Scientific Method, Miscellaneous

Introduction to Karl Popper's philosophy of science.

It is sometimes said that simulation can serve as epistemic substitute for experimentation. Such a claim might be suggested by the fast-spreading use of computer simulation to investigate phenomena not accessible to experimentation (in astrophysics, ecology, economics, climatology, etc.). But what does that mean? The paper starts with a clarification of the terms of the issue and then focuses on two powerful arguments for the view that simulation and experimentation are ‘epistemically on a par’. One is based on the claim (...) that, in experimentation, no less than in simulation, it is not the system under study that is manipulated but a system that ‘stands-in’ for it. The other one highlights the pervasive use of models in experimentation. It will be argued that these arguments, as compelling as they might seem, are each based on a mistaken interpretation of experimentation and that, far from simulation and experimentation being epistemically on a par, they do not have the same epistemic function, do not produce the same kind of epistemic results. (shrink)

Progress in the last few decades in what is widely known as “Chaos Theory” has plainly advanced understanding in the several sciences it has been applied to. But the manner in which such progress has been achieved raises important questions about scientific method and, indeed, about the very objectives and character of science. In this presentation, I hope to engage my audience in a discussion of several of these important new topics.

The general theory of relativity was developed using as a nucleus a principle of symmetry: the principle of general covariance. Initially, Einstein saw the principle of general covariance as an extension of the principle of relativity in classical mechanics, and in SR. For Einstein, the principle of general covariance was a crucial postulate in the development of GR. The freedom of the GR diffeomorphism (the invariance of the form of the laws under transformations of the coordinates depending on the arbitrary (...) functions of space and time) is a "local" spacetime symmetry, as opposed to the "global" spacetime symmetries of the SR (which depend instead on the constant parameters ). DOI: 10.13140/RG.2.2.30854.32326. (shrink)

Metodologia, în activitatea de informații, constă din metodele folosite pentru a lua decizii despre amenințări, în special în cadrul disciplinei de analiză a informațiilor. Teoria prismatică a lui Robert Flood, denumită de alții drept pluralism metodologic, folosește metafora pentru a descrie gândirea creativă și de transformare, respectiv o prismă care descompune lumina în culorile sale componente prin dubla refracție. Tehnicile analitice structurale sunt folosite pentru a provoca judecata, la identificarea mentalităților, depășirea prejudecăților, stimularea creativității și gestionarea incertitudinii. DOI: 10.13140/RG.2.2.10589.36329.

Analiza de informații are multe asemănări epistemologice importante cu știința (rezolvarea problemelor, descoperirea, utilizarea cu abilitate a instrumentelor, verificarea cererilor de cunoștințe). Metafora puzzle este folosită atât în activitatea de informații cât și în arheologie. Ambele discipline implică colectarea de dovezi pentru a construi o imagine cât mai completă posibil. Firmele private inovatoare adaptează din ce în ce mai mult modelul serviciilor de informații la lumea afacerilor pentru a ajuta la planificarea propriilor strategii. Practica medicală de diagnosticare a identificării, colectării, (...) analizării și diseminării este similară cu cea a activității de informații. DOI: 10.13140/RG.2.2.35820.72324. (shrink)

David Singer afirmă că, în prezent, amenințarea constituie principalul obiectiv al agențiilor de informații. Activitatea de informații poate fi considerată ca fiind procesul prin care anumite tipuri de informații sunt solicitate, colectate, analizate și diseminate, și modul în care sunt concepute și desfășurate anumite tipuri de acțiuni secrete. Ciclul informațional reprezintă un set de procese utilizate pentru a furniza informații utile în luarea deciziilor. Ciclul constă din mai multe procese. Domeniul conex al contrainformațiilor este însărcinat cu împiedicarea eforturilor informative ale (...) altora. DOI: 10.13140/RG.2.2.10807.06563. (shrink)

Les analystes sont dans le domaine des « connaissances ». L'activité de renseignement fait référence à la connaissance et les types de problèmes abordés sont des problèmes de connaissance. Nous avons donc besoin d'un concept de travail basé sur la connaissance. Nous avons besoin d'une compréhension de base de ce que nous savons et de la manière dont nous le savons, de ce que nous ne savons pas et même de ce qui peut être connu et de ce qui ne (...) peut pas être connu. L'analyse du renseignement implique de « transformer des faits disparates en conclusions concentrées. » DOI: 10.13140/RG.2.2.11223.91043. (shrink)

