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Atlanta Conference on Science and Innovation Policy

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    GWAS Data and Federally-Funded Public Access Repositories: Considering the Ethical, Policy, and Social Implications from Multiple View Points
    (Georgia Institute of Technology, 2009-10-02) Koenig, Barbara ; McCormick, Jennifer ; Wu, Joel
    The collection and distribution of individual genotypic and phenotypic data has increased enormously in the past 10 years and shows no signs of slowing down. The rapid growth of bioinformatics technologies and genome wide association studies (GWAS) continues to increase the quantity and availability GWAS data. As the size, complexity, and number of GWAS increase, so do the risks to maintaining individual privacy, confidentiality, and autonomy and the public's trust in genomic research. The utility of collecting and using genotype and phenotype to promote advances in our understanding of human health and well-being must be kept in line with individual rights. And, policy governing the depositing of GWAS data into publicly accessible databases as well as obtaining that data by downstream researchers must balance the scientific benefit against the potential social and ethical risks. GWAS are an important tool in ascertaining genetic contribution to health risks, as well as in development of new therapeutic targets. The significance of GWAS data is subject to not only the size of the study population, but also the accuracy of phenotypic measures and density of the markers used in genotyping; as such, meaningful GWAS data are expensive and difficult to obtain. The scientific community has recognized there is high value in sharing the genotype and phenotype data obtained through GWAS. In response, the NIH established the Database of Genotypes and Phenotypes (dbGaP). dbGaP is a centralized database of GWAS data collected from large scale NIH-funded studies. The data collected and deposited into dbGaP can be distributed either publicly, or through a restricted process, depending on the nature of the data being shared and who is making the request for data. All NIH supported investigators are required to deposit GWAS data in dbGaP in order to maintain their NIH funding. Sharing of GWAS data involves distribution of sensitive personal information including at minimum, genotype and phenotype data, potentially including additional information such as individual medical records. The sharing of GWAS data exposes not only research subjects to additional risk of identification, harm, and loss of autonomy on how that data might be used, but also exposes researchers and institutions to increased risks for liability, loss of public trust, and loss of funding. These increased risks raise important ethical, legal, policy, and social issues that must be addressed by institutional and federal data sharing policy. While dbGaP is currently the only such data repository, it is very likely that other similarly federal research agency operated databases will come online in the near future. There are various stakeholders in this endeavor to increase ease of accessibility to GWAS data: researchers - both who deposit the data and who obtain the data from the repository, policy-makers who want to see the utility of the science they fund maximized, patient advocates who focus on pushing science along, government and individual institution research administrators who must oversee the repository and or access to the data, and research participants who contribute samples to the GWAS. This paper will discuss the experiences of the authors in creating an institutional policy as well as their participation in deliberations about cross-institutional data sharing policies. Particular emphasis will be placed on how to balance the utility of the data for scientific progress while still keeping in sight the rights, privacy, and confidentiality of the individual. In addition, the authors will present preliminary empirical data from interviews conducted with various stakeholders. The paper will also address the following questions regarding genotype and phenotype data sharing policy through a federal research agency publicly accessible repository in light of emerging legal and policy developments from late 2008 and 2009, 1. how to balance the scientific value of data sharing against the privacy risks, who should have access to different types of GWAS data; 2. whether GWAS data can be de-identified, and what de-identified really means. As noted above, dbGaP is one of the first such publicly accessible genotype and phenotype databases, and determination of relevant issues in creating policy for these databases is of critical importance. As we move forward in this era for large-scale GWAS, striving for advances in biomedical research and the eventual commonplace of individualized medicine, the combined perspectives of all stakeholders should be synthesized into a guiding framework for how research institutions and the federal government can create informed, relevant policy to protect not only the privacy, confidentiality, and personal interests of individual research subjects, but also to protect and promote the progress of individualized research medicine as a whole.
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    The Price of Silence: Scientists' Trade-offs Between Publishing and Pay
    (Georgia Institute of Technology, 2011-09-16) Roach, Michael ; Sauermann, Henry ; Georgia Institute of Technology. School of Public Policy ; Georgia Institute of Technology. College of Management ; University of North Carolina at Chapel Hill
    A growing body of research draws on the notion that scientists face trade-offs between publishing research results and larger financial returns associated with limited disclosure. Yet little is known how scientists resolve such trade-offs. Using survey data from 1,400 junior life scientists, we find considerable heterogeneity in the price scientists assign to publishing when they consider research positions in industry that allow versus restrict publishing, including scientists who are willing to give up publishing for free . Analyzing sources of heterogeneity, we find that the required wage premium increases with a scientist s preference for publishing but decreases with the preference for money. Scientists who value publishing primarily as a currency in the labor market require a smaller wage premium, ceteris paribus, than scientists who value publishing as a mechanism to advance scientific knowledge, presumably reflecting different degrees of substitutability between publishing and pay. Finally, ability and the quality of training have a positive relationship with the required wage premium. We discuss implications for research on the economics of science, for managers seeking to attract and retain academically trained scientists, and for firms considering their participation in open science .
