Politics & Government

State Rep. Ryan Attends CSG Sound Science Policy Academy

Ryan, a Democrat, represents portions of Bozrah, Montville and Norwich.

From CT State Rep: State Rep. Kevin Ryan (D Bozrah/Montville/Norwich) was selected to attend the Council of State Governments' Policy Academy titled Using Science toInform State Policymaking, during the CSG December 2018 National Conference in Northern Kentucky- Greater Cincinnati.

The one-day policy academy aimed to equip state leaders with a foundation for understanding science-based evaluation and using science in the development of policy.

“We must take every opportunity to utilize all the tools at our disposal to enhance the decision making process, and science provide a solid foundation to work from,” said Rep. Ryan. “I am grateful for the opportunity to participate in this informative panel and learning more about the importance of a sound science perspective when making policy decisions.”

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State leaders increasingly face key policy decisions that rely on the understanding and use of scientific data. Such policy choices can often impact the health of the public and our stewardship of the environment. The absence of sound science in the policymaking process may hinder the deployment of effective policy or result in unintended consequences.

"Even in today's hyper connected world, science is not always easily accessible to policy decision makers, and scientists often do not understand decision makers' information needs," said Devashree Saha, CSG director of energy and environmental policy. "This policy academy aims to bridge the gap between sound science and decision making. While science alone cannot provide policy solutions to the many challenges that confront us today, scientifically informed perspectives must be taken into account for policy decisions to be made by the best available evidence."

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Using the development of consumer products as the broad case study, participants learned about the scientific basis from which product development decisions are derived.

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