The relationship between teaching and argumentation is becoming a crucial issue in the field of education and, in particular, science education. Teaching has been analyzed as a dialogue aimed at persuading the interlocutors, introducing a conceptual change that needs to be grounded on the audience’s background knowledge. This paper addresses this issue from a perspective of argumentation studies. Our claim is that argumentation schemes, namely abstract patterns of argument, can be an instrument for reconstructing the tacit premises in students’ (...) argumentative reasoning and retrieving the background beliefs that are the basis of their arguments. On this perspective, the process of premise reconstruction is followed by a heuristic reasoning process aimed at discovering the students’ previous intuitions that can explain the premises and concepts that are left unexpressed in their arguments. The theoretical insights advanced in this paper are illustrated through selected examples taken from activities concerning predictive claims on scientific issues. (shrink)

A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge (...) bioengineering scientists integrate the cognitive, social, material, and cultural dimensions of practice. Her findings and conclusions have broad implications for researchers in philosophy, science studies, cognitive science, and interdisciplinary studies, as well as scientists, educators, policy makers, and funding agencies. In studying the epistemic practices of scientists, Nersessian pushes the boundaries of the philosophy of science and cognitive science into areas not ventured before. She recounts a decades-long, wide-ranging, and richly detailed investigation of the innovative interdisciplinary modeling practices of bioengineering researchers in four university laboratories. She argues and demonstrates that the methods of cognitive ethnography and qualitative data analysis, placed in the framework of distributed cognition, provide the tools for a philosophical analysis of how scientific discoveries arise from complex systems in which the cognitive, social, material, and cultural dimensions of problem-solving are integrated into the epistemic practices of scientists. Specifically, she looks at how interdisciplinary environments shape problem-solving. Although Nersessian’s case material is drawn from the bioengineering sciences, her analytic framework and methodological approach are directly applicable to scientific research in a broader, more general sense, as well. (shrink)

There is an ongoing methodological debate in philosophy of science concerning the use of case studies as evidence for and/or against theories about science. In this paper, I aim to make a contribution to this debate by taking an empirical approach. I present the results of a systematic survey of the PhilSci-Archive, which suggest that a sizeable proportion of papers in philosophy of science contain appeals to case studies, as indicated by the occurrence of the indicator words (...) “case study” and/or “case studies.” These results are confirmed by data mined from the JSTOR database on research articles published in leading journals in the field: Philosophy of Science, the British Journal for the Philosophy of Science (BJPS), and the Journal for General Philosophy of Science (JGPS), as well as the Proceedings of the Biennial Meeting of the Philosophy of Science Association (PSA). The data also show upward trends in appeals to case studies in articles published in Philosophy of Science, the BJPS, and the JGPS. The empirical work I have done for this paper provides philosophers of science who are wary of the use of case studies as evidence for and/or against theories about science with a way to do philosophy of science that is informed by data rather than case studies. (shrink)

This book argues for the need to put into practice a profound and comprehensive intellectual revolution, affecting to a greater or lesser extent all branches of scientific and technological research, scholarship and education. This intellectual revolution differs, however, from the now familiar kind of scientific revolution described by Kuhn. It does not primarily involve a radical change in what we take to be knowledge about some aspect of the world, a change of paradigm. Rather it involves a radical change in (...) the fundamental, overall intellectual aims and methods of inquiry. At present inquiry is devoted to the enhancement of knowledge. This needs to be transformed into a kind of rational inquiry having as its basic aim to enhance personal and social wisdom. This new kind of inquiry gives intellectual priority to the personal and social problems we encounter in our lives as we strive to realize what is desirable and of value – problems of knowledge and technology being intellectually subordinate and secondary. For this new kind of inquiry, it is what we do and what we are that ultimately matters: our knowledge is but an aspect of our life and being. (shrink)

Robert Henman’s article, Can brain scanning and imaging techniques contribute to a theory of thinking? came to my attention recently. My own work over the years has included applications of mathematics in the biological sciences, collaboration in experimental work in biochemistry, as well as work in the philosophy of the biological sciences. Henman suggests something that, at present, would be out of the ordinary.

This highly multidisciplinary collection discusses an increasingly important topic among scholars in science and technology studies: objectivity in science. It features eleven essays on scientific objectivity from a variety of perspectives, including philosophy of science, history of science, and feminist philosophy. Topics addressed in the book include the nature and value of scientific objectivity, the history of objectivity, and objectivity in scientific journals and communities. Taken individually, the essays supply new methodological tools for theorizing what is (...) valuable in the pursuit of objective knowledge and for investigating its history. The essays offer many starting points, while suggesting new avenues of research. Taken collectively, the essays exemplify the very virtues of objectivity that they theorize—in reading them together, the reader can sense various anxieties about the dangerously subjective in our age and locate commonalities of concern as well as differences of approach. As a result, the volume offers an expansive vision of a research community seeking a communal understanding of its own methods and its own epistemic anxieties, struggling to enunciate the key problems of knowledge of our time and offer insight into how to overcome them. -/- (Contributors: Alex Csiszar, Scott Edgar, Peter Galison, Ian Hacking, Sandra Harding, Moira Howes, Paolo Savoia, Judy Segal, Joan Steigerwald, and Alison Wylie). (shrink)

This paper focuses on the distinction between methods which are mathematically "clever", and those which are simply crude, typically repetitive and computer intensive, approaches for "crunching" out answers to problems. Examples of the latter include simulated probability distributions and resampling methods in statistics, and iterative methods for solving equations or optimisation problems. Most of these methods require software support, but this is easily provided by a PC. The paper argues that the crunchier methods often have substantial advantages from the perspectives (...) of user-friendliness, reliability (in the sense that misuse is less likely), educational efficiency and realism. This means that they offer very considerable potential for simplifying the mathematical syllabus underlying many areas of applied mathematics such as management science and statistics: crunchier methods can provide the same, or greater, technical power, flexibility and insight, while requiring only a fraction of the mathematical conceptual background needed by their cleverer brethren. (shrink)

