Predictive policing has become a new panacea for crime prevention. However, we still know too little about the performance of computational methods in the context of predictive policing. The paper provides a detailed analysis of existing approaches to algorithmic crime forecasting. First, it is explained how predictive policing makes use of predictive models to generate crime forecasts. Afterwards, three epistemologies of predictive policing are distinguished: mathematical social science, social physics and machine learning. Finally, it is shown (...) that these epistemologies have significant implications for the constitution of predictive knowledge in terms of its genesis, scope, intelligibility and accessibility. It is the different ways future crimes are rendered knowledgeable in order to act upon them that reaffirm or reconfigure the status of criminological knowledge within the criminal justice system, direct the attention of law enforcement agencies to particular types of crimes and criminals and blank out others, satisfy the claim for the meaningfulness of predictions or break with it and allow professionals to understand the algorithmic systems they shall rely on or turn them into a black box. By distinguishing epistemologies and analysing their implications, this analysis provides insight into the techno-scientific foundations of predictive policing and enables us to critically engage with the socio-technical practices of algorithmic crime forecasting. (shrink)

This chapter contains sections titled: Why Use Mathematical Models? Theory‐based Models Data‐based Modeling Computational Approaches Conclusions Notes.

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.

This study provides a basic introduction to agent-based modeling (ABM) as a powerful blend of classical and constructive mathematics, with a primary focus on its applicability for social science research. The typical goals of ABM social science researchers are discussed along with the culture-dish nature of their computer experiments. The applicability of ABM for science more generally is also considered, with special attention to physics. Finally, two distinct types of ABM applications are summarized in order (...) to illustrate concretely the duality of ABM: Real-world systems can not only be simulated with verisimilitude using ABM; they can also be efficiently and robustly designed and constructed on the basis of ABM principles. (shrink)

Aims and Scope -/- The Vietnamese Social Sciences and Humanities at a Fork in the Road, utilizing an object-oriented structured database on the productivity of Vietnamese researchers, seeks to provide a comprehensive overview of the development of Social Sciences and Humanities in Vietnam from 2008 to 2018. -/- Quan-Hoang Vuong (Ph.D., Université Libre de Bruxelles) is the director of Centre for Interdisciplinary Social Research, Phenikaa University in Hanoi, Vietnam. He is chairman of the Vietnam chapter of the (...) European Association of Science Editors and serves in the NAFOSTED Scientific Council on Basic Research in the Social Sciences and Humanities (2019-2021). Dr. Vuong has published more than 120 academic articles, and book chapters in about 50 refereed journals and books by such publishers as Elsevier, Inderscience, Nature Publishing Group, Springer, Praeger, Wiley, World Scientific, etc. -/- Trung Tran is an Associate Professor of Mathematics Education and works at Vietnam Academy for Ethnic Minorities. He is a member of the Vietnam chapter of The European Association of Science Editors (EASE), a leader of the Vietnamese Science Editors (VSE) Team, and a chairman of Editor's Board of Journal of Ethnic Minorities Research (ISSN: 0866-773X). (shrink)

Current mathematical models are notoriously unreliable in describing the time evolution of unexpected social phenomena, from financial crashes to revolution. Can such events be forecast? Can we compute probabilities about them? Can we model them? This book investigates and attempts to answer these questions through GOdel's two incompleteness theorems, and in doing so demonstrates how influential GOdel is in modern logical and mathematical thinking. Many mathematical models are applied to economics and social theory, while GOdel's (...) theorems are able to predict their limitations for more accurate analysis and understanding of national and international events. This unique discussion is written for graduate level mathematicians applying their research to the social sciences, including economics, social studies and philosophy, and also for formal logicians and philosophers of science. (shrink)

The tremendous recent growth of the women's movement as a political force has been accompanied by an event of equal import to the academic world--the development of the discipline of women's studies. Colleges across the nation are establishing programs in this area. Women's Studies is a classroom anthology designed for use in these newly-introduced courses.