Programele de cercetare permit dezvoltarea unor teorii mai complexe. Termenii pot fi aplicați atât la teorii individuale cât și la programe. În cazul în care se aplică teoriilor din cadrul unui program de cercetare, consider că acestea devin la rândul lor programe de cercetare, pe care le putem numi subprograme de cercetare. Spre deosebire de revoluțiile științifice ale lui Kuhn, Lakatos a presupus că existența simultană a mai multor programe de cercetare este norma. Știința se confruntă în prezent cu o (...) astfel de situație inedită: două teorii incompatibile, dar ambele acceptate de comunitatea științifică descriu aceeași realitate în două moduri diferite. DOI: 10.13140/RG.2.2.11153.28005. (shrink)

Science is epistemically special, or so I will assume: it is better able to produce knowledge about the workings of the world than other knowledge-directed pursuits. Further, its superior epistemic powers are due to its being in some sense especially empirical: in particular, science puts great weight on a form of inductive reasoning that I call empirical con rmation. My aim in this paper is to investigate the nature of science’s “empiricism”, and to provide a preliminary explanation of the connection (...) between empirical confirmation and epistemic efficacy. I will try to convince you that the place to find an account of empirical confirmation is the dusty, long-neglected instantialist account of scientific inference offered by mid-century logical empiricists. Some revision of instantialism will be required. As for what is advantageous in empirical confirmation, I propose that it is an unusual degree of independence from background belief. (shrink)

What is science, and what is it not? Is falsifiability the key to drawing this line? How and why does science work? Should we worry whether science is talking about a "real" world? And should we stop thinking there is a single thing we can call "the scientific method"? With Deborah Mayo, Robert Rynasiewicz, and Drew Arrowood.

Datafizierung, Publizierung, Metrisierung – unter diesen Stichpunkten untersuchen die AutorInnen des vorliegenden Bandes die Auswirkungen der zunehmenden Digitalisierung auf die Erzeugung, Auswahl, Bereitstellung und Bewertung wissenschaftlicher Erkenntnis. Wie wird Wissen aus den Weiten des digitalen Raums herausgefiltert? Wie wird es generiert? Was wird als Wissen verfügbar gemacht – und was nicht? Wie und von wem wird das digital erfasste Wissen evaluiert? Diese den Wissenschaftsbetrieb herausfordernden Fragen diskutieren ExpertInnen aus Philosophie, Informations- und Bibliothekswissenschaft sowie Informatik. Ihre Beiträge reflektieren in kritischer und (...) konstruktiver Weise die Gestaltung und Folgen der digitalisierten Wissenschaftspraxis. (shrink)

Scientific progress depends crucially on scientific discoveries. Yet the topic of scientific discoveries has not been central to debate in the philosophy of science. This book aims to remedy this shortcoming. Based on a broad reading of the term “science” (similar to the German term “Wissenschaft”), the book convenes experts from different disciplines who reflect upon several intertwined questions connected to the topic of making scientific discoveries. -/- Among these questions are the following: What are the preconditions for making scientific (...) discoveries? What is it that we (have to) do when we make discoveries in science? What are the objects of scientific discoveries, how do we name them, and how do scientific names function? Do discoveries in, say, physics and biology, share an underlying structure, or do they differ from each other in crucial ways? Are other fields such as theology and environmental studies loci of scientific discovery? What is the purpose of making scientific discoveries? Explaining nature or reality? Increasing scientific knowledge? Finding new truths? If so, how can we account for instructive blunders and serendipities in science? -/- In the light of the above, the following is an encompassing question of the book: What does it mean to make a discovery in science, and how can scientific discoveries be distinguished from non-scientific discoveries? (shrink)

Jan G. Michel argues that we need a philosophy of scientific discovery. Before turning to the question of what such a philosophy might look like, he addresses two questions: Don’t we have a philosophy of scientific discovery yet? And do we need one at all? To answer the first question, he takes a closer look at history and finds that we have not had a systematic philosophy of scientific discovery worthy of the name for over 150 years. To answer the (...) second question, Michel puts forward three arguments that show the importance of a philosophy of scientific discovery. Briefly, he arrives at the following answers: No, we don’t yet have a philosophy of scientific discovery, and yes, we definitely need one. To remedy this shortcoming, Michel analyzes the concept of discovery, leading him to the insight that scientific discoveries have an underlying structure with certain structural features. Some of these features may be important but not indispensable to scientific discovery processes; these include eureka moments, serendipities, joint discoveries, special science funding, and others. In addition, Michel identifies three indispensable structural features which he examines in detail and which he places in a picture with a certain dynamics according to which the process of making scientific discoveries can be seen as a path, leading us from finding and acceptance to knowledge. (shrink)

