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A Bias Radar for Responsible Policy-MakingTowards Responsible Scientific Advice: Painting the Complete Picture

A Bias Radar for Responsible Policy-Making: Towards Responsible Scientific Advice: Painting the... [This chapter summarizes the scientific advisory process by presenting a model that combines all of the considerations and tools previously described. The model starts with a holistic approach to the scientific advisory process by zooming out through a systems analysis to get a broad picture of a policy problem within the entire science-policy ecosystem. It combines system analysis with bias checks to raise awareness of possible biases throughout the ecosystem, multi-disciplinary and multi-perspective STEEPED explorations, foresight thinking involving multiple stakeholders, cross-policy analysis and the quality control of evidence. The model aims to ensure a proper balance among the scientific evidence and the other inputs that bear on policy decisions. Lastly, the chapter includes reflections on the issue of trusting science and scientific advisers.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Bias Radar for Responsible Policy-MakingTowards Responsible Scientific Advice: Painting the Complete Picture

Part of the St Antony's Series Book Series
Van Woensel, Lieve
Springer Journals — Dec 27, 2019
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28 pages

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Publisher
Springer International Publishing
Copyright
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020
ISBN
978-3-030-32125-3
Pages
85 –113
DOI
10.1007/978-3-030-32126-0_5
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter summarizes the scientific advisory process by presenting a model that combines all of the considerations and tools previously described. The model starts with a holistic approach to the scientific advisory process by zooming out through a systems analysis to get a broad picture of a policy problem within the entire science-policy ecosystem. It combines system analysis with bias checks to raise awareness of possible biases throughout the ecosystem, multi-disciplinary and multi-perspective STEEPED explorations, foresight thinking involving multiple stakeholders, cross-policy analysis and the quality control of evidence. The model aims to ensure a proper balance among the scientific evidence and the other inputs that bear on policy decisions. Lastly, the chapter includes reflections on the issue of trusting science and scientific advisers.]

Published: Dec 27, 2019

Keywords: Responsible Scientific Advice (RSA); Scientific advice; Policy advice; Science-policy ecosystem; Policy; Scientific foresight

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