The rapidly changing field of genetics affects society through advances in health-care and through implications of genetic research. This study addresses the impacts of new genetic discoveries and technologies on different segments of today's society. The book begins with a chapter on genetic complexity, and subsequent chapters discuss moral and ethical questions arising from today's genetics from the perspectives of health care professionals, the media, the general public, special interest groups and commercial interests.

Causation is the main foundation upon which the possibility of science rests. Without causation, there would be no scientific understanding, explanation, prediction, nor application in new technologies. How we discover causal connections is no easy matter, however. Causation often lies hiddenfrom view and it is vital that we adopt the right methods for uncovering it. The choice of methods will inevitably reflect what one takes causation to be, making an accurate account of causation an even more pressing matter. This (...) enquiry informs the correct norms for an empirical study of the world. In Causation in Science and the Methods of Scientific Discovery, Rani Lill Anjum and Stephen Mumford propose nine new norms of scientific discovery. A number of existing methodological and philosophical orthodoxies are challenged as they argue that progress in science is being held back by an overlysimplistic philosophy of causation. (shrink)

This volume offers selected papers exploring issues arising from scientific discovery in the social sciences. It features a range of disciplines including behavioural sciences, computer science, finance, and statistics with an emphasis on philosophy. The first of the three parts examines methods of social scientific discovery. Chapters investigate the nature of causal analysis, philosophical issues around scale development in behavioural science research, imagination in social scientific practice, and relationships between paradigms of inquiry and scientific fraud. The next part (...) considers the practice of social science discovery. Chapters discuss the lack of genuine scientific discovery in finance where hypotheses concern the cheapness of securities, the logic of scientific discovery in macroeconomics, and the nature of that what discovery with the Solidarity movement as a case study. The final part covers formalising theories in social science. Chapters analyse the abstract model theory of institutions as a way of representing the structure of scientific theories, the semi-automatic generation of cognitive science theories, and computational process models in the social sciences. The volume offers a unique perspective on scientific discovery in the social sciences. It will engage scholars and students with a multidisciplinary interest in the philosophy of science and social science. (shrink)

What is the role of chance in scientific discovery? And, more to the point, if chance plays a key role in scientific discovery, what room is left for reason? These are grounding questions in the debates, for instance, over whether there is a distinction to be made between discovery and justification in science, and whether innate genius must play a role in discovery or if there exists some method that can be taught to anyone. While the role of chance (...) has been discussed throughout the history of science, it has resurfaced in recent debates over how science should be funded, and particularly in the field of biomedical research. The word serendipity, for example, has become increasingly... (shrink)

‘Serendipity’ is a category used to describe discoveries in science that occur at the intersection of chance and wisdom. In this paper, I argue for understanding serendipity in science as an emergent property of scientific discovery, describing an oblique relationship between the outcome of a discovery process and the intentions that drove it forward. The recognition of serendipity is correlated with an acknowledgment of the limits of expectations about potential sources of knowledge. I provide an analysis of (...) serendipity in science as a defense of this definition and its implications, drawing from theoretical and empirical research on experiences of serendipity as they occur in science and elsewhere. I focus on three interrelated features of serendipity in science. First, there are variations of serendipity. The process of serendipitous discovery can be complex. Second, a valuable outcome must be obtained before reflection upon the significance of the unexpected observation or event in respect to that outcome can take place. Therefore, serendipity is retrospectively categorized. Third, the primacy of epistemic expectations is elucidated. Finally, I place this analysis within discussions in philosophy of science regarding the impact of interpersonal competition upon the number and significance of scientific discoveries. Thus, the analysis of serendipity offered in this paper contributes to discussions about the social-epistemological aspects of scientific discovery and has normative implications for the structure of epistemically effective scientific communities. (shrink)

