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Session Title: Evaluating Government Research and Technology Policies: Traditional and Emerging Methods
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Multipaper Session 569 to be held in Texas D on Friday, Nov 12, 10:55 AM to 11:40 AM
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Sponsored by the Research, Technology, and Development Evaluation TIG
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| Chair(s): |
| Cheryl Oros,
Oros Consulting LLC, cheryl.oros@gmail.com
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Quality Evaluations of Government Policies in Research Science and Technology Sector
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| Presenter(s):
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| Yelena Thomas, Ministry of Research Science and Technology, yelena.thomas@morst.govt.nz
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| Abstract:
Evaluation quality is a topic of interest for many. There are a lot of approaches and arguments in favour of one or another method. This presentation describes that the mixed method approach and explains why this is the most successful approach for evaluating government policies in New Zealand. The mixed method approach uncovers the multifaceted interventions of any public policy and show the impacts on different user groups. It also provides cost effective and comprehensive impact evaluations. There are, of course, challenges with this approach. This presentation discusses the challenges the author has encountered when implementing the approach and the risk mitigation strategies employed. The presentation also describes how the New Zealand context compares to other countries and discusses whether or not the same approach would work elsewhere.
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Applications of Agent-based Simulations in Evaluating Science and Technology Policies
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| Presenter(s):
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| Branco Ponomariov, University of Texas, San Antonio, branco.ponomariov@utsa.edu
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| Abstract:
This paper reviews, and applies to the example of cross-sectoral research in nanotechnology, the use of agent-based simulation methods to the evaluation S&T Policy questions, such as the effect of different organizational forms and constraints on collaboration patterns. The paper uses findings from the literature on nano-technology to program a simulation of the behaviors of scientists and institutions entering the field over time. The results from the variety of simulation scenarios will be juxtaposed to the empirically observed network structures. The emphasis of the paper is on showing how the use of simulation techniques is a powerful complement of the conventional approaches of estimating the effects of key variables and policy interventions on behavior. Using such findings to program “decision rules” under which “agents” operate in a collaboration network allows making robust predictions about the likely outcomes of policies aiming at influencing the pattern of S&T collaboration.
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