The modernization of science and technology（S&T）governance heavily relies on the scientific literacy of leading cadres and civil servants. Based on data from the 14th National Civic Scientific Literacy Sampling Survey，this study focuses on leading cadres and civil servants，revealing their characteristics in scientific literacy levels，structural disparities，and AI-related cognition. The findings indicate that while this group maintains a leading position in overall scientific literacy，demonstrating a notable“leading goose effect”，significant structural imbalances persist across gender，urban-rural，region，age，and educational attainment. S&T training plays a positive role in improving their scientific literacy and enhancing AI-related awareness and attitudes，yet its overall effectiveness in fostering scientific literacy remains limited. Moreover，while scientific literacy strengthens their cognitive judgment on frontier technologies such as AI，the translation of such literacy into practical competence remains insufficient. Accordingly，this study proposes reinforcing the“leading goose effect”to leverage the exemplary role of the“critical minority”；implementing targeted policies to narrow intra-group disparities in scientific literacy；and deepening the S&T training system by establishing a“learning-application-evaluation”closed loop to promote the transformation of scientific literacy into practical capabilities.

With the widespread application of artificial intelligence（AI），public understanding and attitudes toward AI have become key indicators of its social acceptance. Drawing on data from the 14th National Civic Scientific Literacy Sampling Survey，this study analyzes group differences in AI cognition and attitudes among Chinese citizens across four major social structural dimensions：educational attainment，occupational type，age cohort，and urban-rural background. The findings show that while Chinese citizens generally hold positive attitudes and exhibit a solid foundation of trust in AI，there are significant disparities among different groups in terms of cognitive level，usage frequency，confidence in AI development，and concerns about job displacement. Individuals with higher education levels and greater exposure to digital technologies tend to demonstrate more favorable cognition and attitudes toward AI. Younger cohorts display active cognition and open attitudes，whereas older adults are characterized by lagging cognition but optimistic expectations. Urban and rural residents also differ significantly in terms of baseline knowledge and anxiety about occupational risks. The study recommends promoting AI literacy among key populations，expanding vocational retraining programs，and improving risk governance mechanisms to ensure inclusive and equitable AI adoption through targeted public education.

The Internet platform media has gradually become the main way for citizens to access scientific and technological information in the digital era. Opportunities and challenges coexist for improving citizens’scientific literacy. Grasping the characteristic differences of citizens’access to scientific and technological information is of great significance for improving the efficiency of science popularization，bridging the digital divide，and improving citizens’scientific quality. Based on the data of the 14th National Civic Scientific Literacy Sampling Survey，this paper analyzes the channels of citizens’access to scientific and technological information and the development of scientific literacy，describes the current situation of Chinese citizens’access to scientific and technological information，and discusses the differences in channels and preference reasons for citizens from different groups to obtain technological information in the context of the digital age. The study found that the proportion of citizens’access to scientific and technological information through the Internet has leapt；social platforms and short video platforms have become the main sources for Internet users to obtain scientific and technological information；citizens interested in scientific and technological information prefer to multiple channels；the internal drive is the first motivation for citizens to obtain scientific and technological information，while the practical demand is the main motivation for citizens to obtain scientific and technological information；the channels for different groups of citizens to obtain scientific and technological information have their own characteristics；different groups with different levels of scientific quality have different access to scientific and technological information. Based on this，this article proposes to improve policy formulation and strengthen the guidance of science popularization content in short videos and social media platforms，strengthen content adaptation and promote precise science popularization supply for various groups，and suggest bridging the digital divide and promoting coordinated development of urban and rural information dissemination infrastructure.

Scientific literacy is an important part of national literacy，and improving scientific literacy is of great significance to the development of citizens themselves and the country. Science popularization places are one of the important ways for citizens to obtain scientific knowledge and improve scientific literacy. Based on the data of the 14th National Civic Scientific Literacy Sampling Survey in 2024，it is found that citizens are willing to visit various science popularization places；Citizens have gained after visiting; Visiting science popularization places is related to the citizens’scientific literacy，and their visiting behavior，motivation and gains all have a positive effect on scientific literacy. However，there are still some problems to be solved in various science popularization places，such as the number of science and technology places can not meet the needs of public visits，the opening opportunities of science innovation places need to be increased，the threshold for visiting museum places is high while the visit gain is low，and the forms of science popularization activities in cultural places need to be enriched. Based on this，this study puts forward suggestions to optimize the layout and construction of science and technology places，build and share science popularization places jointly，and stimulate social forces to do science popularization.

The national science popularization system and the construction of national science popularization capacity are of great significance for continuously improving the scientific literacy of the entire population，achieving high-level scientific and technological self-reliance and self- improvement，meeting the people’s ever-growing demand for scientific life，and comprehensively building a strong country in science and technology. This article explores the conceptual connotations of the national science popularization system and national science popularization capacity from the meta-concepts of“system”and“capability”. That is，the national science popularization system and national science popularization capacity are a concentrated reflection of a country’s entire set of systematic arrangements and comprehensive strength regarding science popularization. From the perspective of“structure-function”，this article systematically examines the diverse logical relationships between the two. The national science popularization system is the front-end structural construction，while the national science popularization capacity is the post-functional embodiment. The two are composed of a closely coordinated and functionally embedded complementary relationship. Based on this institutionalized logical approach，a set of efficiency improvement paths is proposed，including policies on science popularization，subjects of science popularization，diverse safeguard mechanisms for science popularization investment，management mechanisms combining supervision and incentives，and international science popularization exchange mechanisms.

