京津冀高等教育协同创新政策工具量化评价

在京津冀不断推进高等教育协同创新但教育资源存在极大不均的现状下，为探寻如何通过政策设计优化京津冀协同水平，本文使用文本分析、语义网络等模型对2015~2019年74项京津冀高等教育协同创新政策进行政策工具使用现状分析，挖掘现有政策的不足之处；进一步，运用PMC指数模型，本文量化评价了4项关键政策，为优化政策提供路径方案。结果表明：首先，各项政策需对需求型政策工具的使用严重不足；其次，4项代表政策中，除国政PMC得分与Intensity得分达到优秀级别，其余地方政策均仅达到可接受级别，对于协同机制重视程度不足；最后，京津冀各地方政府应基于量化评价结果，着重加强京津冀资源共享机制，从政策性质、激励措施等维度依次优化，以更科学详实的政策文本推动京津冀高等教育协同创新。

Quantitative Evaluation of the Collaborative Innovation Policy in Higher Education of Beijing-Tianjin-Hebei

Under the current situation that Beijing, Tianjin, and Hebei continue to promote the collaborative innovation of higher education, there still exists a significant imbalance in educational resources. To explore how to optimize the collaborative level of Beijing-Tianjin-Hebei through policy design, we first use text analysis and semantic network to analyze 74 Beijing-Tianjin-Hebei higher education collaborative innovation policies from 2015 to 2019, and excavate the shortcomings of existing policies. Furthermore, based on the PMC index model, this paper quantitatively evaluates four vital representative policies to provide path schemes for policies optimization. The results show that: First, the application of demand-based policy tools in various policies is seriously insufficient; Second, among the four representative policies, except for the PMC and intensity scores of the national government achieving the excellent level, the other local policies only reach the acceptable level, indicating that insufficient attention is paid to the coordination mechanism; Finally, based on the quantitative evaluation results, local governments should focus on strengthening the resource sharing mechanism of Beijing-Tianjin-Hebei, optimize the policy type and incentive measures, and then promote the collaborative innovation of higher education in Beijing, Tianjin, and Hebei with more scientific and detailed policy texts.