This article reports on Clean Language Interviewing (CLI), a rigorous, recently developed 'content-empty' (non-leading) approach to second-person interviewing in the science of consciousness. Also presented is a new systematic third-person method of validation that evaluates the questions and other verbal interventions by the interviewer to produce an adherence-to-method or 'cleanness' rating. A review of 19 interviews from five research studies provides a benchmark for interviewers seeking to minimize leading questions. The inter-rater reliability analysis demonstrates substantial agreement among (...) raters with an average intraclass correlation coefficient of 0.72 (95% CI). We propose that this method of validation is applicable not only to CLI but to second-person interviews more generally. (shrink)

Scientists often use aesthetic values in the evaluation and choice of theories. Aesthetic values are not only regarded as leading to practically more useful theories but are often taken to stand in a special epistemic relation to the truth of a theory such that the aesthetic merit of a theory is evidence of its truth. This paper explores what aesthetic considerations influence scientists' reasoning, how such aesthetic values relate to the utility of a scientific theory, and how one can justify (...) the epistemic role for such values. The paper examines ways in which the link between beauty and truth can be defended, the challenges facing such accounts, and explores alternative epistemic roles for aesthetic values in scientific practice. (shrink)

At the end of the 19th century, most professional historians – wherever they existed – deemed history to be a form of knowledge ruled by a method that bears no resemblance with those most commonly traceable in the natural sciences. The bulk of the historian’s task was then frequently regarded as being the application of procedures frequently referred to as ‘historical method’. In the context of such an emerging interest on historical methods and methodology, at least three textbooks (...) stand out: Johann Gustav Droysen’s Grundriss der Historik (Outline of the Theory of History), Ernst Bernheim’s Lehrbuch der historischen Methode (Handbook of Historical Method), and Charles Langlois and Charles Seignobos’s Introduction aux études historiques (Introduction to the Study of History). These books were quite influential in Germany, France, and elsewhere, and they very much helped promote a general idea of historical method that would become relatively consensual among historians of many nationalities by the early 20th century. Such a relative agreement on historical method sponsored both the communication and the development of a sense of disciplinary identity among historians trained within different and sometimes conflicting national traditions. It was then partially extended, partially challenged, and surely made more complex when, from the 1920s on, social and economic historians became a good part of the historiographical establishment in many countries. -/- The three books by Droysen, Bernheim, and Langlois and Seignobos were already pieced together by Rolf Torstendahl, who studied them as a group of texts that, despite their differences, contributed to shape the developments outlined above. However, Torstendahl’s primary aim was to show how Droysen, Bernheim, and Seignobos all resorted to ‘method’ as a way to circumvent skepticism against the possibility of historical knowledge, rather than investigate the internal interrelationships between the three texts. In this chapter I follow precisely this latter, not yet taken, road, focusing on crucial cross-references between the Grundriss, the Lehrbuch, and the Introduction. I intend to show that, at a general level, the schemes of historical method found in these texts are largely convergent, and that this convergence is due to Bernheim’s reading of Droysen and to Langlois and Seignobos’s reading of Bernheim. I will attempt to do it through a regressive approach that starts with an analysis of the Introduction. Aspects of the editorial history and circulation of the three texts will also be briefly addressed, as a way to illustrate their special importance within the framework of early 20th century historical theory. Because my argument calls for a focus on the most general lines of Droysen’s, Bernheim’s, and Langlois and Seignobos’s schemes of historical method, I will, for the sake of consistency, refrain from analysing in-depth the complex epistemological and ontological arguments in which those schemes are nested. (shrink)

Imagination is necessary for scientific practice, yet there are no in vivo sociological studies on the ways that imagination is taught, thought of, or evaluated by scientists. This article begins to remedy this by presenting the results of a qualitative study performed on two systems biology laboratories. I found that the more advanced a participant was in their scientific career, the more they valued imagination. Further, positive attitudes toward imagination were primarily due to the perceived role of imagination in problem-solving. (...) But not all problem-solving episodes involved clear appeals to imagination, only maximally specific problems did. This pattern is explained by the presence of an implicit norm governing imagination use in the two labs: only use imagination on maximally specific problems, and only when all other available methods have failed. This norm was confirmed by the participants, and I argue that it has epistemological reasons in its favour. I also found that its strength varies inversely with career stage, such that more advanced scientists do (and should) occasionally bring their imaginations to bear on more general problems. A story about scientific pedagogy explains the trend away from (and back to) imagination over the course of a scientific career. Finally, some positive recommendations are given for a more imagination-friendly scientific pedagogy. (shrink)

In this article, three concepts that constitute the pillars of sciences, namely the subject, principle and problem, will be examined relying on Avicenna’s (d. 428/1037) book of Burhān. These three concepts, which generally determine the scope of scientific research and the principles on which it should be based, were introduced systematically for the first time by Aristotle (d. 322 BC) in the history of thought. Through these concepts, philosophical sciences could be distinguished from one another and it became possible for (...) each science to examine specific parts of existence. This distinction, which was also adopted by the scholars of Islamic thought, has presented such an integrity that neither philosophical disciplines nor religious sciences could remain indifferent. As a matter of fact, especially in the later period of theologicians, the information was considered as science only if it was based on these three concepts. Therefore, it can be asserted that these three concepts were considered as the measure of scientific activity, first by peripatetic philosophy and later by other disciplines. (shrink)

Resumen: Este artículo trata del método y su relación con la investigación educativa. El objetivo es analizar la relevancia del método en ciencias humanas y sociales, en especial, en educación. Para ello, dividimos este artículo en tres secciones: 1. ¿Hay método? 2. ¿Hay uno o varios métodos? 3. La discusión sobre el método en la investigación educativa. A la primera pregunta, respondemos que hay método. Respondemos a la segunda señalando la necesidad de adoptar un pluralismo metodológico. La tercera sección defiende (...) que las discusiones sobre el método de investigación educativa implican dimensiones ontológicas, epistemológicas y éticas que se han tornado críticas, y se hace una revisión de cada una de ellas. En el apartado conclusivo, sugerimos algunas vías para desanudar esos asuntos críticos en la investigación educativa.: This article deals with method and its relation to educational research. The objective is to analyze the relevance of method in human and social sciences, especially in education. To this end, we divide this article into three sections: 1. Is there a method? 2. Is there one or more methods? 3. The discussion on method in educational research. To the first question, we answer that there is a method. We answer the second question by pointing out the need to adopt methodological pluralism. The third section argues that discussions on the method of educational research involve ontological, epistemological, and ethical dimensions that have become critical, and a review is made of each of them. In the concluding section, we suggest some ways to disentangle these critical issues in educational research. (shrink)