Replications are often taken to play both epistemic and demarcating roles in science: they provide evidence about the reliability of fields’ methods and, by extension, about which fields “count” as scientific. I argue that, in a field characterized by a high degree of theoretical openness and uncertainty, like comparative cognition, replications do not sit well in these roles. Like other experiments conducted under conditions of uncertainty, replications are often equivocal and open to interpretation. As a result, they are poorly placed (...) to deliver clear judgments about the reliability of comparative cognition’s methods or its scientific bona fides. I suggest that this should encourage us to take a broader view of both the nature of scientific progress and the role of replication in comparative cognition. (shrink)

The role of judgments of beauty in scientific theory evaluation is the subject of significant debate in contemporary philosophy of science. This book advances that debate by broadening its scope. In Judgments of Beauty in Theory Evaluation, the author argues that judgments of beauty are a justified part of theory evaluation of all sorts: not only scientific theory evaluation, but also philosophical theory evaluation. The author argues for this thesis by providing an account of beauty—inherited from Kant and Mothersill—on which (...) the distinctive nature of judgments of beauty is that they are unprincipled, yet possible. The author then analyzes two important methods of theory evaluation—reflective equilibrium and simplicity—and argues that these methods require making judgments of beauty so understood. Finally, the author argues that these methods of theory evaluation are not anomalies, but that they point to a deeper lesson about the nature of theorizing and the necessity of using judgments of beauty to evaluate systems, like theories. This conclusion has implications for the debate in philosophy of science over judgments of beauty, but also prompts a reckoning in philosophy itself over the use of judgments of beauty in philosophical theory evaluation. (shrink)

"Correlation is not causation" is one of the mantras of the sciences—a cautionary warning especially to fields like epidemiology and pharmacology where the seduction of compelling correlations naturally leads to causal hypotheses. The standard view from the epistemology of causation is that to tell whether one correlated variable is causing the other, one needs to intervene on the system—the best sort of intervention being a trial that is both randomized and controlled. In this paper, we argue that some purely correlational (...) data contains information that allows us to draw causal inferences: statistical noise. Methods for extracting causal knowledge from noise provide us with an alternative to randomized controlled trials that allows us to reach causal conclusions from purely correlational data. (shrink)

"David Ricardo has been acclaimed - or vilified - for merits he would never have dreamt of, or sins for which he was entirely innocent. Entrenched mythology labels him as a utilitarian economist, an enemy of the working class, an impractical theorist, a scientist with 'no philosophy at all' and the author of a formalist methodological revolution. Exploring a middle ground between theory and biography, this book explores the formative intellectual encounters of a man who came to economic studies via (...) other experiences, thus bridging the gap between the historical Ricardo and the economist's Ricardo. The chapters undertake a thorough analysis of Ricardo's writings in their context, asking who was speaking, what audience was being addressed, with what communicative intentions, using what kind of lexicon and communicative conventions, and starting with what shared knowledge. The work opens in presenting the different religious communities with which Ricardo was in touch. It goes on to describe his education in the leading science of the time - geology - before he turned to the study of political economy. Another chapter discusses five 'philosophers' - students of logic, ethics and politics - with whom he was in touch. From correspondence, manuscripts and publications, the closing chapters reconstruct, firstly, Ricardo's ideas on scientific method, the limits of the 'abstract science' and its application, secondly, his ideas on ethics and politics and their impact on strategies for improving the condition of the working class. This book sheds new light on Ricardian economics, providing an invaluable service to readers of economic methodology, philosophy of economics, the history of economic thought, political thought and philosophy. Sergio Cremaschi is a former Reader of Moral Philosophy at the 'Amedeo Avogadro' University at Vercelli"--. (shrink)

Recent epistemology of modality has seen a growing trend towards metaphysics-first approaches. Contrastingly, this paper offers a more philosophically modest account of justifying modal claims, focusing on the practices of scientific modal inferences. Two ways of making such inferences are identified and analyzed: actualist-manipulationist modality and relative modality. In AM, what is observed to be or not to be the case in actuality or under manipulations, allows us to make modal inferences. AM-based inferences are fallible, but the same holds for (...) practically all empirical inquiry. In RM, modal inferences are evaluated relative to what is kept fixed in a system, like a theory or a model. RM-based inferences are more certain but framework-dependent. While elements from both AM and RM can be found in some existing accounts of modality, it is worth highlighting them in their own right and isolating their features for closer scrutiny. This helps to establish their relevant epistemologies that are free from some strong philosophical assumptions often attached to them in the literature. We close by showing how combining these two routes amounts to a view that accounts for a rich variety of modal inferences in science. (shrink)

