Abstract: Block grant and project funding are the two main modes for government research funding. Scientific analysis of the differences between the two funding modes is of great significance for the rational design of government research funding mechanisms. Multi-dimensional information contained in the output of these two funding modes from 2009-2018 in chemistry from Japan are taken as research objects Three-dimension analysis framework is built. In terms of methods, deep learning algorithms are introduced, and a training model for research object entity recognition in the field of chemistry is established, which realizes accurate recognition of research object entities and provides a factual basis for the analysis of funding differences. Data analysis results show that block grant and project funding have significant differences in multiple dimensions. The scientific research activities funded by block grant are more concerned in the research problem itself, while the scientific research activities funded by projects are more reflect the selection criteria from scientific community for projects. Policy recommendations of scientifically understand the difference between the two funding modes, rational layout, advancing strengths and avoiding weaknesses to establish efficient government research funding mechanism are proposed combing the data analysis results.

摘要： 稳定拨款与项目资助是政府科研资助的两种主要模式。科学分析两种资助模式的差异性，对合理设计政府科研资助机制具有重要意义。本文以日本化学领域2009-2018年，稳定拨款与项目资助的产出所蕴含的多维科研活动特征信息为对象，从研究团队、研究内容、研究产出绩效三个维度入手构建了科研要素视角下的资助差异性分析框架。方法上，引入了深度学习算法，建立了针对化学领域的研究对象实体识别训练模型，实现了对研究对象实体的精准识别，为资助差异性的分析提供了事实基础。数据分析结果显示，稳定拨款与项目资助在多个维度均具有显著的差异性，稳定拨款资助下的科研活动更关注于研究问题本身，而项目资助下的科研活动则更多地体现了科学共同体对项目遴选的标准。结合数据分析结论，研究提出了应科学认识两种资助模式的差异性，合理布局、扬长避短，建立高效的政府科研资助机制的政策建议。