What makes science trustworthy to the public? This chapter examines one proposed answer: the trustworthiness of science is based at least in part on its independence from the idiosyncratic values, interests, and ideas of individual scientists. That is, science is trustworthy to the extent that following the scientific process would result in the same conclusions, regardless of the particular scientists involved. We analyze this "idiosyncrasy-free ideal" for science by looking at philosophical debates about inductive risk, focusing (...) on two recent proposals which offer different methods of avoiding idiosyncrasy: the high epistemic standards proposal and the democratic values proposal. (shrink)

A conspicuous feature of contemporary modelling practices is the use of the same mathematical forms and modelling methods across different scientific domains. This model transfer raises many philosophical questions concerning, for example, the exact object of transfer, the relationship between the model and the target domain, the specific challenges such transfer confronts, and the ways in which model transfer relates to scientific progress. While the interest in studying model transfer has increased among philosophers of science in recent years, the (...) phenomenon has not yet received its due attention. The literature is scattered and much of it has addressed questions around the factors that might explain model transfer, such as whether the different target phenomena to which a model is applied eventually prove to be structurally and dynamically similar, or whether they have to share more fundamental ontological features that explain the interdisciplinary success of distinct models. This chapter surveys the existing literature on model transfer with the main goal of highlighting the main findings of existing discussions and pointing out open issues whose discussion would improve our understanding of this highly relevant phenomenon in science. (shrink)

This article outlines a method of collaboration that will manifest a high probability of cumulative and progressive results in science. The method will accomplish this through a division of labour grounded in the order of occurrence of human cognitional operations. The following article explores the possibility of a method known as functional specialization, distinct tasks presently operative in neuroscience. Functional specialization will enhance collaboration within a science as well as initiate implementation of generalized empirical (...) class='Hi'>method. Implementation of generalized empirical method will be achieved through the focus of individual specialties on specific mental operations. (shrink)

This dissertation is a collection of essays exploring the role of metaphor in Aristotle’s scientific method. Aristotle often appeals to metaphors in his scientific practice; but in the Posterior Analytics, he suggests that their use is inimical to science. Why, then, does he use them in natural science? And what does his use of metaphor in science reveal about the nature of his scientific investigations? I approach these questions by investigating the epistemic status of metaphor in (...) Aristotelian science. In the first essay, I defend an interpretation of metaphor as a type of heuristic reasoning: I claim that Aristotle uses metaphor to express conditions an explanation in natural science must meet if it is to explain regular, ordered change. These conditions specify the kinds of causes—particularly unmoved efficient causes—which the inquirer into nature is seeking. In the second essay, I look to Aristotle’s use of certain endoxa or common beliefs as explanatory principles in science, and show that his use of these principles is similar to his use of metaphor. In the final essay, I present a historical study of the analogy of art and nature, and I suggest that by looking to how the Greeks understood the role of inquiry in the arts, we can shed some light on Aristotle’s views concerning the method of inquiry he thinks the natural scientist should adopt. (shrink)

The article provides a historical contextualization of the debates on theory and method within interwar American sociology. This period is often portrayed as the “golden” age of empirical inquiry resulting in proliferation of methodological orientations. It is argued that the demands of professionalization and specialization within the discipline produced a research model which succeeded in analyzing specific issues, but failed to find a convincing answer to the general question of the logic of society’s development.

Background Professional communities such as the medical community are acutely concerned with negligence: the category of misconduct where a professional does not live up to the standards expected of a professional of similar qualifications. Since science is currently strengthening its structures of self-regulation in parallel to the professions, this raises the question to what extent the scientific community is concerned with negligence, and if not, whether it should be. By means of comparative analysis of medical and scientific codes of (...) conduct, we aim to highlight the role of negligence provisions in codes of conduct for scientists, and to discuss the normative consequences for future codes of conduct. -/- Methods We collected scientific and medical codes of conduct in a selection of OECD countries, and submitted each code of conduct to comparative textual analysis. -/- Results Negligence is invariably listed as an infraction of the norms of integrity in medical codes of conduct, but only rarely so in the scientific codes. When the latter list negligence, they typically do not provide any detail on the meaning of ‘negligence’. -/- Discussion Unlike codes of conduct for professionals, current codes of conduct for scientists are largely silent on the issue of negligence, or explicitly exclude negligence as a type of misconduct. In the few cases where negligence is stipulated to constitute misconduct, no responsibilities are identified that would help prevent negligence. While we caution against unreasonable negligence provisions as well as disproportionate sanctioning systems, we do argue that negligence provisions are crucial for justified trust in the scientific community, and hence that there is a very strong rationale for including negligence provisions in codes of conduct. (shrink)

Famously, in the essay Inquiry Concerning the Distinctness of the Principles of Natural Theology and Morality (Prize Essay), Kant attempts to distance himself from the Wolffian model of philosophical inquiry. In this respect, Kant scholars have pointed out Kant’s claim that philosophy should not imitate the method of mathematics and his appeal to Newton’s “analytic method.” In this article, I argue that there is an aspect of Kant’s critique of the Wolffian model that has been neglected. Kant presents (...) a powerful attack of the idea that philosophy should proceed through the analysis of concepts and argues that we should give up the aim of arriving at “complete” concepts as one of its fundamental desiderata. Importantly, this attack of philosophy conceived as conceptual analysis is distinctive and original if one compares it with Kant’s critique of analysis in the Critique of Pure Reason, which rests on the idea that analysis is insufficient to ground substantial metaphysical truths. I also make an additional point: Scholars have debated whether the appeal to Newton’s analytic method involves a form of empiricism. I submit that this debate is ill-conceived because Kant uses a notion of “given concepts” that is indeterminate with respect to their a priori or a posteriori status. (shrink)