Over the years, mathematics and statistics have become increasingly important in the social sciences1 . A look at history quickly confirms this claim. At the beginning of the 20th century most theories in the social sciences were formulated in qualitative terms while quantitative methods did not play a substantial role in their formulation and establishment. Moreover, many practitioners considered mathematical methods to be inappropriate and simply unsuited to foster our understanding of the social domain. Notably, the (...) famous Methodenstreit also concerned the role of mathematics in the social sciences. Here, mathematics was considered to be the method of the natural sciences from which the social sciences had to be separated during the period of maturation of these disciplines. All this changed by the end of the century. By then, mathematical, and especially statistical, methods were standardly used, and their value in the social sciences became relatively uncontested. The use of mathematical and statistical methods is now ubiquitous: Almost all social sciences rely on statistical methods to analyze data and form hypotheses, and almost all of them use (to a greater or lesser extent) a range of mathematical methods to help us understand the social world. Additional indication for the increasing importance of mathematical and statistical methods in the social sciences is the formation of new subdisciplines, and the establishment of specialized journals and societies. Indeed, subdisciplines such as Mathematical Psychology and Mathematical Sociology emerged, and corresponding journals such as The Journal of Mathematical Psychology (since 1964), The Journal of Mathematical Sociology (since 1976), Mathematical Social Sciences (since 1980) as well as the online journals Journal of Artificial Societies and Social Simulation (since 1998) and Mathematical Anthropology and Cultural Theory (since 2000) were established. What is more, societies such as the Society for Mathematical Psychology (since 1976) and the Mathematical Sociology Section of the American Sociological Association (since 1996) were founded. Similar developments can be observed in other countries. The mathematization of economics set in somewhat earlier (Vazquez 1995; Weintraub 2002). However, the use of mathematical methods in economics started booming only in the second half of the last century (Debreu 1991). Contemporary economics is dominated by the mathematical approach, although a certain style of doing economics became more and more under attack in the last decade or so. Recent developments in behavioral economics and experimental economics can also be understood as a reaction against the dominance (and limitations) of an overly mathematical approach to economics. There are similar debates in other social sciences. It is, however, important to stress that problems of one method (such as axiomatization or the use of set theory) can hardly be taken as a sign of bankruptcy of mathematical methods in the social sciences tout court. This chapter surveys mathematical and statistical methods used in the social sciences and discusses some of the philosophical questions they raise. It is divided into two parts. Sections 1 and 2 are devoted to mathematical methods, and Sections 3 to 7 to statistical methods. As several other chapters in this handbook provide detailed accounts of various mathematical methods, our remarks about the latter will be rather short and general. Statistical methods, on the other hand, will be discussed in-depth. (shrink)

This is an expanded and thoroughly revised edition of the widely adopted introduction to the philosophical foundations of the human sciences. Ranging from cultural anthropology to mathematical economics, Alexander Rosenberg leads the reader through behaviorism, naturalism, interpretativism about human action, and macrosocial scientific perspectives, illuminating the motivation and strategy of each.Rewritten throughout to increase accessibility, this new edition retains the remarkable achievement of revealing the social sciences’ enduring relation to the fundamental problems of philosophy. It includes new discussions (...) of positivism, European philosophy of history, causation, statistical laws, quantitative models, and postempiricist social science, along with a completely updated literature guide that keys chapters to widely anthologized papers. (shrink)

The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This first volume focuses on the scope of computational social science, ethics, and case studies. (...) It covers a range of key issues, including open science, formal modeling, and the social and behavioral sciences. This volume explores major debates, introduces digital trace data, reviews the changing survey landscape, and presents novel examples of computational social science research on sensing social interaction, social robots, bots, sentiment, manipulation, and extremism in social media. The volume not only makes major contributions to the consolidation of this growing research field, but also encourages growth into new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates and researchers engaging with computational methods across the social sciences, as well as those within the scientific and engineering sectors. (shrink)

