The Experts below are selected from a list of 195 Experts worldwide ranked by ideXlab platform
Manuela Fernández Pinto - One of the best experts on this subject based on the ideXlab platform.
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modeling the social Organization of Science chasing complexity through simulations
European journal for philosophy of science, 2017Co-Authors: Carlo Martini, Manuela Fernández PintoAbstract:At least since Kuhn’s Structure, philosophers have studied the influence of social factors in Science’s pursuit of truth and knowledge. More recently, formal models and computer simulations have allowed philosophers of Science and social epistemologists to dig deeper into the detailed dynamics of scientific research and experimentation, and to develop very seemingly realistic models of the social Organization of Science. These models purport to be predictive of the optimal allocations of factors, such as diversity of methods used in Science, size of groups, and communication channels among researchers. In this paper we argue that the current research faces an empirical challenge. The challenge is to connect simulation models with data. We present possible scenarios about how the challenge may unfold.
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Tensions in agnotology: Normativity in the studies of commercially driven ignorance.
Social studies of science, 2015Co-Authors: Manuela Fernández PintoAbstract:As scientific research moves increasingly to the private sector, the social Organization of Science undergoes important transformations. Focusing on the production of ignorance, agnotology has been a fruitful approach to understanding the social and epistemic consequences of the recent commercialization of scientific research. Despite their important contributions, scholars working on agnotology seem to hold implicit normative commitments that are in tension with their descriptive accounts of ignorance-constructive practices. The main aim of this article is to uncover these commitments and to expose the emerging tensions. Thus, this article begins an exploration into normative aspects of the studies of ignorance. In particular, it shows that agnotology still needs the support of a well-articulated normative approach capable of identifying and evaluating the epistemic and social concerns raised by the private funding and performance of Science.
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Learning from ignorance: agnotology's challenge to philosophy of Science
Erasmus Journal for Philosophy and Economics, 2014Co-Authors: Manuela Fernández PintoAbstract:The recent commercialization and privatization of scientific research has reconfigured the Organization of Science worldwide, fostering new scientific practices and new political tools to manage scientific research. Focusing on the mechanisms of ignorance production, the recent literature in agnotology has been a fruitful approach for understanding the social and epistemological consequences that emerge in commercialized Science today. Strictly speaking, agnotology is the study of ignorance broadly conceived. Agnotology's innovative contribution to the studies of Science stems from its treatment of ignorance as a social construction, one that differs from the traditional conception of ignorance as a natural vacuum (Proctor 2008). Agnotology has uncovered different ways in which the commercialization of scientific research has encouraged the production of ignorance, thus challenging the epistemic adequacy of the current social Organization of Science. Consequently, agnotology has made evident the need for a well-articulated normative approach capable of identifying and evaluating the epistemic concerns raised by the private funding and performance of Science. Although philosophers of Science have dealt with some of the social aspects of scientific knowledge production, they have yet to articulate an appropriate social epistemology that addresses these pressing issues. In my dissertation I take up this task.The aim of my dissertation is twofold. First, I examine the epistemic and social problems emerging from cases of ignorance production to argue that agnotology poses a serious challenge for philosophy of Science. Second, I draw a path for philosophers of Science to address this challenge.The dissertation is divided in five chapters. The introductory chapter describes some of the main challenges that philosophy of Science has encountered in the past half century, i.e., the historical challenge posed by scholars such as Thomas Kuhn and Paul Feyerabend, and the constructivist challenge posed by the Strong Program in the sociology of scientific knowledge and the social studies of Science more generally, and then introduces agnotology as a new terrain, posing important questions for the philosopher of Science. In the second chapter, I present the works of Philip Kitcher (2011) and Helen Longino (2002) as representative of a philosophy of Science concerned with the social dimensions of scientific knowledge. I also give a historical account of the major changes that the Organization of Science has undergone in the past three decades with the move towards the commercialization and privatization of research. I then argue that Kitcher's and Longino's accounts of scientific knowledge have important limitations when evaluating the process of knowledge production in the commercialized framework in which scientific research develops today.The third chapter examines the recent literature on agnotology, focusing on four cases: the tobacco industry's support of cancer research (Proctor 2011), the ongoing debate over global warming (Oreskes and Conway 2010), the pharmaceutical industry's design of clinical trials (Michaels 2008; Nik-Khah 2014), and economists' assessment of the financial crisis of 2008 (Mirowski 2013). I argue that scholars working on agnotology seem to hold implicit normative commitments that are in tension with their descriptive accounts of ignorance-constructive practices. Accordingly, and despite uncovering the limitations of the current Organization of Science, agnotology does not provide an appropriate normative account of the current production of scientific knowledge either. Further exploration into the normative aspects of agnotology is still needed.In order to start addressing the challenge of agnotology, I build upon the contributions of philosophers of Science to the Science and values debate. Thus, the fourth chapter presents the Science and values framework, describing the lines of argument that philosophers of Science have used to understand the role of social and political values in scientific inquiry (e. …
Carlo Martini - One of the best experts on this subject based on the ideXlab platform.