Romanian pedagogical theory rests on the assumption that any educational content can be taught and learned faster and better by recourse to a battery of teaching methods. In the present study we question that assumption and show that the methods generally recommended have no didactic merits when it comes to teaching philosophy and the human sciences. In order to prove that we commence by rendering manifest the origins, the specificity and the presuppositions of the teaching methods described in the literature. (...) Afterwards we determine the specificity of the objects of study of philosophy and the human sciences in general. On these bases we develop a series of three arguments that show why, given the particularity of both, the recourse to methods for teaching philosophy and the human sciences is inadequate. (shrink)

Academia is a competitive environment. Early Career Researchers (ECRs) are limited in experience and resources and especially need achievements to secure and expand their careers. To help with these issues, this book offers a new approach for conducting research using the combination of mindsponge innovative thinking and Bayesian analytics. This is not just another analytics book. 1. A new perspective on psychological processes: Mindsponge is a novel approach for examining the human mind’s information processing mechanism. This conceptual framework is used (...) to construct models in studies. The framework is highly flexible and widely applicable for many different types of information processes. The mindsponge approach can help researchers discover interesting ideas or even formulate their very own theories when investigating psychosocial phenomena. This approach brings a fresh wind to the current landscape of social sciences and humanities (SSH). 2. Easy-to-follow analysis protocol: The Bayesian Mindsponge Framework (BMF analytics) is useful in terms of computing and visualizing power but also easy to learn and apply. Contrary to being intimidating, the Bayesian analytics section of this book is presented in a reader-friendly manner with a detailed yet clear step-by-step procedure. Examples are from published BMF articles, allowing readers to immediately practice the method and quickly create their own applications. With educational purposes in mind, the book is very suitable for ECRs who are looking to innovate their research methods. 3. Advocating for low-cost, high-quality research: Doing science can be very costly. Mindsponge innovative thinking and BMF analytics help produce impactful studies using openly available data on online repositories. This is based on the authors’ previous works and experiences. The book presents examples of employing the open R package bayesvl on secondary data from different sources. With less financial constraints, researchers can have more freedom of thought to pursue their curiosity and creativity. ECRs in low- and middle-income countries may find this aspect crucial in their careers. 4. Support and collaboration: The authors share their insights from experiences in the academic publishing system to help readers get through the processes of manuscript writing and peer-reviewing more easily. The authors are also ready to support other researchers with further inquiries and collaboration opportunities at the following website, mindsponge(dot)info. This book is for: a) ECRs whose only abundant resources are their innovation capacity and strength of will; b) Researchers in SSH who want to explore a novel approach to thinking and study conducting; c) Low- and middle-income countries’ researchers looking for a cost-effective research protocol; and, d) Innovative thinkers who want to turn their interesting thoughts into good publications. (shrink)

In the present paper, our objective is to examine the application of belief revision models to scientific rationality. We begin by considering the standard model AGM, and along the way a number of problems surface that make it seem inadequate for this specific application. After considering three different heuristics of informational economy that seem fit for science, we consider some possible adaptations for it and argue informally that, overall, some paraconsistent models seem to better satisfy these principles, following Testa (...) (2015). These models have been worked out in formal detail by Testa, Cogniglio, & Ribeiro (2015, 2017). (shrink)

There is an ongoing debate on whether or to what degree computer simulations can be likened to experiments. Many philosophers are sceptical whether a strict separation between the two categories is possible and deny that the materiality of experiments makes a difference (Morrison 2009, Parker 2009, Winsberg 2010). Some also like to describe computer simulations as a “third way” between experimental and theoretical research (Rohrlich 1990, Axelrod 2003, Kueppers/Lenhard 2005). In this article I defend the view that computer simulations are (...) not experiments but that they are tools for evaluating the consequences of theories and theoretical assumptions. In order to do so the (alleged) similarities and differences between simulations and experiments are examined. It is found that three fundamental differences between simulations and experiments remain: 1) Only experiments can generate new empirical data. 2) Only Experiments can operate directly on the target system. 3) Experiments alone can be employed for testing fundamental hypotheses. As a consequence, experiments enjoy a distinct epistemic role in science that cannot completely be superseded by computer simulations. This finding in connection with a discussion of border cases such as hybrid methods that combine measurement with simulation shows that computer simulations can clearly be distinguished from empirical methods. It is important to understand that computer simulations are not experiments, because otherwise there is a danger of systematically underestimating the need for empirical validation of simulations. (shrink)

Scientific models share one central characteristic with fiction: their relation to the physical world is ambiguous. It is often unclear whether an element in a model represents something in the world or presents an artifact of model building. Fiction, too, can resemble our world to varying degrees. However, we assign a different epistemic function to scientific representations. As artifacts of human activity, how are scientific representations allowing us to make inferences about real phenomena? In reply to this concern, philosophers of (...) science have started analyzing scientific representations in terms of fictionalization strategies. Many arguments center on a dyadic relation between the model and its target system, focusing on structural resemblances and “as if” scenarios. This chapter provides a different approach. It looks more closely at model building to analyze the interpretative strategies dealing with the representational limits of models. How do we interpret ambiguous elements in models? Moreover, how do we determine the validity of model-based inferences to information that is not an explicit part of a representational structure? I argue that the problem of ambiguous inference emerges from two features of representations, namely their hybridity and incompleteness. To distinguish between fictional and non-fictional elements in scientific models my suggestion is to look at the integrative strategies that link a particular model to other methods in an ongoing research context. To exemplify this idea, I examine protein modeling through X-ray crystallography as a pivotal method in biochemistry. (shrink)

Science is founded on a method based on critical thinking. A prerequisite for this is not only a sufficient command of language but also the comprehension of the basic concepts underlying our understanding of reality. This constraint implies an awareness of the fact that the truth of the World is not directly accessible to us, but can only be glimpsed through the construction of mod- els designed to anticipate its behaviour. Because the relationship between models and reality rests (...) on the interpretation of founding postulates and in- stantiations of their predictions (and is therefore deeply rooted in language and culture), there can be no demarcation between science and non-science. However, critical thinking is essential to ensure that the link between models and reality is gradually made more adequate to reality, based on what has already been established, thus guaranteeing that science progresses on this basis and excluding any form of relativism. (shrink)