Abstract‘Serendipity’ is a category used to describe discoveries in science that occur at the intersection of chance and wisdom. In this paper, I argue for understanding serendipity in science as an emergent property of scientific discovery, describing an oblique relationship between the outcome of a discovery process and the intentions that drove it forward. The recognition of serendipity is correlated with an acknowledgment of the limits of expectations about potential sources of knowledge. I provide an analysis of (...) serendipity in science as a defense of this definition and its implications, drawing from theoretical and empirical research on experiences of serendipity as they occur in science and elsewhere. I focus on three interrelated features of serendipity in science. First, there are variations of serendipity. The process of serendipitous discovery can be complex. Second, a valuable outcome must be obtained before reflection upon the significance of the unexpected observation or event in respect to that outcome can take place. Therefore, serendipity is retrospectively categorized. Third, the primacy of epistemic expectations is elucidated. Finally, I place this analysis within discussions in philosophy of science regarding the impact of interpersonal competition upon the number and significance of scientific discoveries. Thus, the analysis of serendipity offered in this paper contributes to discussions about the social-epistemological aspects of scientific discovery and has normative implications for the structure of epistemically effective scientific communities. (shrink)

An important fact about human labor is that it can result not just in reproduction of what it started with, but in something new, a surplus product. When the latter is a means of production, it makes possible a mechanism of change consisting of reproduction by means of the expanded means of production. Each iteration of the labor process can differ from the preceding one insofar as it incorporates the surplus generated previously. Over the long-term, this cyclical process can lead (...) to the self-transformation of labor and, through it, of human societies and cultures. In this paper, I argue that this mechanism of change is also at work in the history of science. I argue that the form this mechanism takes in science is that of a feedback loop between discovery and instrument construction. This process requires the integration, and transformation into material form, of different kinds of knowledge. Based on this mechanism, I defend a concept of scientific progress as transcendence of the limitations of native human epistemic abilities. I also criticize narrowly biologistic approaches to the history of science for ignoring the role of surplus generation in transforming the labor process, and discuss some problems associated with viewing science as labor. (shrink)

The ArgumentScientific tools—measurement and calculation instruments, techniques of inference—straddle the line between the context of discovery and the context of justification. In discovery, new scientific tools suggest new theoretical metaphors and concepts; and in justification, these tool-derived theoretical metaphors and concepts are morelikely to be accepted by the scientific community if the tools are already entrenched in scientific practice.Techniques of statistical inference and hypothesis testing entered American psychology first as tools in the 1940s and 1950s and then as cognitive theories (...) in the 1960s and 1970s. Not only did psychologists resists statistical metaphors of mind prior to the institutionalization of inference techniques in their own practice; the cognitive theories they ultimately developed about “the mind as intuitive statistician” still bear the telltale marks of the practical laboratory context in which the tool was used. (shrink)

This paper analyzes features of the emergence of new fields in science by examining the cases of cytology and biochemistry. The first step in the emergence of these new fields was the discovery of a new entity. A subsequent claim was made that entities of this kind are found more generally; making this generalization constituted the construction of a new theory. As a line of research to test the theory began, a new domain was formed and the new field (...) emerged. In each case the theory proposed a new solution to an old problem in science. Some implications of this analysis for understanding the emergence of other fields are indicated. (shrink)

Name der Zeitschrift: Jahrbuch für Wissenschaft und Ethik Jahrgang: 20 Heft: 1 Seiten: 293-302.

Name der Zeitschrift: Jahrbuch für Wissenschaft und Ethik Jahrgang: 20 Heft: 1 Seiten: 237-240.

Multiple simultaneous independent discoveries, so well enunciated by Robert K. Merton in the early 1960s but already discussed for several hundreds of years, is a classic concept in the sociology of science. In this paper, the concept of multiple simultaneous independent errors is proposed, analyzed, and discussed. The concept of Selective Pessimistic Induction is proposed and used to connect MIDs with MIEs. Five types of MIEs are discussed: multiple errors in the interpretation of experimental data or computational results; (...) multiple misjudgments of the value of another’s research results or conclusions; multiple cases of false anticipation of achieving a certain experimental result; multiples of ignoring or omitting relevant precedents; and multiple instances of failure due to a not-yet-conceived scientific concept or principle. Causal MIDs and MIEs are those that can be traced directly to antecedent knowledge. Acausal MIDs and MIEs are those involving a consequential and identifiable leap from antecedent knowledge. Examples of causal and acausal MIEs are provided, mostly but not exclusively from the discipline of chemistry. Comparisons are made between MIDs and MIEs. Topics for future research are discussed and implications of these concepts are proposed. (shrink)