Galileo and his fellowers discovered, and subsequent centuries have amply confirmed, that you get much better predictions by thinking of things as masses of particles blindly bumping each other than by thinking of them as Aristotle thought of them — animistically, teleologically, anthromorphically. They also discovered that you get a better handle on the universe by thinking of it as infinite and cold and comfortless than by thinking of it as finite, homey, planned, and relevant to human concerns. Finally, they (...) discovered that if you view planets or missiles or corpuscles as point-masses, you can get nice simple predictive laws by looking for nice simple mathematical ratios. These discoveres are the basis of modern technological civilization. We can hardly be too grateful for them. But they do not, pace Descartes and Kant, point any epistemological moral. (shrink)

At first glance singularity would seem to be necessarily opposed to the physical sciences, indeed to any kind of science. As the hallowed saying goes: “Science deals only in universals.” According to this view, the aim of any true scientific endeavor must be the discovery of universals or, in other words, the value of such an endeavor is based on its ability to explain phenomena in terms of universals. The status of singularity in science is a direct (...) result of this approach. Singularity is associated with the presence, either in a person or an object, of an unusual or exceptional quality, or of an individual trait. Singularity so conceived must therefore be seen as inherently compromising the aims of any scientific endeavor, since the purpose of that endeavor is universality as defined above. In this sense, the basis of scientific explication is the ability to determine a feature common to a collection of objects, thus allowing them to be explained by deductive reasoning. This common feature can therefore not be individual, if individual is understood as unusual or exceptional. (shrink)

The author finds no support for the claim that J. M. Keynes had severe reservations, in general, as opposed to particular, concerning the application of mathematical, logical and statistical methods in economics. These misinterpretations rest on the omission of important source material as well as a severe misconstrual ofThe Treatise on Probability (1921).

The approach of structuralism came to philosophy from social science. It was also in social science where, in 1950–1970s, in the form of the French structuralism, the approach gained its widest recognition. Since then, however, the approach fell out of favour in social science. Recently, structuralism is gaining currency in the philosophy of mathematics. After ascertaining that the two structuralisms indeed share a common core, the question stands whether general structuralism could not find its (...) way back into social science. The nature of the major objections raised against French structuralism – concerning its alleged ahistoricism, methodological holism and universalism – are reconsidered. While admittedly grounded as far as French structuralism is concerned, these objections do not affect general structuralism as such. The fate of French structuralism thus does not seem to preclude the return of general structuralism into social science, rather, it provides some hints where the difficulties may lie. (shrink)

The approach of structuralism came to philosophy from social science. It was also in social science where, in 1950–1970s, in the form of the French structuralism, the approach gained its widest recognition. Since then, however, the approach fell out of favour in social science. Recently, structuralism is gaining currency in the philosophy of mathematics. After ascertaining that the two structuralisms indeed share a common core, the question stands whether general structuralism could not find its (...) way back into social science. The nature of the major objections raised against French structuralism – concerning its alleged ahistoricism, methodological holism and universalism – are reconsidered. While admittedly grounded as far as French structuralism is concerned, these objections do not affect general structuralism as such. The fate of French structuralism thus does not seem to preclude the return of general structuralism into social science, rather, it provides some hints where the difficulties may lie. (shrink)

Several case studies and theoretical reports indicate that the structuralist concept of a constraint has a central role in the reconstruction of physical theories. It is surprising that there is, in the literature, only little theoretical discussion on the relevance of constraints for the reconstruction of social scientific theories. Almost all structuralist reconstructions of social theorizing are vacuously constrained. Consequently, constraints are methodologically irrelevant.In this paper I try to show that there really exist constraint-type assumptions in mathematical (...) modelling in the social sciences. Methodologically constraints have exactly the same role in the context of social mathematical modelling as they have in physical theories. In typical cases of mathematical modelling in the social sciences, the related constraints work as empirical hypotheses and should be tested by statistical means. (shrink)

Contemporary social science tends to suffer from too many misplaced attempts at mathematical or game-theoretical formulation, and much effort is wasted in either propounding such formulations, or in showing their inanity. Jon Elster does not entirely escape this himself, but Logic and Society is truly remarkable in pointing the way to some possibly very relevant formalizations. These are particularly to be found in the chapter on 'contradictions of society'. There Elster attempts to delineate the properties of certain (...) self-frustrating predicaments of action, and to relate them as well to Hegelian-Marxist conceptions of contradiction. It may be, however, that the relevance of this analysis is restricted to societies whose form of life has become atomistic, and whose members thus function in an individual-calculative way in many spheres of life. But even so, formalizations of the kind Elster provides would be useful in defining one kind of historically evolved society among others. (shrink)