The clamour for scientific reasoning in philosophy is born out of a belief that scientific reasoning is infallible and universal. This paper argues that while scientific reasoning is infallible, it is so only with regard to the objects of knowledge in science. And because objects of knowledge are not the same across disciplines, claims that scientific reasoning is universal in its application are patently misplaced. -/- The belief in the universality of scientific reasoning has its genesis in what may (...) be called the ‘same genre argument’. If all objects of knowledge have a common essential and characteristic quality they can be put in a common basket and so belong to a common set. So far so good. The problem with this thesis arises when it is assumed that all objects of knowledge there can be (in this universe and beyond, if there is a beyond) are elements of that common universal set. If they are, they share an essential quality with and so belong to the same genre as material objects in our material universe. This essential quality is the material nature (mass and/or energy) of all matter in the phenomenal world, a quality that gives matter (a) objective reality and (b) makes it a percept. Scientific method is geared to studying percepts through a percept-perceiver one-to-one relationship. -/- If all objects of knowledge, however, are not material objects, they will neither be percepts nor show up as objective realities to perceiver/scientific observers and on their scientific tools. There are such objects. What was mere speculation once can be scientifically proven today. Only, the approach to the proof must be different. -/- There is a category of objects that are not material in nature; but they are objects of knowledge. These are called wholes. Examples of wholes are (i) God of Abrahamic religions; (ii) the Self/Brahman of the Upanishads; (iii) the universe in entirety. Every whole is characterized by dimensions. Dimensions are not objective realities because they are not material objects. Because they are not objective realities they are not objectively verifiable. Hence they will always elude science and scientific reasoning. That does not mean that they don’t exist. The universe is a whole. Its dimensions are space and time. Neither is objectively real; yet both are realities. -/- The paper concludes by considering the dynamics of logical progression from premise (axiom) to theorem. If the premise is wrong there can be no knowledge, no matter how powerful the logical apparatus that is used. (shrink)

Science and mathematics continually change in their tools, methods, and concepts. Many of these changes are not just modifications but progress---steps to be admired. But what constitutes progress? This dissertation addresses one central source of intellectual advancement in both disciplines: reformulating a problem-solving plan into a new, logically compatible one. For short, I call these cases of compatible problem-solving plans "reformulations." Two aspects of reformulations are puzzling. First, reformulating is often unnecessary. Given that we could already solve a problem (...) using an older formulation, what do we gain by reformulating? Second, some reformulations are genuinely trivial or insignificant. Merely replacing one symbol with another does not lead to intellectual progress. What distinguishes significant reformulations from trivial ones? According to what I call "conceptualism" (or "conceptual empiricism"), reformulations are intellectually significant when they provide a different plan for solving problems. Significant reformulations provide inferentially different routes to the same solution. In contrast, trivial reformulations provide exactly the same problem-solving plans, and hence they do not change our understanding. This answers the second question about what distinguishes trivial from significant reformulations. However, the first question remains: what makes a new way of solving an old problem valuable? Here, a bevy of practical considerations come to mind: one formulation might be faster, less complicated, or use more familiar concepts. According to "instrumentalism," these practical benefits are all there is to reformulating. Some reformulations are simply more instrumentally valuable for meeting the aims of science than others. At another extreme, "fundamentalism" contends that a reformulation is valuable when it provides a more fundamental description of reality. According to this view, some reformulations directly contribute to the metaphysical aim of carving reality at its joints. Conceptualism develops a middle ground between instrumentalism and fundamentalism, preserving their benefits without their costs. I argue that the epistemic value of significant reformulations does not reduce to either practical or metaphysical value. Reformulations are valuable because they are a constitutive part of problem-solving. Both science and mathematics aim at solving all possible problems within their respective domains. Meeting this aim requires being able to plan for any possible problem-solving context, and this requires reformulating. By reformulating, we clarify what we need to know to solve problems. Still, one might wonder whether the value of reformulations requires underlying differences in explanatory power. According to "explanationism," a reformulation is valuable only when it provides a better explanation. Explanationism stands as a rival middle ground position to my own. However, it faces numerous counterexamples. In many cases, two reformulations provide the same explanation while nonetheless providing different ways of understanding a phenomenon. Hence, reformulating can be valuable even when neither formulation is more explanatory. Methodologically, I draw on a variety of case studies to support my account of reformulation. These range from classical mechanics to quantum chemistry, along with examples from mathematics. Symmetry arguments provide a paradigmatic example: the mathematics of symmetry groups radically recasts quantum mechanics and quantum chemistry. Nevertheless, elementary approaches exist that eschew this additional mathematical apparatus, solving problems in a more tedious but less mathematically-demanding manner. Further examples include reformulations of quantum field theory, Arabic vs. Roman numerals, and Fermat's little theorem in number theory. In each case, my account identifies how reformulations change and improve our understanding of science and mathematics. (shrink)

The term ‘scientism’ has not attracted consensus about its meaning or about its scope of application. In this paper, we consider Mizrahi’s suggestion to distinguish ‘Strong’ and ‘Weak’ scientism, and the consequences this distinction may have for philosophical methodology. While we side with Mizrahi that his definitions help advance the debate, by avoiding verbal dispute and focussing on questions of method, we also have concerns about his proposal as it defends a hierarchy of knowledge production. Mizrahi’s position is that (...) Weak Scientism should be adopted, stating that “of all the knowledge we have, scientific knowledge is the best knowledge”. This version of scientism, however, has consequences for philosophical methodology. In particular, if one conceives of philosophy as an a priori discipline and holds Weak Scientism, the introduction of empirical methods in philosophy may threaten its very essence or soul. In this chapter, we will defend the move to adopt empirical methods in philosophy and argue that, rather than threatening its essence or soul, these methods put philosophy in a better position to contribute to knowledge production, an endeavor shared with the sciences, and in a very interdisciplinary spirit. Our point of disagreement with Mizrahi is that we should avoid any hierarchy of knowledge, and instead focus on what each perspective -- scientific, philosophical, historical, or other -- can contribute to understanding phenomena. (shrink)