This book examines the historical development of studies of the brain and behavior from the early work of Aristotle and Galen up to the late twentieth century. Modern neuroscience, a multidisciplinary endeavor, emerged only recently as a unified field . This book does not treat the disciplinary history of neuroscience per se but, rather, the history of attempts to understand the nervous system and its relationship to behavior from a constellation of disciplines all related to what we now call “neuroscience”: (...) anatomy, physiology, psychology, psychiatry, evolutionary theory, and anthropology.Louise H. Marshall is a neuroscientist and director of the UCLA Brain Research Institute's Neuroscience History Archives. Her coauthor, the late neuroscientist Horace W. Magoun, founded the Department of Anatomy at UCLA's Medical School in 1953. Their book grew out of a series of poster presentations put together by Magoun for several national and international neuroscience meetings during the early 1980s. Magoun wrote a twenty‐seven‐page brochure after receiving much enthusiasm from neuroscientists at these meetings—both students and those more established in the field—and many wanted a publication.Not surprisingly, given its early beginnings in poster presentations, the book is richly illustrated. The chapters are arranged only loosely chronologically; their sequence is directed more explicitly by investigative themes. The first chapter outlines three basic “postulates” that direct the organization of the rest of the book and act as conceptual threads: phylogeny , the idea of a structural and functional hierarchy in the nervous system, and the notion that function determines structure. The last chapter, by way of discussion, moves into twentieth‐century developments in the understanding of certain “integrative” systems in the brain and the recognition by neuroscientists of the need for multidisciplinary approaches that integrate anatomical, physiological, and behavioral perspectives.The third postulate, the idea that “form follows function,” receives the most emphasis in the book, and most chapters touch on the oscillating relationship between studies of form and studies of function . The book also illustrates certain historical trends: the anatomical studies of the ancient and Renaissance periods, the more physiological and clinical studies of the nineteenth century, and the instrument‐centered approaches of early twentieth‐century neurophysiology.The book has certain strengths and weaknesses related to the authors' perspective as neuroscientists. As one might expect, elements of presentism arise, as the work of some investigators is described as “anticipating” that of later scientists, and other research—for example, J. L. W. Thudichum's work on brain chemistry—is deemed “surprisingly modern” . However, the book gives wonderfully detailed, precise accounts of scientific developments related to brain and behavior. The authors demonstrate a critical mastery of both primary and secondary sources, with thorough citations, and the book comes with a comprehensive bibliography.Discoveries in the Human Brain does not place neuroscientific developments within a wider cultural or social context, but the authors had no ambitions to do so. They even point to drawbacks of such historical approaches, arguing that they “create issues where none exist and … couch ideas in such convoluted language that the events and concepts become unfamiliar and difficult to fathom” . This position reflects their intended audience: neuroscientists interested in the history of their field. While there is certainly room for professional historians of science to tackle the history of neuroscience, this book will be valuable for historians because literature in the history of neuroscience is sparse. However, it is likely to be of greater value to neuroscientists—in the authors' words, “those workers at the bench who are curious to learn how it all happened.”. (shrink)

The idea of elegance in science is not necessarily a familiar one, but it is an important one. The use of the term is perhaps most clear-cut in mathematics - the elegant proof - and this is where Ian Glynn begins his exploration. Scientists often share a sense of admiration and excitement on hearing of an elegant solution to a problem, an elegant theory, or an elegant experiment. The idea of elegance may seem strange in a field of endeavour (...) that prides itself in its objectivity, but only if science is regarded as a dull, dry activity of counting and measuring. It is, of course, far more than that, and elegance is a fundamental aspect of the beauty and imagination involved in scientific activity. Ian Glynn, a distinguished scientist, selects historical examples from a range of sciences to draw out the principles of science, including Kepler's Laws, the experiments that demonstrated the nature of heat, and the action of nerves, and of course the several extraordinary episodes that led to Watson and Crick's discovery of the structure of DNA. With a highly readable selection of inspiring episodes highlighting the role of beauty and simplicity in the sciences, the book also relates to important philosophical issues of inference, and Glynn ends by warning us not to rely on beauty and simplicity alone - even the most elegant explanation can be wrong. (shrink)