A collection of papers delivered at a colloquium in 1960. Most are quite brief; all are at a rather high level of technical sophistication. Of general interest are L. Apostel's "Toward the Formal Study of Models in the Non-Formal Sciences," which concludes that a unique definition of models in terms of their function should be the basis for a general description of this "multiform concept"; H. Freudenthal's discussion of "models in Applied Probability"; a historical treatment of "Model and Insight" by (...) A. Kuipers; and P. Suppes's "Comparison of the Meaning and Uses of Models in Mathematics and the Empirical Sciences," which stresses the "set-theoretical" notion of model and emphasizes the possibility of greater formalization of the empirical sciences through the former. Among other authors represented are E. W. Beth, J. L. Destouches, and J. B. Ubbink.--R. D. P. (shrink)

Our aim in this article is to put into practice, in the field of social sciences, the principles that Husserl displayed in his book from 1936, "The crisis of European sciences and transcendental phenomenology”. In that seminal work, Husserl reflected on the mathematization of nature and produced an historical meditation on the essence of geometry. Here we will try to extend the reach of Husserlian postulates in order to deal with economics and, more specifically, with the theory of money. (...) We think that, in certain social sciences, and in particular in those with a clear mathematical penchant like economics, the use of formalization often helps to cover an uncritical use of phenomenologically ungrounded idealizations. This fact ultimately results in a massive concealment of the true sense of some of its principal phenomenanamely, money. It is worth mentioning that this concern does not have its roots only in phenomenology, for even academic monetary theory openly acknowledges that we lack an understanding of the meaning of money which could help us clarify and prevent financial crisis and economic collapses. Crisis, in short, are not the result of a deep understanding of the concept of money; on the contrary, they highlight the fact that we don’t really know what money is. Thus, our goal here is to illustrate the possibilities offered by the phenomenological method in its application to the question of money. It is in this sense that the research taking place here can be understood as a “phenomenological critique of monetary theory”.En el presente artículo se pretende llevar a cabo una aplicación de los principios que Husserl lleva a cabo en su obra de 1936, “La crisis de las ciencias europeas y la fenomenología transcendental”, a las ciencias sociales; concretamente, al concepto de dinero. En su obra de 1936, Husserl puso el énfasis en la matematización de la naturaleza, centrándose sobre todo en la meditación histórica sobre la geometría. Pero en el caso de algunas ciencias sociales, como la economía, la utilización libre de construcciones idealizadoras fenomenológicamente infundadas, como en el caso del dinero, está teniendo como resultado un enorme encubrimiento de sentido del fenómeno monetario. Esto no es vivido tan solo desde la feno-menología: desde la propia teoría monetaria se reconoce que estamos faltos de una comprensión del sentido del dinero que nos ayude a clarificar y prevenir de manera suficiente las crisis financieras. Estas crisis no son fruto de que hayamos comprendido demasiado bien el concepto de dinero, sino de que todavía estamos faltos de una comprensión profunda del sentido del dinero. Aquí pretendemos ilustrar las posibilidades que el método fenomenológico ofrece, aplicado al caso del dinero. En este sentido, pueden considerarse las investigaciones que tienen lugar aquí como “crítica fenomenológica de la teoría monetaria”. (shrink)

It is generally agreed that a strong line of continuity in Wittgenstein’s writings, from the early Tractatus Logico-Philosophicus to the late Philosophical Investigations, is marked by his constant preoccupation with questions about language and meaning. Here I argue that another and equally important continuity lies in his attitude towards science, here understood as including logic, geometry and mathematics. His early work shows him deeply impressed by these disciplines, which in many ways supplied the model for his ideas about language (...) and meaning. Later, he came to see that he had been ‘captured’ by these scientific ‘pictures’, and in numerous ways he set out to show that our thinking about how we understand the world, ourselves and each other and the degree of certainty that it is desirable and possible to achieve, can take many different forms. When the social sciences today are often denigrated for lacking the ‘rigour’ and certainty of the physical science, and when some social scientists respond by trying to borrow or imitate the methods of the physical sciences, Wittgenstein’s repudiation of the ‘picture’ of science and his welcoming of a broader conception of knowledge and understanding are of great value to educational researchers and social scientists of all kinds. (shrink)