Although there has been a lot of investigation into the influence of the network structure of scientific communities on the one hand and into testimonial norms on the other, a discussion of TNs that take the network structure into account has been lacking. In this paper, I introduce two TNs which are sensitive to the local network structure. According to these norms, scientists should give less weight to the results of well-connected colleagues, as compared to less connected ones. I employ (...) an Agent Based Model to test the reliability of the two novel TNs against different versions of conventional, structure-insensitive TNs in networks of varying size and structure. The results of the simulations show that the novel TNs are more reliable. This suggests that it would be beneficial for scientific communities if their members followed such norms. For individual scientists, I show that there are both reasons for and reasons against adopting them. (shrink)

Transcendental philosophy was not born like Athena out of Zeus’s head, mature and in full armour from the very beginning. That is why in both prefaces to the Critique of Pure Reason (1781 and 1787) Kant introduces the concept of transcendental philosophy as an “idea.” The idea understood architectonically develops slowly and only gradually acquires a definite form. As witnessed by the works of Kant himself and of his predecessors and followers, the idea of transcendental philosophy has undergone a series (...) of changes and adjustments compared to the initial plan. In this context, my goal is not simply exegesis and historical investigation of transcendental philosophy, but also to look at it from a systematic and methodological perspective. I examine the concept of transcendental philosophy from the viewpoint of programmatic metaphilosophy. The first part discusses programmatics as a distinct subsection of metaphilosophy. I argue that Kant’s architectonic methodology and the methodology of Lakatos can be used to understand the inception, development and degradation of philosophical systems. In the second part I look at the project of transcendental philosophy and the stages of its development from the standpoint of architectonics. The third part shows that Lakatos’s methodology can provide a detailed insight into the elements of transcendental philosophy, a clear idea of its logic and identify the component parts that can be improved and developed. In spite of the different levels of detailing and epistemological prerequisites, the methodologies of Kant and Lakatos can be combined to achieve a metaphilosophically informed and progressive understanding of philosophical projects. -/- Keywords: transcendental philosophy, Kant, programmatics, architectonics, metaphilosophy, ideas of reason, Lakatos, research programmes. (shrink)

William S. Lewis examines the contribution to philosophy of science made by Lefebvre, in the context of his membership of the French Communist Party.

Ce livre est un livre d’épistémologie de la sociologie. L’objectif est d’appliquer des méthodes analytiques pour clarifier le vocabulaire, expliciter des relations non-apparentes entre concepts, dégager la portée d’une méthode, ou souligner les incohérences d’un programme de recherche. Les questions épineuses ne sont pas écartéees: Comment clarifier des notions confuses? Peut-on mathématiser les concepts sociologiques? Peut-on pratiquer la sociologie comme on pratique les sciences naturelles? Quelle est la place du déterminisme? Chaque question est examinée à la fois dans sa structure (...) logique et sur des cas concrets. La mathématisation est étudiée sur les mécanismes agrégatifs et sur les modèles de diffusion des innovations. La sociologie expérimentale – généralement méconnue dans la sociologie française – est étudiée sur des programmes de relogement, la diffusion de l’information, ou la genèse de la solidarité sociale. Le livre aborde frontalement la question du déterminisme, du naturalisme, du matérialisme et du scientisme, réputés intenables en sociologie. L’enquête montre que leur rejet résulte généralement de confusions conceptuelles. Une fois écartées, peu d’obstacles s’opposent à leur emploi en sociologie. L’objet de ce livre est la sociologie fondamentale: ensemble des mécanismes qui structurent la production des connaissances sociologiques de base à partir de concepts, programmes ou principes, c’est-à-dire tout ce qui ne relève pas de l’expérience immédiate du terrain et des mondes sociaux. (shrink)

The history of the philosophy of thought experiments has touched on the work of Kuhn, Popper, Duhem, Mach, Lakatos, and other big names of the 20th century, but so far, almost nothing has been written about Paul Feyerabend. His most influential work was Against Method, 8 chapters of which concern a case study of Galileo with a specific focus on Galileo’s thought experiments. In addition, the later Feyerabend was very interested in what might be called the epistemology of drama, including (...) stories and myths. This paper brings these different aspects of Feyerabend’s work together in an attempt to present what might have been his considered views on scientific thought experiments. I conclude by contrasting Feyerabend’s ideas with two modern currents in the debate surrounding thought experiments: 1) the claim that the epistemology of thought experiments is just the epistemology of deductive or inductive arguments, and 2) the claim that the specifically narrative quality of thought experiments must be taken into account if we want a complete epistemology of thought experiments. (shrink)