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Modeling the social Organization of Science
European Journal for Philosophy of Science, 2017Co-Authors: Carlo Martini, Manuela Fernández PintoAbstract:At least since Kuhn’s Structure , philosophers have studied the influence of social factors in Science’s pursuit of truth and knowledge. More recently, formal models and computer simulations have allowed philosophers of Science and social epistemologists to dig deeper into the detailed dynamics of scientific research and experimentation, and to develop very seemingly realistic models of the social Organization of Science. These models purport to be predictive of the optimal allocations of factors, such as diversity of methods used in Science, size of groups, and communication channels among researchers. In this paper we argue that the current research faces an empirical challenge. The challenge is to connect simulation models with data. We present possible scenarios about how the challenge may unfold.
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modeling the social Organization of Science chasing complexity through simulations
European journal for philosophy of science, 2017Co-Authors: Carlo Martini, Manuela Fernández PintoAbstract:At least since Kuhn’s Structure, philosophers have studied the influence of social factors in Science’s pursuit of truth and knowledge. More recently, formal models and computer simulations have allowed philosophers of Science and social epistemologists to dig deeper into the detailed dynamics of scientific research and experimentation, and to develop very seemingly realistic models of the social Organization of Science. These models purport to be predictive of the optimal allocations of factors, such as diversity of methods used in Science, size of groups, and communication channels among researchers. In this paper we argue that the current research faces an empirical challenge. The challenge is to connect simulation models with data. We present possible scenarios about how the challenge may unfold.
Roger A Pielke - One of the best experts on this subject based on the ideXlab platform.
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the neglected heart of Science policy reconciling supply of and demand for Science
Environmental Science & Policy, 2007Co-Authors: Daniel Sarewitz, Roger A PielkeAbstract:Abstract The funding of scientific research is almost always justified in terms of the potential for achieving beneficial societal outcomes. In pursuing a particular societal outcome, how can we know if one research portfolio is better than another? In this paper we conceptualize: (1) Science in terms of a “supply” of knowledge and information, (2) societal outcomes in terms of a “demand” function that seeks to apply knowledge and information to achieve specific societal goals, and (3) Science policy decision-making as a process aimed at “reconciling” the dynamic relationship between “supply” and “demand.” The core of our argument is that “better” Science portfolios (that is, portfolios viewed as more likely to advance desired societal outcomes, however defined) would be achieved if Science policy decisions reflected knowledge about the supply of Science, the demand for Science, and the relationship between the two. We provide a general method for pursuing such knowledge, using the specific example of climate change Science to illustrate how research on Science policy could be organized to support improved decisions about the Organization of Science itself.
Joseph A Kotarba - One of the best experts on this subject based on the ideXlab platform.
