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Collaborative knowledge-driven governance: Types and mechanisms of collaboration between science, social science, and local knowledge

机译：知识驱动的协作式治理：科学，社会科学和本地知识之间的协作类型和机制

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Knowledge plays an important role in modern public governance characterized by complexity, but collaboration between different types of knowledge in public governance has not been systematically studied. Increasingly, literature has stressed the importance of the application of science, social science, and local knowledge in public governance, whereas it has paid little attention to the types and mechanisms of collaboration between these three fields. The aims of this study were to explore the influence of collaboration between the three types of knowledge on governance performance, the major types of collaboration, and the major institutional design principles for successful collaboration. Based on a combined field study including surveys, interviews, observations, and archive data as well as a meta-analysis study on desertification control in northern China, the largest developing country in the world, this study made the following three key findings: (1) Although natural science was the most widely applied area of knowledge and social science was least applied, the order of the correlation coefficients of the three types of knowledge with governance performance from the highest to the lowest was social science, local knowledge, and natural science. (2) Collaboration between these three types of knowledge influenced governance performance. The types of collaboration with low levels of all three types of knowledge always had low governance performance, and the types of collaboration with high levels of social science and local knowledge often had high performance. (3) Successful collaboration among different types of knowledge shared nine significant institutional design principles. These principles stressed the integration of three types of knowledge, the collaboration among knowledge possessors and other social actors, and reliable and sustainable external support (government, financial, and institutional). These findings shed new light on collaboration between science, social science, and local knowledge in public and environmental governance in China as well as in other countries around the world.
机译：知识在以复杂性为特征的现代公共治理中起着重要作用，但是公共治理中不同类型知识之间的协作尚未得到系统的研究。文献越来越强调在公共治理中应用科学，社会科学和地方知识的重要性，而很少关注这三个领域之间的合作类型和机制。本研究的目的是探讨三种知识类型之间的协作对治理绩效，协作的主要类型以及成功协作的主要机构设计原则的影响。基于一项包括调查，访谈，观察和存档数据的综合实地研究，以及关于世界最大的发展中国家中国北方沙漠化控制的荟萃分析研究，该研究得出以下三个主要发现：（1 ）尽管自然科学是知识应用最广泛的领域，而社会科学的应用最少，但三种类型的知识与治理绩效从最高到最低的相关系数的顺序是社会科学，本地知识和自然科学。 （2）这三种知识之间的协作影响了治理绩效。这三类知识水平低的协作类型始终具有较低的治理绩效，而社会科学和本地知识水平高的协作类型通常具有较高的绩效。 （3）不同类型知识之间的成功协作共享了九项重要的机构设计原则。这些原则强调了三类知识的整合，知识所有者与其他社会行为者之间的协作以及可靠和可持续的外部支持（政府，财政和机构）。这些发现为中国以及世界其他国家在公共和环境治理方面的科学，社会科学和地方知识之间的合作开辟了新的亮点。

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