Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands.
Int J Environ Res Public Health. 2018 Feb 3;15(2):260. doi: 10.3390/ijerph15020260.
Cumulative burden assessment (CuBA) has the potential to inform planning and decision-making on health disparities related to multiple environmental burdens. However, scholars have raised concerns about the social complexity to be dealt with while conducting CuBA, suggesting that it should be addressed in an adaptive, participatory and transdisciplinary (APT) approach. APT calls for deliberation among stakeholders by engaging them in a process of social learning and knowledge co-production. We propose an interactive stakeholder-based approach that facilitates a science-based stakeholder dialogue as an interface for combining different knowledge domains and engendering social learning in CuBA processes. Our approach allows participants to interact with each other using a flexible and auditable CuBA model implemented within a shared workspace. In two workshops we explored the usefulness and practicality of the approach. Results show that stakeholders were enabled to deliberate on cumulative burdens collaboratively, to learn about the technical uncertainties and social challenges associated with CuBA, and to co-produce knowledge in a realm of both technical and societal challenges. The paper identifies potential benefits relevant for responding to social complexity in the CuBA and further recommends exploration of how our approach can enable or constraint social learning and knowledge co-production in CuBA processes under various institutional, social and political contexts.
累积负担评估 (CuBA) 有可能为与多种环境负担相关的健康差异的规划和决策提供信息。然而，学者们对在进行 CuBA 时需要应对的社会复杂性提出了担忧，认为应该采用适应性、参与性和跨学科 (APT) 的方法来解决。APT 呼吁利益相关者之间进行审议，让他们参与社会学习和知识共同生产的过程。我们提出了一种基于利益相关者的互动方法，该方法通过促进基于科学的利益相关者对话作为将不同知识领域结合起来并在 CuBA 过程中产生社会学习的接口。我们的方法允许参与者使用在共享工作空间中实现的灵活且可审核的 CuBA 模型相互交互。在两个研讨会上，我们探讨了该方法的有用性和实用性。结果表明，利益相关者能够共同协商累积负担，了解与 CuBA 相关的技术不确定性和社会挑战，并在技术和社会挑战领域共同生产知识。本文确定了与应对 CuBA 中的社会复杂性相关的潜在益处，并进一步建议探讨我们的方法如何在各种制度、社会和政治背景下，为 CuBA 过程中的社会学习和知识共同生产提供支持或限制。