The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more (...) fact-oriented and less theoretical than physics. However, the key leverageable idea is that careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While these have some universal application and demonstrate computational advantages, they are not theoretically mandated for the living. A new set of mathematical abstractions derived from biology can now be similarly extended. This is made possible by leveraging new formal tools to understand abstraction and enable computability. [The latter has a much expanded meaning in our context from the one known and used in computer science and biology today, that is "by rote algorithmic means", since it is not known if a living system is computable in this sense (Mossio et al., 2009).] Two major challenges constitute the effort. The first challenge is to design an original general system of abstractions within the biological domain. The initial issue is descriptive leading to the explanatory. There has not yet been a serious formal examination of the abstractions of the biological domain. What is used today is an amalgam; much is inherited from physics (via the bridging abstractions of chemistry) and there are many new abstractions from advances in mathematics (incentivized by the need for more capable computational analyses). Interspersed are abstractions, concepts and underlying assumptions “native” to biology and distinct from the mechanical language of physics and computation as we know them. A pressing agenda should be to single out the most concrete and at the same time the most fundamental process-units in biology and to recruit them into the descriptive domain. Therefore, the first challenge is to build a coherent formal system of abstractions and operations that is truly native to living systems. Nothing will be thrown away, but many common methods will be philosophically recast, just as in physics relativity subsumed and reinterpreted Newtonian mechanics. -/- This step is required because we need a comprehensible, formal system to apply in many domains. Emphasis should be placed on the distinction between multi-perspective analysis and synthesis and on what could be the basic terms or tools needed. The second challenge is relatively simple: the actual application of this set of biology-centric ways and means to cross-disciplinary problems. In its early stages, this will seem to be a “new science”. This White Paper sets out the case of continuing support of Information and Communication Technology (ICT) for transformative research in biology and information processing centered on paradigm changes in the epistemological, ontological, mathematical and computational bases of the science of living systems. Today, curiously, living systems cannot be said to be anything more than dissipative structures organized internally by genetic information. There is not anything substantially different from abiotic systems other than the empirical nature of their robustness. We believe that there are other new and unique properties and patterns comprehensible at this bio-logical level. The report lays out a fundamental set of approaches to articulate these properties and patterns, and is composed as follows. -/- Sections 1 through 4 (preamble, introduction, motivation and major biomathematical problems) are incipient. Section 5 describes the issues affecting Integral Biomathics and Section 6 -- the aspects of the Grand Challenge we face with this project. Section 7 contemplates the effort to formalize a General Theory of Living Systems (GTLS) from what we have today. The goal is to have a formal system, equivalent to that which exists in the physics community. Here we define how to perceive the role of time in biology. Section 8 describes the initial efforts to apply this general theory of living systems in many domains, with special emphasis on crossdisciplinary problems and multiple domains spanning both “hard” and “soft” sciences. The expected result is a coherent collection of integrated mathematical techniques. Section 9 discusses the first two test cases, project proposals, of our approach. They are designed to demonstrate the ability of our approach to address “wicked problems” which span across physics, chemistry, biology, societies and societal dynamics. The solutions require integrated measurable results at multiple levels known as “grand challenges” to existing methods. Finally, Section 10 adheres to an appeal for action, advocating the necessity for further long-term support of the INBIOSA program. -/- The report is concluded with preliminary non-exclusive list of challenging research themes to address, as well as required administrative actions. The efforts described in the ten sections of this White Paper will proceed concurrently. Collectively, they describe a program that can be managed and measured as it progresses. (shrink)

Human stories lie at the heart of professional practice in the human, social services, though these are often discounted when it comes to researching such services and sharing practice through publication. This article identifies and addresses certain methodological and epistemological biases and consequent challenges in human science research, and discusses the importance of story (autoethnography) and discovery (heuristics) in research which can inform practice, meaningfully and ethically. It considers this by addressing both research and publication, illustrating both the challenges (...) and the solutions from the authors’ own experiences. The article argues for reclaiming the subjective and the subjectivist dimension in human, social science, and, therefore, the experiential, in both research and publication; and addresses four problems with regard to publishing in the human sciences, namely: privilege, quality, anonymity in peer-review, and capital. (shrink)