Structural realism is arguably one of the most influential movements to have emerged in philosophy of science in the last decade or so. Advocates of this movement attempt to answer epistemological and/or ontological questions concerning science by arguing that the key to all such questions is the mathematical formalism of a theory. This is so, according to structural realists, because the mathematical formalism encodes all and only what is important about a theory’s target domain, namely its (...) structure. Almost without exception, discussions of structural realism centre on the natural sciences and in particular on modern physics. Given that a number of other sciences are less – indeed in some cases much less – mathematised than modern physics, does structural realism have anything informative to say about them? In this talk, I take up the task of articulating what structural realists ought to say about the social sciences if they are to consider themselves as offering a coherent philosophy for the whole of science. (shrink)

This volume represents a magnum opus by Wolfgang Weidlich, summarizing his long work in the area of sociodynamics. It lays out the origins and development of his ideas on this topic, presents a variety of applications drawn from his previous work, and offers some new insights and suggestions. For those acquainted with Professor Weidlich’s work it is a satisfying summing up. For those unacquainted with it, the book provides a good overview and discussion of what is involved in it, both (...) its weaknesses and its strengths. It has a definite predecessor, Weidlich’s 1983 book with his frequent coauthor, Günter Haag, Concepts and Models of a Quantitative Sociology, but goes well beyond the arguments and models presented in that volume. (shrink)

Kitcher's philosophical approach has moved from the reflection on the nature of mathematical knowledge to an explicit social concern about science, because he considers seriously the relevance of democratic values to scientific activity. Focal issues in this trajectory - from the internal perspective to the external - have been naturalism and scientific progress, which includes studies of the uses of scientific findings in the social milieu. Within this intellectual context, the chapter pays particular attention to his (...) epistemological and methodological evolution. The analysis of Philip Kitcher's contents on progress begins with mathematics, a conception that follows a naturalist perspective. Thereafter, the growth of science comes to the front line, an advancement that he views according to realism and cognitive naturalism. Later, the social concern about science receives a visible consideration, when his vision of scientific undertaking is characterized following modest realism and social naturalism. After these four steps (philosophical context, progress in mathematics, the growth in science, and the social concern about science), there is an analysis of his philosophical-methodological framework in retrospective. This is continued by the presentation of the origins of this book and the bibliography related to this thinker. (shrink)

This broad and insightful book presents current scholarship in important subfields of philosophy of science and addresses an interdisciplinary and multidisciplinary readership. It groups carefully selected contributions into the four fields of I) philosophy of physics, II) philosophy of life sciences, III) philosophy of social sciences and values in science, and IV) philosophy of mathematics and formal modeling. Readers will discover research papers by Paul Hoyningen-Huene, Keizo Matsubara, Kian Salimkhani, Andrea Reichenberger, Anne Sophie Meincke, Javier Suárez, Roger (...) Deulofeu, Ludger Jansen, Peter Hucklenbroich, Martin Carrier, Elizaveta Kostrova, Lara Huber, Jens Harbecke, Antonio Piccolomini d'Aragona and Axel Gelfert. This collection fosters dialogue between philosophers of science working in different subfields, and brings readers the finest and latest work across the breadth of the field,illustrating that contemporary philosophy of science has successfully broadened its scope of reflection. It will interest and inspire a wide audience of philosophers as well as scholars of the natural sciences, social sciences and the humanities. The volume shares selected contributions from the prestigious second triennial conference of the German Society for Philosophy of Science/ Gesellschaft für Wissenschaftsphilosophie (GWP.2016, March 8, 2016 - March 11, 2016). (shrink)