Precision medicine and molecular systems medicine (MSM) are highly utilized and successful approaches to improve understanding, diagnosis, and treatment of many diseases from bench-to-bedside. Especially in the COVID-19 pandemic, molecular techniques and biotechnological innovation have proven to be of utmost importance for rapid developments in disease diagnostics and treatment, including DNA and RNA sequencing technology, treatment with drugs and natural products and vaccine development. The COVID-19 crisis, however, has also demonstrated the need for systemic thinking and transdisciplinarity and the limits (...) of MSM: the neglect of the bio-psycho-social systemic nature of humans and their context as the object of individual therapeutic and population-oriented interventions. COVID-19 illustrates how a medical problem requires a transdisciplinary approach in epidemiology, pathology, internal medicine, public health, environmental medicine, and socio-economic modeling. Regarding the need for conceptual integration of these different kinds of knowledge we suggest the application of general system theory (GST). This approach endorses an organism-centered view on health and disease, which according to Ludwig von Bertalanffy who was the founder of GST, we call Organismal Systems Medicine (OSM). We argue that systems science offers wider applications in the field of pathology and can contribute to an integrative systems medicine by (i) integration of evidence across functional and structural differentially scaled subsystems, (ii) conceptualization of complex multilevel systems, and (iii) suggesting mechanisms and non-linear relationships underlying the observed phenomena. We underline these points with a proposal on multi-level systems pathology including neurophysiology, endocrinology, immune system, genetics, and general metabolism. An integration of these areas is necessary to understand excess mortality rates and polypharmacological treatments. In the pandemic era this multi-level systems pathology is most important to assess potential vaccines, their effectiveness, short-, and long-time adverse effects. We further argue that these conceptual frameworks are not only valid in the COVID-19 era but also important to be integrated in a medicinal curriculum. (shrink)

In order to gain a better understanding of the impact and circulation of the first edition of the Principia, we offer an analysis of public perceptions in Britain of Isaac Newton’s approach to physical inquiry in the Principia between the appearance of its first and second editions, in 1687 and 1713, respectively. We treat Newton’s readers as actors with distinctive scholarly backgrounds and interests rather than as followers or popularisers of a “Newtonian philosophy,” a label we find to be largely (...) absent in the historical record before 1713, when it was purposefully used by Roger Cotes in his preface to the second edition of the Principia. Through our survey, we gain considerable insight into how Newton’s readers characterised the Principia and its author. We establish that British readers of the first edition of the Principia ascribed a relatively stable and interrelated number of characteristics to Newton’s natural philosophical approach, although different readers emphasised different things. We also show that the most detailed accounts of Newton’s natural philosophical approach were, not surprisingly, given in polemical contexts. We find that it is only at the very end of this period, and in polemical contexts, that the notion of a “Newtonian philosophy” with a specific and pathbreaking approach to physical inquiry arose. (shrink)

This article explains Kant’s claim that sciences must take, at least as their ideal, the form of a ‘system’. I argue that Kant’s notion of systematicity can be understood against the background of de Jong & Betti’s Classical Model of Science (2010) and the writings of Georg Friedrich Meier and Johann Heinrich Lambert. According to my interpretation, Meier, Lambert, and Kant accepted an axiomatic idea of science, articulated by the Classical Model, which elucidates their conceptions of systematicity. I show that (...) Kant’s critique of the mathematical method is compatible with his adherence to this axiomatic conception of science. I further show that systematicity furthers traditionally accepted logical ideals of scientific knowledge, which explains why Meier and Kant think that sciences must be ‘systematic’. (shrink)

Neil Levy defends no-platforming people who espouse dangerous or unacceptable views. I reject his notion of higher-order evidence as authoritarian and dogmatic. I argue that no-platforming frustrates the growth of knowledge.

The psychoanalytical case history was in many ways the pivot point of John Forrester’s reflections on case-based reasoning. Yet the Freudian case is not without its own textual forebears. This article closely analyses texts from two earlier case-writing traditions in order to elucidate some of the negotiations by which the case history as a textual form came to articulate the mode of reasoning that we now call ‘thinking in cases’. It reads Eugène Azam’s 1876 observation of Félida X and her (...) ‘double personality’—the case that brought both Azam and Félida to prominence in late 19th-century French science—against a medico-surgical case penned by the Bordeaux physician in the same decade. While the stylistics of Azam’s medical case mirror its epistemic underpinnings in the ‘vertical’ logics of positivist science, the multiple narratives interwoven in Félida’s case grant both Azam and his patient the role of knowledge-making actors in the text. This narrative transformation chimes with the way Azam reasons ‘horizontally’ from particulars to Félida’s singular condition, but sits in tension with his choice to structure the observation along a ‘vertical’ axis. Between the two, we glimpse the emergence of the psychological observation as a mode of writing and thus of thinking in cases. (shrink)