The paper deals with the problem of future biology teachers’ vocational preparation process and shaping in them of those capacities that contribute to the conservation and enhancement of our planet’s biodiversity as a reflection of the leading sustainable development goals of society. Such personality traits are viewed through the prism of forming the future biology teachers’ professional and terminological competence. The main aspects and categories that characterize the professional and terminological competence of future biology teachers, including terminology, nomenclature, term, nomen (...) and term element, have been explained. The criteria and stages of shaping the future biology teachers’ professional and terminological competence during the vocational training process have been fixed. Methods, techniques, technologies, guiding principles and forms of staged work on the forming of an active terminological dictionary of students have been described and specified. The content of the distant special course “Latin. Botanical Terminology”, which provides training for future teachers to study the professional subjects and to understand of international scientific terminology, has been presented. It is concluded that the proper level of formation of the future biology teachers’ professional and terminological competence will eventually ensure the qualitative preparation of pupils for life in a sustainable development era. (shrink)

Kant maintains that his Critique of Pure Reason follows a “synthetic method” which he distinguishes from the analytic method of the Prolegomena by saying that the Critique “rests on no other science” and “takes nothing as given except reason itself”. The paper presents an account of the synthetic method of the Critique, showing how it is related to Kant’s conception of the Critique as the “science of an a priori judging reason”. Moreover, the author suggests, (...) understanding its synthetic method sheds light on the structure of the Transcendental Deduction, and its function in the work as a whole. (shrink)

There is widespread recognition at universities that a proper understanding of science is needed for all undergraduates. Good jobs are increasingly found in fields related to Science, Technology, Engineering, and Medicine, and science now enters almost all aspects of our daily lives. For these reasons, scientific literacy and an understanding of scientific methodology are a foundational part of any undergraduate education. Recipes for Science provides an accessible introduction to the main concepts and methods of scientific reasoning. (...) With the help of an array of contemporary and historical examples, definitions, visual aids, and exercises for active learning, the textbook helps to increase students’ scientific literacy. The first part of the book covers the definitive features of science: naturalism, experimentation, modeling, and the merits and shortcomings of both activities. The second part covers the main forms of inference in science: deductive, inductive, abductive, probabilistic, statistical, and causal. The book concludes with a discussion of explanation, theorizing and theory-change, and the relationship between science and society. The textbook is designed to be adaptable to a wide variety of different kinds of courses. In any of these different uses, the book helps students better navigate our scientific, 21st-century world, and it lays the foundation for more advanced undergraduate coursework in a wide variety of liberal arts and science courses. Selling Points Helps students develop scientific literacy—an essential aspect of _any_ undergraduate education in the 21 st century, including a broad understanding of scientific reasoning, methods, and concepts Written for all beginning college students: preparing science majors for more focused work in particular science; introducing the humanities’ investigations of science; and helping non-science majors become more sophisticated consumers of scientific information Provides an abundance of both contemporary and historical examples Covers reasoning strategies and norms applicable in all fields of physical, life, and social sciences, _as well as_ strategies and norms distinctive of specific sciences Includes visual aids to clarify and illustrate ideas Provides text boxes with related topics and helpful definitions of key terms, and includes a final Glossary with all key terms Includes Exercises for Active Learning at the end of each chapter, which will ensure full student engagement and mastery of the information include earlier in the chapter Provides annotated ‘For Further Reading’ sections at the end of each chapter, guiding students to the best primary and secondary sources available Offers a Companion Website, with: For Students: direct links to many of the primary sources discussed in the text, student self-check assessments, a bank of exam questions, and ideas for extended out-of-class projects For Instructors: a password-protected Teacher’s Manual, which provides student exam questions with answers, extensive lecture notes, classroom-ready Power Point presentations, and sample syllabi Extensive Curricular Development materials, helping any instructor who needs to create a Scientific Reasoning Course, ex nihilo. (shrink)

Is there a place in scientific inquiry for guessing? Jonathan Cohen has recently argued that resorting to guesswork entails a loss of objectivity and regard for evidence which are essential to proper scientific investigation. I assess the merits of Cohen’s view first by taking as a test case Aristotle’s positive view of the role of guesswork (anchinoia) and conjecture (eustochia) in the search for the connections essential to the construction of scientific demonstrations. I then argue contra Cohen that one can (...) usefully employ guesswork while also employing reason; that it is possible to guess either intelligently or mindlessly; and consequently, that the use of guesswork need not represent a diminution in respect for the objectivity essential to scientific investigation. Although I would not claim that guesswork has a role to play in all scientific inquiry, there appear to be some datable instances of the useful and respectable scientific guess. (shrink)

Engineering failure investigations seek to reconstruct the actual causes of major engineering failures. The investigators need to establish the existence of certain past events and the actual causal relationships that these events bear to the failures in question. In this paper, I examine one method for reconstructing the actual causes of failure events, which I call "feature dependence". The basic idea of feature dependence is that some features of an event are informative about the features of its causes; therefore, (...) the investigators can use the features of a known failure event to reconstruct details of its causes. I make explicit the structure of feature dependence and the evidential basis of its key premises, and show how feature dependence works in the investigation of the American Airlines Flight 191 accident. (shrink)

Can we find necessary and sufficient conditions for a mental state to be a pain state? That is, does pain have a nature? Or is the term ‘pain’ ambiguous? I argue here that our expression ‘pain’ lacks necessary use conditions if one considers a range of contexts. As use conditions constrain the reference class, I argue that ‘pain’ does not refer to a natural category, but binds together a bunch of loosely resembling phenomena. This leads to problems for scientific and (...) clinical discourse. To solve these, a method of explication is suggested, based on a discursive combination between analysis of first-person reports and theories of natural science. Lastly, I consider the ethical implications of this ambiguity that lead to a reformulation of the goal of pain science: Not alleviation of all pains ought to be our goal, but only manipulation of conscious and negatively emotionally charged pains. (shrink)