This paper presents the outline of an ontology of the social realm that aims to provide a new perspective to the study of social phenomena. It will be argued that in order to raise the impact of the social sciences, research should start from a new ontological discursive perspective. This implies that rather than dividing the social and psychological realm into different “disciplines”, the social and the psychological realm need to be imagined as two sides (...) of the same coin. And also, that space and time should not be regarded as the primary referential grid for the social sciences but conversations and people. Within this perspective the “substance” of the social realm can be imagined as a species-wide and history-long web of conversations between people in which speech-acts are the basic forces that create agents and structures. The power of speech-acts is in essence non-local: it does not matter much where and when they occur, but rather by whom and in which conversational contexts they are uttered. This can be captured by the metaphor of social entanglement where social events have particular bonds that transcend space and time. All of this resonates more with the probabilistic realm of quantum physics than with the Newtonian world were causality reigns. (shrink)

The on-the-ground case conference at the interface of philosophical ethics and clinical psychiatry is an innovative idea that advances pedagogy in presenting a creative approach to teaching and practicing psychiatric ethics. In the current exercise of the proposed partnership, there was a generally positive outcome. The philosopher and the psychiatrist learned from each other, were able to find norms that made their collaboration productive, and found that clinical care was enhanced. My commentary aims to help others replicate this model, and (...) preserve its virtues without its vulnerabilities.Would a mathematical logician or philosopher of aesthetics be as good of a collaborator as a moral philosopher? Probably not.... (shrink)

The article explores the transformative impact on human and social sciences in response to anticipated societal shifts driven by the forthcoming proliferation of artificial systems, whose intelligence will match human capabilities. Initially, it was posited that artificial intelligence (AI) would excel beyond human abilities in computational tasks and algorithmic operations, leaving creativity and humanities as uniquely human domains. However, recent advancements in large language models have significantly challenged these conventional beliefs about AI’s limitations and strengths. It is projected that, (...) in the near future, generative AI models will adeptly replicate individual qualities, desires, beliefs, opinions, and the essence of human identity and consciousness to a degree that is nearly indistinguishable from that of humans. This lends support to the connectionist approach to understanding consciousness, suggesting an inherent similarity between biological and artificial neural networks. The discussion posits two innovative areas of scientific inquiry: “mathematical anthropology” and “multi-dimensional calculus of value.” The former suggests that viewing human nature through a mathematical and calculative lens not only preserves but enriches our understanding of the complexity of anthropological experience and its perceived contradictions. The latter hypothesis explores how mathematical models could facilitate various social interactions. The advanced simulation capabilities of neural networks suggest that traditional social and political frameworks face a growing vulnerability to AI-driven manipulations. This trend underscores the urgency of developing social interaction models that incorporate explicitly defined calculative rules. In conclusion, the paper advocates for a paradigm shift in how mathematics is perceived – not merely as a tool for computation but as a foundational science for crafting sophisticated models. In conclusion, the article advocates for transitioning from perceiving mathematics solely as a science of computation to viewing it as a discipline dedicated to constructing various formalized models, thereby deepening our insight into the complexities of human and social phenomena. (shrink)

Philosophizing about the social sciences involves an initial problem of denotation. Although the natural sciences are the scene of intramural disputes like those between proponents of quantum mechanics and relativity theory, no one doubts either what the natural sciences are or that they are sciences; and all of them may be said to use, broadly speaking, the same scientific method. But the case of the social sciences is different. It resembles somewhat the situation in mathematics where the intuitionists (...) deny that non-constructible concepts or problems belong to mathematics; and even more the situation in philosophy where groups like the analysts and the existentialists not only do not speak the same language but do not even recognize one another's right to be called “philosophy.” Similarly, the disciplines which comprise the social sciences today differ from one another in basic ways, involving long-standing disputes over which ones have a right to the names of the several social sciences and what their proper methods are. Familiar examples of these disputes are the controversies between the classicists and institutionalists in economics, and between the analytical and sociological schools in jurispurdence. Consequently, it is impossible for philosophers, or social scientists philosophizing about their general field, to proceed to discuss “the” subject-matter or “the” method of “the” social sciences as if the phrases containing these definite articles were definite descriptions on whose objects there was general agreement. (shrink)