Our understanding of folk and scientific psychology often informs the law’s conclusions regarding questions about the voluntariness of a defendant’s action. The field of psychology plays a direct role in the law’s conclusions about a defendant’s guilt, innocence, and term of incarceration. However, physical sciences such as neuroscience increasingly deny the intuitions behind psychology. This paper examines contemporary biases against the autonomy of psychology and responds with considerations that cast doubt upon the legitimacy of those biases. The upshot is that (...) if reasonable doubt is established regarding whether psychology’s role in the law should be displaced, then there is room for future work to be done with respect to the truth of psychology’s conclusions about criminal responsibility. (shrink)

The Historia densi et rari, published posthumously in 1658, is probably Francis Bacon’s most complex natural and experimental history. It contains observations and experimental reports, quantitative estimates and tables, and theoretical and methodological considerations, in a structure which has never been fully investigated. I provide here a fresh reading of this text from the perspective of scientific practices. I claim that Historia densi et rari represents a quantitative and instrumental investigation assembled with the help of Bacon’s philosophy of experiment as (...) developed in the Novum organum. I first discuss the role played in the Historia densi et rari by the various instances of special power in delineating the object of research. I then analyze the ways in which a special class of instances of special power, the “mathematical instances,” are used in the Historia densi et rari to make the inquiry both more precise, and more abstract. Bacon used mathematical instances to transform traditional recipes of pneumatics into quantitative, more general investigations into universal motions and processes. Finally, I discuss two examples of scientific practice at work: the attempt to use instruments to gradually define and clarify “proper” notions of “rarefaction” and “condensation,” and the redefinition of a metaphysical concept in instrumental and operational terms. (shrink)

The idea of science being the best – or the only – way to reach the truth about our cosmos has been a major belief of modern civilization. Yet, science has grown tall on fragile legs of clay. Every scientific theory uses axioms and assumptions that by definition cannot be proved. This poses a serious limitation to the use of science as a tool to find the truth. The only way to search for the latter is to redefine the former (...) to its original glory. In the days well before Galileo and Newton, science and religion were not separated. They worked together to discover the truth and while the latter had God as its final destination, the former had God as its starting point. Science is based on the irrational (unproven) belief that the world is intelligible along many other assumptions. This poses a serious limitation to science that can only be overcome if we accept the irrationality of the cosmos. The motto “Credo quia absurdum” holds more truth than one can ever realize at first glance. There is nothing logical in logic, whereas there is deep wisdom in the irrational. For while the former tries to build castles on moving sand, the latter digs deep inside the depths of existence itself in order to build on the most concrete foundations that there can be: the cosmos itself. The only way forward is backwards. Backwards to a time when religion led the quest for knowledge by accepting what we cannot know, rather than trying to comprehend what we do not. Science was anyway based on that in the first place. (shrink)

For centuries, science was considered as something radically different from religion. Yet, the foundations of true science are deeply religious in nature. This paper seeks to show how religion is the only foundation needed for the formulation of scientific theories, since it provides the core principles on which the building of exact sciences is based upon. Our need to understand the cosmos and our faith in us being able to do so, are the main prerequisites for conducting science; prerequisites that (...) are derived from our belief in us being the sons of God and, thus, being able to read His mind. From its birth on 7 March 1277 up to today, science seems to be the only logical attitude of religious people towards the unknown cosmos. (shrink)

Fukuyama's 'The End of History' has referred to Kojeve's 'homogenous state' as some sort of conceptual container for the evolving idea of liberal democracy. This paper critically re-assess the homogeneity of state as final stage of liberal idea and defends civil society in terms of democratic governance. It also invites to discuss the role of scholars as public intellectuals and repels the ideological abuse of the scientific method.

Experimental design is one aspect of a scientific method. A well-designed, properly conducted experiment aims to control variables in order to isolate and manipulate causal effects and thereby maximize internal validity, support causal inferences, and guarantee reliable results. Traditionally employed in the natural sciences, experimental design has become an important part of research in the social and behavioral sciences. Experimental methods are also endorsed as the most reliable guides to policy effectiveness. Through a discussion of some of the central concepts (...) associated with experimental design, including controlled variation and randomization, this chapter will provide a summary of key ethical issues that tend to arise in experimental contexts. In addition, by exploring assumptions about the nature of causation and by analyzing features of causal relationships, systems, and inferences in social contexts, this chapter will summarize the ways in which experimental design can undermine the integrity of not only social and behavioral research but policies implemented on the basis of such research. (shrink)

It is generally accepted among philosophers of science that hypothesis testing is a key methodological feature of science. As far as philosophical theories of confirmation are con...