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symbolic interaction and applied social research a focus on translational Science
Symbolic Interaction, 2014Co-Authors: Joseph A KotarbaAbstract:In symbolic interaction, a traditional yet unfortunate and unnecessary distinction has been made between basic and applied research. The argument has been made that basic research is intended to generate new knowledge, whereas applied research is intended to apply knowledge to the solution of practical (social and Organizational) problems. I will argue that the distinction between basic and applied research in symbolic interaction is outdated and dysfunctional. The masters of symbolic interactionist thought have left us a proud legacy of shaping their scholarly thinking and inquiry in response to and in light of practical issues of the day (e.g., Park and Blumer). Current interactionist work continues this tradition in topical areas such as social justice studies. Applied research, especially in term of evaluation and needs assessment studies, can be designed to serve both basic and applied goals. Symbolic interaction provides three great resources to do this. The first is its orientation to dynamic sensitizing concepts that direct research and ask questions instead of supplying a priori and often impractical answers. The second is its orientation to qualitative methods, and appreciation for the logic of grounded theory. The third is interactionism's overall holistic approach to interfacing with the everyday life world. The primary illustrative case here is the qualitative component of the evaluation of an National Institutes of Health-funded, translational medical research program. The qualitative component has provided interactionist-inspired insights into translational research, such as examining cultural change in medical research in terms of changes in the form and content of formal and informal discourse among scientists; delineating the impact of significant symbols such as “my lab” on the social Organization of Science; and appreciating the essence of the self-concept “scientist” on the increasingly bureaucratic and administrative identities of medical researchers. This component has also contributed to the basic social scientific literature on complex Organizations and the self.
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symbolic interaction and applied social research a focus on translational Science research1
Symbolic Interaction, 2014Co-Authors: Joseph A KotarbaAbstract:In symbolic interaction, a traditional yet unfortunate and unnecessary distinction has been made between basic and applied research. The argument has been made that basic research is intended to generate new knowledge, whereas applied research is intended to apply knowledge to the solution of practical (social and Organizational) problems. I will argue that the distinction between basic and applied research in symbolic interaction is outdated and dysfunctional. The masters of symbolic interactionist thought have left us a proud legacy of shaping their scholarly thinking and inquiry in response to and in light of practical issues of the day (e.g., Znaniecki, and Blumer). Current interactionist work continues this tradition in topical areas such as social justice studies. Applied research, especially in term of evaluation and needs assessment studies, can be designed to serve both basic and applied goals. Symbolic interaction provides three great resources to do this. The first is its orientation to dynamic sensitizing concepts that direct research and ask questions instead of supplying a priori and often impractical answers. The second is its orientation to qualitative methods, and appreciation for the logic of grounded theory. The third is interactionism’s overall holistic approach to interfacing with the everyday life world. The primary illustrative case here is the qualitative component of the evaluation of an NIH-funded, translational medical research program. The qualitative component has provided interactionist-inspired insights into translational research, such as examining cultural change in medical research in terms of changes in the form and content of formal and informal discourse among scientists; delineating the impact of significant symbols such as "my lab" on the social Organization of Science; and appreciating the essence of the self-concept "scientist" on the increasingly bureaucratic and administrative identities of medical researchers. This component has also contributed to the basic social scientific literature on complex Organizations and the self.
Manuela Fernández Pinto - One of the best experts on this subject based on the ideXlab platform.
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Modeling the social Organization of Science
European Journal for Philosophy of Science, 2017Co-Authors: Carlo Martini, Manuela Fernández PintoAbstract:At least since Kuhn’s Structure , philosophers have studied the influence of social factors in Science’s pursuit of truth and knowledge. More recently, formal models and computer simulations have allowed philosophers of Science and social epistemologists to dig deeper into the detailed dynamics of scientific research and experimentation, and to develop very seemingly realistic models of the social Organization of Science. These models purport to be predictive of the optimal allocations of factors, such as diversity of methods used in Science, size of groups, and communication channels among researchers. In this paper we argue that the current research faces an empirical challenge. The challenge is to connect simulation models with data. We present possible scenarios about how the challenge may unfold.