Promoting the popularization of scientific and technological resources in national key laboratories is an important part of the construction of the development pattern of science popularization. Combining the real advantages of laboratory popularization of science and technology resources and the current social demand for safety and emergency response，with public service theory as the theoretical support，this paper constructs a“1+3”framework for analyzing the supply of public services for science popularization，and compares the cases of public services for science popularization in eight national key laboratories. It also compares the cases of eight national key laboratories’safety science popularization public services，and finally puts forward countermeasures and suggestions to reform the laboratory’s scientific research evaluation system，strengthen the development of the laboratory’s science popularization resources，centralize the network information resources for science popularization，and make full use of the new media platform to optimize the laboratory’s science popularization public services. The study will provide a useful reference for laboratories to concentrate on the themes of science popularization and construct a resource landscape for the provision of safety science popularization public services.

This study focuses on Generation Z users’experiences and behavioral preferences with museum mobile guides. Based on the pragmatic and hedonic dimensions of the positive user experience model，20 one-on-one in-depth semi-structured interviews were conducted with Gen Z participants. NVivo 14.0 software was used for coding and analysis. The research identifies four core experiential needs: ease of information access，personalization of tour paths，immersive multi- sensory engagement，and narrative-based knowledge construction. Accordingly，an optimized mobile guide strategy framework was developed，structured around three phases：information presentation，information transmission，and information feedback. The findings provide both theoretical support and practical guidance for the integrated development of cultural communication and science popularization in museums under digital empowerment，offering a valuable reference for enhancing the effectiveness of experiential mobile guide systems in science popularization.

To strengthen the national capacity for science popularization and further implement the initiative to enhance the scientific literacy of all citizens，the China Association for Science and Technology（CAST），in collaboration with the National Bureau of Statistics，conducted the 14th national sample survey on Chinese civic scientific literacy in 2024. This survey provided critical data for the evaluation of the“Outline of the National Scheme for Scientific Literacy（2021—2035）”during the 14th Five-Year Plan period，as well as for achieving the goal of raising the proportion of citizens with scientific literacy to over 15% by 2025. The results show that the scientific literacy of Chinese citizens has been improving at an accelerating pace，with the proportion reaching 15.37% in 2024. The imbalance in scientific literacy development has been alleviated to some extent，and the population with basic scientific literacy is now substantial. The internet has further solidified its position as the primary channel for citizens to access scientific and technological information，while science and technology museums have demonstrated higher visitation and utilization efficiency among various science popularization infrastructures. Overall，Chinese citizens increasingly value science，adopt rational and pragmatic attitudes，and support innovation，with further improvements in critical thinking and scientific awareness. The development of artificial intelligence（AI）enjoys a strong public foundation，with citizens holding positive attitudes and ample confidence toward AI applications，though some concerns remain about job displacement.

The popularization of frontier scientific achievements plays a pivotal role in enhancing public understanding and engagementwith science. With the widespread application of generative artificial intelligence（GenAI），its potential performance of popularizing frontier scientific achievements has become a critical topic. Unlike the generation of general science popularization content，GenAI encounters distinct challenges when addressing topics related to frontier scientific achievements. Firstly，there is a paucity of sufficient online textual data for GenAI training.Secondly，these topics often entail relatively higher uncertainty，necessitating a more cautious approach to content formulation. This study conducts a comparative analysis of science popularization content on frontier scientific achievements generated by traditional science popularizers and that produced by GenAI models. The results indicate no significant disparities between the two in terms of scientific accuracy and source reliability. However，the content generated by GenAI models tends to exhibit a more positive emotional tone compared to that produced by traditional science popularizers. Based on these results，this study suggests that while the risk of GenAI disseminating misinformation may be limited，it has the potential to reinforce existing stereotypes. Consequently，GenAI can not entirely supplant traditional science popularizers within the current framework of science popularization.

Generative artificial intelligence（AI）has emerged as a pivotal tool in the creation of science popularization literature; however，its capability in this domain remains subject to skepticism when compared to human authors. To evaluate the sciencepopularization writing competence of generative artificial intelligence，a four-dimensional evaluation framework was developed，comprising readability，engagement，scientific accuracy，and dissemination effectiveness. Using“microbiology”as the thematic focus，sciencepopularization works produced by human creators，DeepSeek，ChatGPT，and ERNIE Bot were systematically examined. The results indicate that both the initial-prompt and deep-prompt versions generated by ChatGPT showed no significant difference in overall scores relative to the human-authored version，with the deep-prompt version exhibiting a significantly superior performance in terms of readability. Moreover，the deep-prompt version of DeepSeek outperformed the human version in the dimensions of engagement and dissemination effectiveness. Notably，evaluators correctly distinguished AI-generated works in less than 55% of cases and showed a tendency to attribute high-scoring works to human creators. These experimental findings suggest that generative artificial intelligence holds the potential to substitute for humanscience popularization creators，thereby prompting the proposal of a novel“human-machine collaborative sciencepopularization creation”model. The study further calls upon the academic community to critically examine the phenomenon of the“Hallucination of Human’s Ability”.