Has the rise of data-intensive science, or ‘big data’, revolutionized our ability to predict? Does it imply a new priority for prediction over causal understanding, and a diminished role for theory and human experts? I examine four important cases where prediction is desirable: political elections, the weather, GDP, and the results of interventions suggested by economic experiments. These cases suggest caution. Although big data methods are indeed very useful sometimes, in this paper’s cases they improve predictions either limitedly or not (...) at all, and their prospects of doing so in the future are limited too. (shrink)

In the late 19th century, the questionnaire was one means of taking the case study into the multitudes. This article engages with Forrester’s idea of thinking in cases as a means of interrogating questionnaire-based research in early American psychology. Questionnaire research was explicitly framed by psychologists as a practice involving both natural historical and statistical forms of scientific reasoning. At the same time, questionnaire projects failed to successfully enact the latter aspiration in terms of synthesizing masses of collected data into (...) a coherent whole. Difficulties in managing the scores of descriptive information questionnaires generated ensured the continuing presence of individuals in the results of this research, as the individual case was excerpted and discussed alongside a cast of others. As a consequence, questionnaire research embodied an amalgam of case, natural historical, and statistical thinking. Ultimately, large-scale data collection undertaken with questionnaires failed in its aim to construct composite exemplars or ‘types’ of particular kinds of individuals; to produce the singular from the multitudes. (shrink)

Bayesian epistemologyEpistemology offers a powerful framework for characterizing scientific inference. Its basic idea is that rational belief comes in degrees that can be measured in terms of probabilities. The axioms of the probability calculus and a rule for updatingUpdating emerge as constraints on the formation of rational belief. Bayesian epistemologyEpistemology has led to useful explications of notions such asConfirmation confirmation. It thus is natural to ask whether Bayesian epistemologyEpistemology offers a useful framework for thinking about the inferences implicit in the (...) validation of computer simulations. The aim of this chapter is to answer this question. Bayesian epistemologyEpistemology is briefly summarized and then applied to validation. UpdatingUpdating is shown to form a viable method for data-driven validation. Bayesians can also express how a simulation obtains prior credibilityCredibility because the underlying conceptual modelConceptual model is credible. But the impact of this prior credibilityCredibility is indirect since simulations at best provide partial and approximate solutions to theConceptual model conceptual model. Fortunately, this gap between the simulations and the conceptual model can be addressed using what we call Bayesian verification. The final part of the chapter systematically evaluates the use of Bayesian epistemologyEpistemology in validation, e.g., by comparing it to a falsificationist approach. It is argued that Bayesian epistemologyEpistemology goes beyond mere calibrationCalibration and that it can provide the foundations for a sound evaluationEvaluation of computer simulations. (shrink)

Many questions about the fundamentals of some area take the form “What is …?” It does not come as a surprise then that, at the dawn of Western philosophy, Socrates asked the questions of what piety, courage, and justice are. Nor is it a wonder that the philosophical preoccupation with computer simulations centered, among other things, about the question of what computer simulations are. Very often, this question has been answered by stating that computer simulation is a species of a (...) well-known method, e.g., experimentation. Other answers claim at least a close relationship between computer simulation and another method. In any case, correct answers to the question of what a computer simulation is should help us to better understand what validation of simulations is. The aim of this chapter is to discuss the most important proposals to understand computer simulation in terms of another method and to trace consequences for validation. Although it has sometimes been claimed that computer simulations are experiments, there are strong reasons to reject this view. A more appropriate proposal is to say that computer simulations often model experiments. This implies that the simulation scientists should to some extent imitate the validation of an experiment. But the validation of computer simulations turns out to be more comprehensive. Computer simulations have also been conceptualized as thought experimentsThought experiment or close cousins of the latter. This seems true, but not very telling since thought experiments are not a standardStandard method and since it is controversial how they contribute to our acquisition of knowledge. I thus consider a specific view on thought experiments to make some progress on understanding simulations and their validation. There is finally a close connection between computer simulation and modeling, and it can be shown that the validation of a computer simulation is the validation of a specific model, which may either be thought to be mathematical or fictional. (shrink)

This chapter clarifies the concept of validation of computer simulations by comparing various definitions that have been proposed for the notion. While the definitions agree in taking validation to be an evaluationEvaluation, they differ on the following questions: What exactly is evaluated—results from a computer simulation, a model, a computer codeCode? What are the standardsStandard of evaluationEvaluation––truthTruth, accuracyAccuracy, and credibilityCredibility or also something else? What type of verdict does validation lead to––that the simulation is such and such good, or that (...) it passes a testTest defined by a certain threshold? How strong needs the case to be for the verdict? Does validation necessarily proceed by comparing simulation outputsOutput with measured dataData? Along with these questions, the chapter explains notions that figure prominently in them, e.g., the concepts of accuracy and credibility. It further discusses natural answers to the questions as well as arguments that speak in favor and against these answers. The aim is to obtain a better understandingUnderstanding of the options we have for defining validation and how they are related to each other. (shrink)

