推行科技特派员制度政策的量化评价分析——基于PMC指数模型

Quantitative Evaluation of Promoting the Sci-tech Experts System Policy

摘要:

推行科技特派员制度的政策是推进科技助农兴农、深入实施乡村振兴战略的重要抓手，为进一步丰富科技特派员政策体系建设，本文基于42份中国省域推行科技特派员制度的政策文本为研究对象，综合运用文本内容分析、PMC指数模型法等方法，构建包括9个一级变量、40个二级变量的PMC指数模型，从政策内容的全面性、政策对象的覆盖面、施策部门的协同性、对成果转化推广的引导作用等多维度评价推行科技特派员制度政策水平。研究发现：科技特派员制度政策样本的PMC指数均值为5.45，处于良好水平；其中3项政策效果为优秀，29项政策效果为良好，10项政策效果为可接受，说明深入推行科技特派员制度体系较为完善，具备较好的科学性、全面性与合理性，在政策目标、政策功能等方面表现较好，但在多部门协同性、成效跟踪、平台搭建、培训交流、健全社会化服务体系等方面仍有可优化空间，并据此在完善服务机制、加强成效跟踪、健全考核体系等方面提出政策优化建议。

关键词:科技特派员;PMC指数模型;政策文本量化分析

Abstract:

The policy on implementing the system of the science and technology commissioner is an important lever for promoting agriculture development through science and technology and deepening the implementation of the rural revitalization strategy. To further enrich the construction of the policy system on the science and technology commissioner, this study takes 42 policy texts on the implementation of the science and technology commissioner system in China's provinces as the research object, and uses text content analysis and PMC index model method to construct a PMC index model, which including 9 primary variables and 40 secondary variables, evaluates the policy level from multiple perspectives, including the comprehensiveness of policy content, the coverage of policy objects, the synergy of implementing departments, and the guiding role of achievement transformation and promotion. The study found that the average PMC index of the policy samples of the science and technology commissioner system was 5.45, which was at a good level; among them, 3 policies had excellent effects, 29 policies had good effects, and 10 policies had acceptable effects, indicating that the policy system on implementing the science and technology commissioner is relatively complete, with reasonable scientific nature, comprehensiveness, and rationality, and performs well in terms of policy objectives and policy functions. However, there is still room for optimization in multi departmental collaboration, performance tracking, platform building, training and exchange, and improving social service system. Based on this, policy optimization suggestions are put forward.

Key words:sci-tech experts; provincial policy; policy text data; qualitative analysis