/explanations in one of the most successful research movements in twentieth-century science. And, in present debates, it frames contemporary emergentist positions offering ontological innovations, underwriting new families of models, to address problems at the cutting-edge of twenty-first-century science.
The scientific enterprise is embedded in the institutional framework of the society consisting of informal and formal institutions. What we call “science” is not a means toward the accomplishment of anything. It is, instead, the institutional embodiment of the processes of constructing and criticizing solutions to theoretical problems that are entered into by individuals in their several abilities and skills. What we call the Scientific Method is constituted by the informal institutions that have originally emerged and diffused during the Scientific Revolution, consisting of essentially three types of rules, the scientific conventions, the moral rules and the scientific techniques. The term should be understood as a type, with the different informal institutions of science being the tokens. The scientific method may take very different forms, but as long as it consists in the techniques of bringing the products of our theoretical imagination in contact with empirical data by scientists following the scientific conventions of their time and the moral rules necessary for this kind of epistemic problem-solving, it remains a distinctive way of grasping the structure of the world.
How can science be protected, by whom and at what level? If science is valued positively as the incubator of the most successful solutions to representational problems of reality as well as the basis of the most effective interventions in the natural and social world, then its constitutional foundations must be protected. This book develops a specific normative outlook on science by introducing the idea of a 'Constitution of Science'. Scientific activities are special kinds of epistemic problem-solving activities unfolding in an institutional context. The scientific enterprise is a social process unfolding within an intricate institutional framework that structures the daily activities of scientists and shapes their outcomes. Those institutions of science which are of the highest generality make up the 'Constitution of Science' and are of fundamental importance for channelling the scientific process effectively.
Control is a key ingredient of scientific experimentation; arguably, an uncontrolled intervention or manipulation is not even a genuine experiment. Experiments in the life sciences, however, are notoriously difficult to control due to the complexity and variability of living things. This Element discusses general features of controlled experimentation, epistemic and practical aspects, and historical perspectives. It argues that controlled experimentation has a material-technical and a conceptual side. It shifts the focus from control experiments, comparisons with a control, to the broader issue of controlling for background factors as the epistemologically fundamental issue in experimentation. To understand the nature of controlled experimentation, one needs to consider the making – the design phase – of controlled experiments, particularly the conceptualization and treatment of background factors. The making of controlled experiments is at the same time constitutive for the knowledge that can be gained in the experiment, contingent on a research situation, and historically shaped.
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.
The Five Domains model is influential in contemporary studies of animal welfare. It was originally presented as a conceptual model to understand the types of impact that procedures may impose on experimental animals. Its application has since broadened to cover a wide range of animal species and forms of animal use. However, it has also increasingly been applied as an animal welfare assessment tool, which is the focus of this paper. Several critical limitations associated with this approach have not been widely acknowledged, including that: (1) it relies upon expert or stakeholder opinion, with little transparency around the selection of these individuals; (2) quantitative scoring is typically attempted despite the absence of clear principles for aggregation of welfare measures and few attempts to account for uncertainty; (3) there have been few efforts to measure the repeatability of findings; and (4) it does not consider indirect and unintentional impacts such as those imposed on non-target animals. These deficiencies lead to concerns surrounding testability, repeatability and the potential for manipulation. We provide suggestions for refinement of how the Five Domains model is applied to partially address these limitations. We argue that the Five Domains model is useful for systematic consideration of all sources of possible welfare compromise and enhancement, but is not, in its current state, fit-for-purpose as an assessment tool. We argue for wider acknowledgment of the operational limits of using the model as an assessment tool, prioritisation of the studies needed for its validation, and encourage improvements to this approach.
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.).