Verification and validation are methods with which computer simulations are tested. While many practitioners draw a clear line between verification and validation and demand that the former precedes the latter, some philosophers have suggested that the distinction has been over-exaggerated. This chapter clarifies the relationship between verification and validation. Regarding the latter, validation of the conceptual and of the computational modelComputational model are distinguished. I argue that, as a method, verification is clearly different from validation of either of the models. (...) However, the methods are related to each other as follows: If we allow that the validation of the computational model need not include the comparisonComparison between simulation output and measured data, then the computational model may be validated by validating the conceptual model independently and by verifying the simulation with respect to it. This is often not realistic, however, because, in most cases, the conceptual modelConceptual model cannot be validated independently from the simulation. In such cases, the computational modelComputational model is verified with the aim to use it as an appropriate substitute for the conceptual model. Then simulation output is compared to measured data to validate both the computational and the conceptual model. I analyze the underlying inferences and argue that they require some prior confidence in the conceptual model and in verification. This suggests that verification precede validation that proceeds via a comparisonComparison between simulation outputOutput and measured data. Recent arguments to the effect that the distinction between verification and validation is not clear-cut do not refute these results, or so I argue against philosopher E. Winsberg. (shrink)

This book on Philosophy of Science includes a comprehensive discussion of ontology, epistemology, and axiology of science in the constellation of various other knowledge, as well as the development of scientific knowledge holistically contained in each module in this course. These three things are branches of philosophy which are very useful for students of Teacher Training and Education in mediating the learning and learning process so that the essence of Philosophy of Science can then be implemented within the scope of (...) professionalism in particular and society in general and the challenges of the industrial era 4.0 in the 20th century 21 The discussion on ontology is focused on elements of empirical reality (empericism) such as facts, data, and information without releasing it from rational reality (rationalism), and its position in scientific activities. The epistemology of science is focused on the scientific method and its operationalization in research methodology. The axiology of science discusses the values ​​associated with scientific activities and their uses, both internally, externally, and socially. (shrink)

Recent studies of scientific interaction based on agent-based models suggest that a crucial factor conducive to efficient inquiry is what Zollman has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories lasting sufficiently long for the community to identify the best theory and to converge on it. But what exactly generates transient diversity? And is transient diversity a decisive factor when it comes to the efficiency of inquiry? In this paper we (...) examine the impact of different conditions on the efficiency of inquiry, as well as the relation between diversity and efficiency. This includes certain diversity-generating mechanisms previously proposed in the literature, as well as some factors that have so far been neglected. This study is obtained via an argumentation-based ABM. Our results suggest that cautious decision-making does not always have a significant impact on the efficiency of inquiry while different evaluations underlying theory-choice and different social networks do. Moreover, we find a correlation between diversity and a successful performance of agents only under specific conditions, which indicates that transient diversity is sometimes not the primary factor responsible for efficiency. Altogether, when comparing our results to those obtained by structurally different ABMs based on Zollman’s work, the impact of specific factors on efficiency of inquiry, as well as the role of transient diversity in achieving efficiency, appear to be highly dependent on the underlying model. (shrink)

Recent studies of scientific interaction based on agent-based models suggest that a crucial factor conducive to efficient inquiry is what Zollman has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories lasting sufficiently long for the community to identify the best theory and to converge on it. But what exactly generates transient diversity? And is transient diversity a decisive factor when it comes to the efficiency of inquiry? In this paper we (...) examine the impact of different conditions on the efficiency of inquiry, as well as the relation between diversity and efficiency. This includes certain diversity-generating mechanisms previously proposed in the literature, as well as some factors that have so far been neglected. This study is obtained via an argumentation-based ABM. Our results suggest that cautious decision-making does not always have a significant impact on the efficiency of inquiry while different evaluations underlying theory-choice and different social networks do. Moreover, we find a correlation between diversity and a successful performance of agents only under specific conditions, which indicates that transient diversity is sometimes not the primary factor responsible for efficiency. Altogether, when comparing our results to those obtained by structurally different ABMs based on Zollman’s work, the impact of specific factors on efficiency of inquiry, as well as the role of transient diversity in achieving efficiency, appear to be highly dependent on the underlying model. (shrink)

The overflow of scientific literature stimulates poor reading habits which can aggravate science's reproducibility crisis. Thus, solving the reproducibility crisis demands not only methodological changes, but also changes in our relationship with the scientific literature, especially our reading habits. Importantly, this does not mean reading more, it means reading better.