Gui Ping ZHAO, De Cai LIANG, Qian Yu SHU
The National Natural Science Foundation of China (NSFC) is one of the fundamental departments funding mathematical research. Since its establishment, it has supported over 22,000 mathematical projects in China, with more than 8,600 being Youth Science Fund projects. Examining the application and funding status of the Youth program in mathematical disciplines is beneficial for understanding the scale of young mathematical talent development in China, assessing the quality of fund reviews, and planning fund support strategies. Utilizing data science techniques, the paper initially conducts an overall analysis of the application and funding status of Youth Science Fund projects. We then conduct hierarchical statistics analysis on project funding rates based on factors such as discipline, age, institution, and gender. Addressing the recent phenomenon of an overall “decreasing growth rate" in the Youth program, we further conduct statistical analysis from the applicants' perspective, including analyzing the changing patterns of funding proportions and comparing the funding rates of different applicants. Regarding the situation where recipients of Youth projects continue to apply for General projects, the paper utilizes the censored data mechanism and Kaplan—Meier estimation to infer the distribution of the time intervals between the approval of Youth and General programs. This approach provides more accurate estimates of the mean and quantiles of the time interval, effectively addressing the “sampling bias" problem that arises when considering only those who have obtained general project approvals.