This study aimed to determine whether learning engagement plays a mediating effect on the relationship between family capital and students’ higher education gains in mainland China. We used family capital, learning engagement, and higher education gains as measures and analyzed data using a structural equation model. Data were collected from 1334 students at a Chinese university. The results show that family cultural capital had the most significant effect on students’ learning engagement, while economic capital also played a positive role, and social capital had no significant impact. Learning engagement played a mediating role in the relationship between cultural capital and higher education gains, as did the relationship between economic capital and higher education gains. However, learning engagement did not have a mediating effect on the relationship between social capital and higher education gains. Our results show that we should focus on the importance of students’ learning engagement, improve the cultural capital of disadvantaged groups, and provide financial support for students from low-income families.

The Creative Research Group (CRG) is the special high-level scientific and innovation team funded by the National Natural Science Foundation of China to promote basic research at the frontiers of science. In general, there are problems of “structure anomie” and “cooperation inefficiency” in the operations and teamwork dynamics within the nationwide CRG project. By extending and developing the two-stage teamwork quality model, this study aims to depict and analyze the impact factors behind the success and sustainability of the Creative Research Group (SSCRG), and reveal the relationships among them. Herein, rationality of team structure (ROTS) is used to describe the rationality of team formation and structure collocation, teamwork quality (TWQ) is used to describe the process of team members’ integration and cooperation, and SSCRG includes team performance, personal success and team comprehensive impacts. The results show that ROTS and TWQ have different influences on SSCRG, while TWQ is the key mediation factor between ROTS and SSCRG. In summary, the model built describes the complex phenomena and relationships in the teamwork of the CRG, and helps us to understand and solve the problems of structure and cooperation. Although the limitations lie in the specific samples and research methods, the extension and migration of classical models and theories would help to further deepen such research and contribute to the governance and development of such innovation teams.

Information technology (IT) policies have played an indispensable role in China’s IT research and development (R&D) and industrial development. However, there has been a lack of quantitative and clear understanding of the consistency and diversity of China’s IT policy mixes. In this article, we constructed policy target network to simulate the real policy mixes. Based on the distribution and evolution of networks, we identify and analyse the ‘diversity’ and ‘consistency & continuity’ of China’s IT policy. Our results show that China’s IT policies cover 12 different demands, and each demand corresponds to 5–10 core policy goals. At the same time, we divide the history of IT policy into seven periods and compare the characteristics of each period. Despite the scale of the policy mixes continuing to expand, the synergy between different policy targets has become clearer, forming unique communities. Among them, there are 25 core policy targets that reflect varying degrees of consistency and continuity. This study not only deepens the understanding of China’s policy characteristics and patterns, but also provides a quantitative framework for the assessment of policy consistency and diversity.