With In Search of Mechanisms, Carl F. Craver and Lindley Darden offer both a descriptive and an instructional account of how biologists discover mechanisms. Drawing on examples from across the life sciences and through the centuries, Craver and Darden compile an impressive toolbox of strategies that biologists have used and will use again to reveal the mechanisms that produce, underlie, or maintain the phenomena characteristic of living things. They discuss the questions that figure in the search for mechanisms, characterizing the (...) experimental, observational, and conceptual considerations used to answer them, all the while providing examples from the history of biology to highlight the kinds of evidence and reasoning strategies employed to assess mechanisms. At a deeper level, Craver and Darden pose a systematic view of what biology is, of how biology makes progress, of how biological discoveries are and might be made, and of why knowledge of biological mechanisms is important for the future of the human species. (shrink)

An homage to the men and women of science, and an exposition of Einstein's place in scientific history In this fascinating collection of articles and speeches, Albert Einstein reflects not only on the scientific method at work in his own theoretical discoveries, but also eloquently expresses a great appreciation for his scientific contemporaries and forefathers, including Johannes Kepler, Isaac Newton, James Clerk Maxwell, Max Planck, and Niels Bohr. While Einstein is renowned as one of the foremost innovators of (...) modern science, his discoveries uniquely his own, through his own words it becomes clear that he viewed himself as only the most recent in a long line of scientists driven to create new ways of understanding the world and to prove their scientific theories. Einstein's thoughtful examinations explain the "how" of scientific innovations both in his own theoretical work and in the scientific method established by those who came before him. This authorized Philosophical Library book features a new introduction by Neil Berger, PhD, and an illustrated biography of Albert Einstein, which includes rare photos and never-before-seen documents from the Albert Einstein Archives at the Hebrew University of Jerusalem. "What place does the theoretical physicist's picture of the world occupy among all these possible pictures? It demands the highest possible standard of rigorous precision in the description of relations, such as only the use of mathematical language can give" -Albert Einstein, "Principles of Research" Albert Einstein (1879-1955) was born in Germany and became an American citizen in 1934. A world-famous theoretical physicist, he was awarded the 1921 Nobel Prize for Physics and is renowned for his Theory of Relativity. In addition to his scientific work, Einstein was an influential humanist who spoke widely about politics, ethics, and social causes. After leaving Europe, Einstein taught at Princeton University. His theories were instrumental in shaping the atomic age. Neil Berger, an associate professor emeritus of mathematics, taught at the University of Illinois at Chicago in the Mathematics, Statistics, and Computer Science department from 1968 until his retirement in 2001. He was the recipient of the first Monroe H. Martin Prize (1975), which is now awarded by the University of Maryland every five years for a singly authored outstanding applied mathematics research paper. He has published numerous papers and reviews in his fields of expertise, which include elasticity, tensor analysis, scattering theory, and fluid mechanics. (shrink)

All types of logic started with Aristotle and have been corrected as a traditional, formal, conditional, classical logic and even modern logic carry the main problems of Aristotelian logic. Despite their important differences, because of these core commonalities they are all called Classical Logic. The fundamental limitations of classical logic make it impossible to advance the knowledge necessary to solve growing human problems. All human knowledge, especially scientific knowledge is based on the logical principles that seem to hinder the knowledge (...) of reality rather than facilitate it; although in the beginning, this logic has helped mankind in acquiring knowledge. Fuzzy logic has been successful as an effective solution in science and in practice, but it lacks the necessary philosophical foundations so it has faced with several major problems and on important paradox in theorizing. First, the main challenges in classical logic are diseased in this article, then it is explained how to solve the problems and most important paradox to apply the fuzzy logic for scientific discoveries in a new approach. Finally, the new paradigm of Fuzziological Epistemology (fuzzy based epistemology) has been proposed in term of Dynamic Fuzzy Puzzle Theory. (shrink)