This book contributes to the developing dialogue between cognitive science and social sciences. It focuses on a central issue in both fields, i.e. the nature and the limitations of the rationality of beliefs and action. The development of cognitive science is one of the most important and fascinating intellectual advances of recent decades, and social scientists are paying increasing attention to the findings of this new branch of science that forces us to consider many classical (...) issues related to epistemology and philosophy of action in a new light. This book encourages scholars from different fields who are interested in the dialogue between cognitive science and social sciences, to develop and analyze new perspectives that allow us to elucidate the mystery of rationality. What is rationality? What are its limitations? What rationality assumptions must be used to study social and economic phenomena? The target audience primarily comprises researchers and experts in the field. Analysis of the concept of rationality is a leitmotiv in the history of the social sciences and has involved endless disputes. Since it is difficult to give a precise definition of this concept, and there is a lack of agreement about its meaning, it is possible to say that there is a ‘mystery of rationality’. What is it to be rational? Is rationality merely instrumental or does it also involve the endorsement of values, i.e. the choice of goals? Should we consider rationality to be a normative principle or a descriptive one? Can rationality be only Cartesian or can it also be argumentative? Is rationality a conscious skill or a partly tacit one? This book, which has been written by an outstanding collection of authors, including both philosophers and social scientists, tries to make a useful contribution to the debates on these problems and shed some light on the mystery of rationality. (shrink)

Mathematical models are potentially as useful for culture as for evolution, but cultural models must have different designs from genetic models. Social sciences must borrow from biology the idea of modeling, rather than the structure of models, because copying the product is fundamentally different from copying the design. Transfer of most cultural information from brains to artificial media increases the differences between cultural and biological information. (Published Online November 9 2006).

Recent developments in social science methods have made most of the objectivism-subjectivism arguments in the philosophy of social science obsolete. Developments in experimental methods have made possible a behavioristic treatment of everything cherished as important in human action by the subjectivists; developments in computer and mathematical models have made possible a type of theory which carries out the program of the subjectivists but is not vulnerable to the arguments of the objectivists. What remains of the (...) philosophical argument are two types of theory (for example, game theory and learning theory) which are both useful, both scientific, and frequently equivalent. Choice between them by scientists can be made on empirical grounds rather than on the grounds developed in the philosophical controversy. (shrink)

Mathematical models are a well established tool in most natural sciences. Although models have been neglected by the philosophy of science for a long time, their epistemological status as a link between theory and reality is now fairly well understood. However, regarding the epistemological status of mathematical models in the social sciences, there still exists a considerable unclarity. In my paper I argue that this results from specific challenges that mathematical models and especially computer simulations (...) face in the social sciences. The most important difference between the social sciences and the natural sciences with respect to modeling is that in the social sciences powerful and well confirmed background theories (like Newtonian mechanics, quantum mechanics or the theory of relativity in physics) do not exist in the social sciences. Therefore, an epistemology of models that is formed on the role model of physics may not be appropriate for the social sciences. I discuss the challenges that modeling faces in the social sciences and point out their epistemological consequences. The most important consequences are that greater emphasis must be placed on empirical validation than on theoretical validation and that the relevance of purely theoretical simulations is strongly limited. (shrink)

Science and Technology Studies has attained a strong international profile in recent decades. Science Studies incorporates work in the History and Philosophy of Science, but emphasizes the social, cultural, and political implications of developments in the natural sciences, mathematics, engineering, and medicine. The Sociology of Science remains a vital part of Science Studies, but many other key contributors in the field identify more strongly with core disciplines such as Anthropology, Political Science, and Communication (...) Studies. Edited by a leading scholar in the field, this new four-volume collection from Routledge brings together classic work and the very best contemporary and cutting-edge scholarship. It provides researchersâe"and advanced studentsâe"with easy access to the key items of scholarly literature, material that is otherwise inaccessible or scattered throughout a variety of specialist journals and books. In particular, the collection enables users to gain a deep understanding of the current controversies surrounding science. The materials gathered exemplify important arguments, empirical studies, perspectives, and controversies (such as âe~the science warsâe(tm) of the 1990s). The collection also includes a full index, together with a comprehensive introduction, newly written by the editor, which places the collected material in its historical and intellectual context. Science and Technology Studies is an essential work of reference and will be welcomed as a vital one-stop research and pedagogic resource. (shrink)