The classical theory of computation does not represent an adequate model of reality for simulation in the social sciences. The aim of this paper is to construct a methodological perspective that is able to conciliate the formal and empirical logic of program verification in computer science, with the interpretative and multiparadigmatic logic of the social sciences. We attempt to evaluate whether social simulation implies an additional perspective about the way one can understand the concepts of program and computation. We (...) demonstrate that the logic of social simulation implies at least two distinct types of program verifications that reflect an epistemological distinction in the kind of knowledge one can have about programs. Computer programs seem to possess a causal capability (Fetzer, 1999) and an intentional capability that scientific theories seem not to possess. This distinction is associated with two types of program verification, which we call empirical and intentional verification. We demonstrate, by this means, that computational phenomena are also intentional phenomena, and that such is particularly manifest in agent-based social simulation. Ascertaining the credibility of results in social simulation requires a focus on the identification of a new category of knowledge we can have about computer programs. This knowledge should be considered an outcome of an experimental exercise, albeit not empirical, acquired within a context of limited consensus. The perspective of intentional computation seems to be the only one possible to reflect the multiparadigmatic character of social science in terms of agent-based computational social science. We contribute, additionally, to the clarification of several questions that are found in the methodological perspectives of the discipline, such as the computational nature, the logic of program scalability, and the multiparadigmatic character of agent-based simulation in the social sciences. (shrink)

This is the second book by Baz that aims to show that a big chunk of contemporary philosophy is fundamentally misguided. His first book, When Words Are Called For: A Defense of Ordinary Language Philosophy (2012) adopted a therapeutic approach (in the Wittgensteinian style) to problems in contemporary epistemology, arguing that when properly thought through, the way philosophers talk about ‘knowing’ that something is the case ultimately does not make sense. Baz’s goal in his second book is less therapeutic and (...) more constructive: he aims to start a methodological revolution (in the Kuhnian sense)—to shake contemporary philosophers out of the unconscious habits of normal science and provoke them into making a radical change in the methods they use to do philosophy and the basic assumptions that motivate those methods. (shrink)

This dissertation concerns the methodology Kant employs in the first two sections of the Groundwork of the Metaphysics of Morals (Groundwork I-II) with particular attention to how the execution of the method of analysis in these sections contributes to the establishment of moral metaphysics as a science. My thesis is that Kant had a detailed strategy for the Groundwork, that this strategy and Kant’s reasons for adopting it can be ascertained from the Critique of Pure Reason (first Critique) (...) and his lectures on logic, and that understanding this strategy gains us interpretive insight into Kant’s moral metaphysics. At the most general level of methodology, Kant says there are four steps for the establishment of any science: 1) make distinct the idea of the natural unity of its material 2) determine the special content of the science 3) articulate the systematic unity of the science 4) critique the science to determine its boundaries The first two of these steps are accomplished by the genetically scholastic method of analysis, paradigmatically the method whereby confused and obscure ideas are made clear and distinct, thereby logically perfecting them and transforming them into possible grounds of cognitive insight that are potentially complete and adequate to philosophical purposes. The analysis of Groundwork I is a paradigmatic analysis that makes distinct what is contained in common understanding, i.e. its Inhalt or intension, making distinct the higher partial concepts that together define the concept of morality. The analysis of Groundwork II is an employment more specifically of the method of logical division, which makes distinct what is contained under the concept, i.e. its Umfang, by which the extension or object of morality is determined. Part I introduces Kant’s conception of moral metaphysical science and why he took it to be in need of establishment, explains the general method for establishing science and the scholastic method of analysis by which its first two steps are to be accomplished, then provides an interpretation of Groundwork I as an execution of this method. Part II details Kant’s determination of the special content of moral science in Groundwork II in relation to the central problem for moral metaphysics – how synthetic a priori practical cognition is possible. (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.

Preparing students for the real challenges in life is one of the most important goals in education. Constructivism is an approach that uses real-life experiences to construct knowledge. Problem-Based Learning (PBL), for almost five decades now, has been the most innovative constructivist pedagogy used worldwide. However, with the rising popularity, there is a need to revisit empirical studies regarding PBL to serve as a guide and basis for designing new studies, making institutional policies, and evaluating educational curricula. This need has (...) led the researchers to do a meta-analysis to analyse the effectiveness of PBL on secondary students’ achievement in different scientific disciplines. Following the set of inclusion and exclusion criteria, 11 studies in Eurasia, Africa, and America conducted from 2016 to 2020 have qualified for this study. Six of which focused on JHS (n = 1047) and five on SHS (n = 375). Studies were obtained from various meta-search engines including Google, ERIC, and JSTOR. Further, the researchers used Harzing’s Publish and Perish software to exhaust the search process. Sample size, mean, and standard deviation were analysed using the Comprehensive MetaAnalysis version 3 to determine the effect sizes (Hedge’s g) and the results of moderator analysis, forest plot, funnel plot, and Begg-Mazumdar test. Findings have shown that PBL, as an approach to teaching science, had a large and positive effect (ES = .871) on the achievement of secondary students. However, grade levels and various scientific disciplines did not influence students’ learning achievement. The conduct of more studies on the different factors affecting PBL implementation and specific effects of PBL on various student domains is recommended to facilitate comparative educational research in the future. (shrink)

This paper analyzes what it means for philosophy of science to be normative. It argues that normativity is a multifaceted phenomenon rather than a general feature that a philosophical theory either has or lacks. It analyzes the normativity of philosophy of science by articulating three ways in which a philosophical theory can be normative. Methodological normativity arises from normative assumptions that philosophers make when they select, interpret, evaluate, and mutually adjust relevant empirical information, on which they base their (...) philosophical theories. Object normativity emerges from the fact that the object of philosophical theorizing can itself be normative, such as when philosophers discuss epistemic norms in science. Metanormativity arises from the kind of claims that a philosophical theory contains, such as normative claims about science as it should be. Distinguishing these three kinds of normativity gives rise to a nuanced and illuminating view of how philosophy of science can be normative. (shrink)