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    Scientists Engaged in Emerging Technology Research: The Nature of Scientific Networks and Collaborative Groups
    (Georgia Institute of Technology, 2009-10) Melkers, Julia ; Xiao, Fang ; Georgia Institute of Technology ; Georgia State University
    Emerging technologies are generally seen as those latest scientific innovations which "embody the latest in efficiency and productivity design that have most recently been commercialized" (Lung, Masanet et al. 2006), have a potential impact on industry structure (Day and Schoemaker 2000) and a significant influence on economy (Porter, Roessner et al. 2002). A key characteristic of emerging technologies is that they are new - therefore the notion of "emerging" is a time limited status that reflects the development and adjustment affiliated with the creation of something novel. Generally speaking, technologies are no longer considered to be emerging once they have been successfully commercialized for ten years (Lung, Masanet et al. 2006). In recent years, an increasing number of scientists are conducting research in areas of emerging technology, and becoming active in commercializing their scientific discoveries (Kleinman 1998; Stuart and Ding 2006). Meanwhile, research funding opportunities in areas of emerging technology have increased; for example, NSF funding on Nano has grown from $150 million in 2001 to $389 million in 2007 (NNI 2008). In this, the competitiveness of the grant environment has also increased. In many of these new technology areas, there is an increasing expectation for interdisciplinary collaboration (Oliver 2004; Heinze and Bauer 2007). This paper addresses the nature of scientists that have been successful in this competitive process in the area of emerging technologies and the collaborative network factors that predict their success. Data are drawn from a recent national survey of science and engineering faculty in 150 Research 1 universities in the United States in (n=1,764). First, we provide detailed descriptive statistics on characteristics of scientists engaged in funded emerging technology research. In particular, we address their interdisciplinary collaboration interactions and networks, as well as their interaction with industry. To address the factors that explain successful funding in the emerging technologies area, we develop and test an endogenous dependent variable model which estimates the determinants of scientists' success in obtaining funding to conduct emerging technology research. We expect that individuals who are more active to engage in boundary-spanning activities, who have more interdisciplinary collaborators, who have more industrial linkages are more successfully funded to conduct emerging technology research. Day, G. S. and P. J. H. Schoemaker (2000). A Different Game. Wharton on Managing Emerging Technologies. G. S. Day, P. J. H. Schoemaker and R. E. Gunther. New York, John Wiley and Sons, Inc. Heinze, T. and G. Bauer (2007). "Characterizing creative scientists in nano-S&T: Productivity, multidisciplinarity, and network brokerage in a longitudinal perspective." Scientometrics 70(3): 811-830. Kleinman, D. L. (1998). "Untangling Context: Understanding a University Laboratory in the Commercial World." Science, Technology, & Human Values 23(3): 285-314. NNI. (2008). "Funding." from http://www.nano.gov/html/about/funding.html. Oliver, A. L. (2004). "Biotechnology entrepreneurial scientists and their collaborations." Research Policy 33: 583-597. Porter, A. L., J. D. Roessner, et al. (2002). "Measuring national 'emerging technology' capabilities." Science and Public Policy 29(3). Stuart, T. and W. Ding (2006). "When Do Scientists Become Entrepreneurs? The Social Structural Antecedents of Commercial Activity in the Academic Life Sciences." American Journal of Sociology 112(1): 97-144.
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    A Window into the Field of Biotechnology Risk Analysis: A Bibliometric Approach
    (Georgia Institute of Technology, 2011-09-17) Kuzhabekova, Aliya ; Kuzma, Jennifer ; University of Minnesota. School of Pubic Affairs
    Risk assessment is growing in its importance and application, and it plays a special role in the permeation of emerging technology products into the marketplace. Despite its importance, we know very little about the portfolio of risk analysis research for emerging technologies. In this paper, we use bibliometric methods to better understand the portfolio of risk analysis research for agricultural biotechnology with the goal of identifying gaps that are important for decision making and risk management.