Physics has for a long time been regarded as the most mature of all sciences due to strict mathematically formulated laws of physics and success of theories in applications, for which it has been taken as the example of scientificity which other sciences should strive towards. Just what aspect of physics it is that is regarded as the cause of its success and hence the yardstick of scientificity – this question has given rise to differing opinions. In his book Making (...) Social Sciences More Scientific. The Need For Predictive Models Rein Taagepera criticises the opinion that physics is a rigorous science ‘merely’ due to the use of mathematical operations and numerical accuracy of results. He shows that the strictness of physics consists instead in its method that allows to set numbers and mathematical formalism into correspondence with real phenomena in a way that enables application (first of all prediction), and to unite physical theories into uniform, integral systems. At the same time he teaches how it would be possible to reach the same in social sciences. In the first part of my review I will give an overview of the book’s chapters, describing in more detail Taagepera’s general understanding of science and scientific method. In the second part of the review I analyse the positions presented in the book from the point of view of philosophy of science (particularly that of constructive realism), providing examples from social sciences. With my critique I show that the society cannot be handled with strict theories similar to those of physics, and that in order to raise the applicational strength of social sciences, other means often suit better than rendering them similar to physics by developing mathematical formalism. (shrink)

Academia’s mathematical metaphysics are briefly explored en route to an elaboration of the qualitatively rigorous requirements underpinning the calibration and unambiguous interpretation of quantitative instrumentation in any science. Of particular interest are Gadamer’s emphases on number as the paradigm of the noetic, on the role of play in interpretation, and on Hegel’s sense of method as the activity of the thing itself that thought experiences. These point toward and overlap with (1) Latour’s study of the metrological social (...) networks through which technological phenomena are brought into language as modes of being that can be understood, and (2) the way that Rasch’s models for measurement comprise a potential beginning for metaphysically astute, qualitatively and quantitatively integrated, mathematical methods in the social sciences. The paper closes with observations on the general problem that is philosophy, the need to remain open to multiplicities of meaning even as clear understandings are sought and obtained. (shrink)

When von Neumann's and Morgenstern's Theory of Games and Economic Behavior appeared in 1944, one thought that a complete theory of strategic social behavior had appeared out of nowhere. However, game theory has, to this very day, remained a fast-growing assemblage of models which have gradually been united in a new social theory - a theory that is far from being completed even after recent advances in game theory, as evidenced by the work of the three Nobel Prize (...) winners, John F. Nash, John C. Harsanyi, and Reinhard Selten. Two of them, Harsanyi and Selten, have contributed important articles to the present volume. This book leaves no doubt that the game-theoretical models are on the right track to becoming a respectable new theory, just like the great theories of the twentieth century originated from formerly separate models which merged in the course of decades. For social scientists, the age of great discover ies is not over. The recent advances of today's game theory surpass by far the results of traditional game theory. For example, modem game theory has a new empirical and social foundation, namely, societal experiences; this has changed its methods, its "rationality. " Morgenstern (I worked together with him for four years) dreamed of an encompassing theory of social behavior. With the inclusion of the concept of evolution in mathematical form, this dream will become true. Perhaps the new foundation will even lead to a new name, "conflict theory" instead of "game theory. (shrink)

It is the thesis of this paper that the term scientific law can and should mean in the social sciences exactly what it means in any of the other sciences. There seems to be considerable agreement among scientists as well as others that a scientific law is a generalized and verifiable statement, within measurable degrees of accuracy, of how certain events occur under stated conditions. If I were to attempt a more specific statement I would say that a law (...) is a group of verbal or mathematical symbols designating an unlimited number of defined events in terms of a limited number of reactions so that the performance of specified operations always yields predictable results within measurable limits. (shrink)