Recent years have seen a surge in online collaboration between experts and amateurs on scientific research. In this article, we analyse the epistemological implications of these crowdsourced projects, with a focus on Zooniverse, the world’s largest citizen science web portal. We use quantitative methods to evaluate the platform’s success in producing large volumes of observation statements and high impact scientific discoveries relative to more conventional means of data processing. Through empirical evidence, Bayesian reasoning, and conceptual analysis, we show how (...) information and communication technologies enhance the reliability, scalability, and connectivity of crowdsourced e-research, giving online citizen science projects powerful epistemic advantages over more traditional modes of scientific investigation. These results highlight the essential role played by technologically mediated social interaction in contemporary knowledge production. We conclude by calling for an explicitly sociotechnical turn in the philosophy of science that combines insights from statistics and logic to analyse the latest developments in scientific research. (shrink)

Introduction to the Special Volume, “Method, Science and Mathematics: Neo-Kantianism and Analytic Philosophy,” edited by Scott Edgar and Lydia Patton. At its core, analytic philosophy concerns urgent questions about philosophy’s relation to the formal and empirical sciences, questions about philosophy’s relation to psychology and the social sciences, and ultimately questions about philosophy’s place in a broader cultural landscape. This picture of analytic philosophy shapes this collection’s focus on the history of the philosophy of mathematics, physics, and psychology. The (...) following essays uncover, reflect on, and exemplify modes of philosophy that are engaged with these allied disciplines. They make the case that, to the extent that analytic philosophers are still concerned with philosophy’s ties to these disciplines, we would do well to pay attention to neo-Kantian views on those ties. (shrink)

Engaging with the question of the extent to which the so-called human, economic or social sciences are actually sciences, this book moves away from the search for a criterion or definition that will allow us to sharply distinguish the scientific from the non-scientific. Instead, the book favours the pursuit of clarity with regard to the various enterprises undertaken by human beings, with a view to dissolving the felt need for such a demarcation. In other words, Read pursues a ‘therapeutic’ approach (...) to the issue of the status and nature of these subjects. Discussing the work of Kuhn, Winch and Wittgenstein in relation to fundamental question of methodology, Wittgenstein among the Sciences undertakes an examination of the nature of (natural) science itself, in the light of which a series of successive cases of putatively scientific disciplines are analysed. A novel and significant contribution to social science methodology and the philosophy of science and ‘the human sciences’, this book will be of interest to social scientists and philosophers, as well as to psychiatrists, economists and cognitive scientists. (shrink)

The social sciences face a problem of sample non-representation, where the majority of samples consist of undergraduate students from Euro-American institutions. The problem has been identified for decades with little trend of improvement. In this paper, I trace the history of sampling theory. The dominant framework, called the design-based approach, takes random sampling as the gold standard. The idea is that a sampling procedure that is maximally uninformative prevents samplers from introducing arbitrary bias, thus preserving sample representation. I show how (...) this framework, while good in theory, faces many challenges in application. Instead, I advocate for an alternative framework, called the model-based approach to sampling, where representative samples are those balanced in composition, however they were drawn. I argue that the model-based framework is more appropriate in the social sciences because it allows for systematic assessment of imperfect samples and methodical improvement in resource-limited scientific contexts. I end with practical proposals of improving sample quality in the social sciences. (shrink)

Whereas “Science does not think" (Heidegger), the "new historiography of science" - mainly Koyré's and Kuhn's ones - has addressed our minds to think about science in a new way. Recently Heelan suggested taking this new viewpoint for conceiving hermeneutic method in a more adequate way to present scientific practice. By an interpretative analysis of the categories of the above two historians, the present paper suggests a new way to conceive the foundations of science. Two (...) basic dichotomies result: on the kind of logic and on the kind of mathematics. They generate four models of scientific theory, sharply severed by the radical differences in their respective choices; that offers an accurate definition of incommensurability and even of an alternative scientific theory to a dominant one, which can be properly called a paradigm. In the past hermeneutic scholars gave negative appraisals on Western science; according to the new viewpoint recognising pluralism in the foundations of science, these appraisals concern the dominant paradigm only. In the light of the basic dichotomies a new way to define hermeneutics is suggested; it can be qualified in short by the following words: ‘The understanding of science is the science of understanding’. (shrink)

_ Source: _Volume 5, Issue 2, pp 228 - 250 Despite inroads made by critical realism against the ‘scientific method’ in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper (...) takes as a case study empirical research on the alleged empirical association between human resource management practices and organisational performance. By unpacking the confusion surrounding the two basic notions of prediction used, it reveals what is wrong with them, why the scientific method cannot actually make accurate predictions and why, therefore, the scientific method fails to meet its own criteria for scientificity. Finally, explanation is considered in order to prevent any confusion between it and prediction and to offer what we call _tendential prediction_. (shrink)

There is a need to bring about a revolution in the philosophy of science, interpreted to be both the academic discipline, and the official view of the aims and methods of science upheld by the scientific community. At present both are dominated by the view that in science theories are chosen on the basis of empirical considerations alone, nothing being permanently accepted as a part of scientific knowledge independently of evidence. Biasing choice of theory in the direction (...) of simplicity, unity or explanatory power does not permanently commit science to the thesis that nature is simple or unified. This current ‘paradigm’ is, I argue, untenable. We need a new paradigm, which acknowledges that science makes a hierarchy of metaphysical assumptions concerning the comprehensibility and knowability of the universe, theories being chosen partly on the basis of compatibility with these assumptions. Eleven arguments are given for favouring this new ‘paradigm’ over the current one. (shrink)

Contentious debate has played out in the ‘science wars’ generally, but perhaps nowhere has the possibility and value of objectivity been more controversial than in respect to the social sciences and historiography, the writing of history. Most of the individual social sciences took shape and became academic disciplines during the 19th century, and the issue of differences between studying humankind and studying the natural world goes back at least this far as well. How should we understand the relationship between (...) the human and natural sciences? Do the human and natural science share a common methodology, or are they quite dissimilar? If the “sciences of man, of society, and the state,” as Dilthey called the social sciences, try to emulate the physical sciences in their methods, will they perhaps miss what is distinctive about human existence? These and other questions are examined in Chapter 4. (shrink)