Bioproduct Approval Regulation : An Analysis of Front-line Governance Complexity
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The behaviors and seemingly disconnected exchanges between actors operating within subcomponents of hierarchical decision-making systems can contribute to unanticipated broader-system effects. The concept of complexity is a useful way of better understanding the influential nature of these connections on decision-making outcomes. This article presents the findings on subsystem complexity in bioeconomy governance from research undertaken by members of the VALGEN Regulation and Governance team. It demonstrates how applying Social Networking Analysis (SNA) and kurtosis analysis to regulatory frameworks can be used to uncover complexity within multilevel governance. SNA reveals how informal interactions in the decision-making process can impact the regulatory process. Kurtosis analysis shows how inputs into regulatory frameworks are not evenly reflected in the outputs. The article discusses the results of these methodologies applied to approvals in Canada of plants with novel traits and argues that appropriate qualitative and quantitative data sources are important to understanding complexity within the governance structures of the bioeconomy.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.