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    What are the Main Determinants Behind the Three Dimensions of Globalization of Technology? Insights From Developed and Developing Countries
    (Georgia Institute of Technology, 2011-09-16) Chaminade, Cristina ; De Fuentes, Claudia ; Lunds universitet. Centre for Innovation, Research and Competence in the Learning Economy
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    The Concept of 'Sociotechnology' and Funding Agencies Dedicated to Science and Technology for Society
    (Georgia Institute of Technology, 2009-10-03) Tahara, Keiichiro ; Yarime, Masaru ; Yoshizawa, Go ; University of Tokyo
    Note: This is part of the panel presentation "Knowledge Use and Exchange for Policy and Society in Japan: Concepts and Practices." Research Question Research Institute of Science and Technology for Society (RISTEX) in Japan has a unique funding agency dedicated to research projects on "sociotechnology". One question is what is meant by "sociotechnology" and what are similar concepts and practices comparable to this term. Another question concerns in what sense this organization is unique compared to other agencies in the world. For the research on the concept and similar terms of sociotechnology, a mind map software and a qualitative data analysis (QDA) software are employed to visually and constructively arrange text data collected from a vast range of documents including books, articles and manuscripts in English and Japanese. For the research on foreign agencies comparable to RISTEX, web research, document analysis and e-mail interviews are basic tools. Preliminary Results The umbrella term "sociotechnology" includes technology for, as, with, and by society. Technology for society refers to practical activities aiming to solve tangible but often intractable problems. It is more than applied technology. Technology as society was known as social control and is now developed under the name of social engineering. This somewhat Popperian concept (Popper 1936, 1945) covers social activities and structures as a technological system. Technology with society has often been used as a popular adjective "socio-technical" (Emery & Trist 1960), the concept of which now refers to a balanced way of seeing technology and society and particularly focuses on the often complicated interactions and networks of technological and social actors - actors include data, figures, objects, architects, as well as humans in a Latourian sense (Latour 1987). Technology by society may be the most understandable in its first appearance, but probably this concept includes more than usually imagined by the term like collaboration, multiplicity of perspectives etc. Lastly, technology for society is more straightforward - technology oriented to problem-solving in the policy process and the social practice. From a preliminary research we identified three key functions of sociotechnology. The first is oriented to problem-solving. The corresponding disciplines, frameworks and approaches include policy science, finalization of science, knowledge use and exchange, problem-oriented learning and utilization-focused evaluation. The second is extensiveness, comprising of comprehensiveness and interrelatedness. The related keywords are, for instance, STS, evolutionary economics, social engineering, management studies, socio-technical system, network theory, soft systems methodology, creative holism, transition management, problem structuring, and systematic review. The third is collaboration and trans-disciplinarity. These are similar in the sense that both appreciate the collection and diversity of perspectives, drawn from actors in the former and disciplines in the latter. Regional sociology, communication studies, social intelligence, empowerment, appreciative inquiry, participatory technology assessment, regional foresight, and upstream engagement can perform the function of this kind. In this way terms comparable to "sociotechnology" so far we enumerate are mode-2 science, constructive/real-time technology assessment, soft science and technology, participatory action research, and collaborative problem-solving. These will be organized and distributed in a schematic map with the help of the computer applications. Rarely can we find organizations dedicated to the promotion of science and technology for society. Some possible organizations include NESTA (National Endowment for Science, Technology and the Arts) in the UK, and STW (Dutch Technology Foundation) in the Netherlands.
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    Real Option Valuation of R&D Projects: Consideration of Portfolio Effects
    (Georgia Institute of Technology, 2011-09-15) Linquiti, Peter ; Vonortas, Nicholas ; Georgia Institute of Technology. School of Public Policy ; George Washington University. Center for International Science and Technology Policy
    This analysis focuses on portfolios of R&D projects, rather than individual R&D projects. It explores the effect of portfolio diversification on risk and identifies both theoretical and practical considerations relevant to the portfolio formation process. A Monte Carlo simulation of a hypothetical R&D portfolio is used to illustrate implications for policymakers.
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    Knowledge Use and Exchange for the Making of National Science and Innovation Strategies
    (Georgia Institute of Technology, 2009-10-03) Tahara, Keiichiro ; Yarime, Masaru ; Yoshizawa, Go ; University of Tokyo
    Note: This is part of the panel presentation "Knowledge Use and Exchange for Policy and Society in Japan: Concepts and Practices." Research questions addressed in this presentation are what kind of information and knowledge was used for the making of the Science and Technology Basic Plan (STBP) and in particular, to what extent academic policy analysis was useful in the making process. A further question is what kind of field in which practitioners, researchers and decision-makers communicate and exchange their knowledges would be effective and legitimate in the making of national science and innovation strategies. Following interviews with working and former government administrators heavily engaged in the making of the Basic Plans, qualitative data analysis is applied to organize interview and document text data and form a logical structure implicitly embedded in the contents of Basic Plans. We also conducted interviews with researchers and practitioners concerning evidence-based policy making or the use and exchange of knowledge on national science and innovation strategies in the Netherlands, France, England and Scotland. Preliminary Results We firstly defined the term "policy analysis" discriminating it from other information and knowledge. For this, a two-dimensional taxonomy of information and knowledge used for policymaking roughly illustrated by Parsons (1995) was developed with more fine-tuned and detailed definitions: 1) Internal vs. External: Whether or not information and knowledge is generated mainly by decision-makers and their affiliated actors; 2)Formal vs. Informal: Whether or not the procedure of information and knowledge generation is authenticated both institutionally and methodologically. Then, policy analysis is defined as an activity with accountability and policy-orientation, or information and knowledge generated thereby. Accountability is the extent to which information and knowledge generation activity is publicly accounted and the responsibility for the activity and account is clear. It comprises explicitness and definiteness of the generation activity and responsibility (voluntary openness), logical consistency and capability of being referred (endogenous logic), and multiplicity and rationality of data and methods (methodological validity). Policy-orientation (exogenous logic) is the extent to which the logic is explicitly consistent with the endogenous logic and is developed directed to the actual policy process. The analytical result shows that internal and formal policy analysis (mainly by NISTEP) and internal and informal policy information has been increasingly used, but external and informal policy analysis has remained unused. We also find that issues on the decision-making system lie in deliberation institutions/processes, institutional void of the discussion of meta-analysis on how policy studies should be incorporated into the decision-making, flawed system of commissioned research, interactions between policymakers and researchers, short job rotation system in bureaucracy, few opportunities for policymakers to increase capacities (to identify what kind of research is necessary) as practitioners, and biased perspectives toward promotion. With regard to the knowledge generation system, first of all, the policy research community is in its infancy. Immaturity of (internal and external) think-tanks and flawed university training system for policy researchers are also issues to be seriously considered when researchers are less aware of policymakers' needs. Generated knowledge itself may not be able to guarantee its quality because of flawed data management system for policy analysis, few studies on national issues but more on bureaucratic sectoral interests, and few long-term studies except Delphi. Furthermore, the focus on review studies (performance evaluation) does not lead to the institutional and procedural reform of the planning. What we are trying to do is actively changing this situation by setting a number of interaction fields and communication spaces in which these actors come to meet. Our reflexive attempt is the workshop jointly organized by academic societies for science and innovation and for science and technology studies (STS), and supported by a science communication network involving working scientists and engineers. The workshop is to be held in March 2009 and the result will be presented in this conference.
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    S&T Policy Scorecard: The Effects of S&T Policy Mechanisms on the Economy
    (Georgia Institute of Technology, 2011-09-15) Hayslett, Marlit ; Kim, Moon ; Petrakieva, Elena ; Georgia Tech Research Institute. Office of Policy Analysis and Research
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    What Determines the Foreign Direct Investment in R&D in Developed vs. Developing Host Countries: A Country-Panel Analysis
    (Georgia Institute of Technology, 2011-09-17) Lee, Dong Joon ; Lee, Keun ; Park, Jun-ki ; CJ Corporation ; Seoul National University. Department of Economics
    In this paper, we analyze the determinants of the increasing foreign direct investments on research and development (R&D) as multinationals expand their business functions abroad. We use panel data analysis based on the country-specific variables suggested by the literature. The panel data taken from developed and developing countries are analyzed separately to examine the significant differences in levels of economic development and identify representative variables between the groups. Three different specifications widely used for panel analysis were employed: pooled OLS, fixed effect model, and random effect model. The result reveals that the host countries' systematic R&D activity, the level of existing foreign direct investment, and the concentration of workforce in R&D have positive impacts on the flow of foreign direct investment on R&D. More interesting results also show that while local private R&D is positively related to the degree of foreign R&D in the host developed countries, private R&D in the host developing countries is negatively related to foreign R&D, and public R&D is positively related to foreign R&D. This implies that in developing countries, foreign firms investing in R&D are concerned about the effects of competitive leakage with local companies. This also implies that it is effective for the government in developing countries to support local public R&D because this will induce foreign investment in R&D.