摘要：
目的 全面审视科技期刊编辑群体的就业质量，并据此提出应对就业变革的有效举措。 方法 从宏观与微观双重层面出发，收集并分析2020—2024年《中国科技期刊发展蓝皮书》中“人力资源”部分数据，采用“问卷星”平台在全国范围内实施大规模问卷调查并分析1058份有效问卷的相关数据。 结果 科技期刊编辑群体的就业规模较为平稳、岗位类型设置多样、从业人员素质较高、职业发展方式丰富且职业情感较为浓厚，整个群体的就业质量表现良好。但是，行业内部劳动力市场的潜在风险及生成式人工智能技术的强力冲击，导致编辑群体就业质量的提升还有一定障碍。 结论 加速人工智能应用场景创新、赋能科技期刊就业生态，提升编辑群体数字技能、分门别类进行人力资本投资，动态更新职业分类、探索做好人机协同布局，以此推动整个科技期刊行业形成匹配高效、机会充分、保障健全、流动顺畅的就业格局。
关键词:
科技期刊,
编辑,
生成式人工智能,
就业质量,
就业形态
Abstract:
Purposes To conduct a comprehensive examination of the employment quality of the scientific journal editor group and propose effective measures to address employment changes accordingly. Methods This study adopts a dual macro-micro analytical framework. It collected and analyzed data from the “Human Resources” section of the China Scientific Journal Development Blue Book （2020—2024） and conducted a nationwide large-scale questionnaire survey and analyzed 1058 valid responses. Findings The findings reveal that the employment scale of scientific journal editors remains stable， with diverse post types， highly qualified practitioners， multifaceted career development pathways， and strong professional commitment， indicating overall favorable employment quality. However， potential risks in the internal labor market of the industry and the strong impact of generative AI technology have created certain obstacles to improving the employment quality of editors. Conclusions First， accelerate the innovation of AI application scenarios to empower the employment ecosystem of scientific journals； second， enhance the digital skills of editors and carry out categorized human capital investment； third， dynamically update occupational classifications and explore the layout of human-machine collaboration. These measures aim to promote the formation of an employment pattern in the entire scientific journal industry with efficient matching， sufficient opportunities， sound protection， and smooth mobility.
Key words:
Scientific journals,
Editors,
Generative artificial intelligence,
Employment quality,
Employment patterns
高虹, 米然. 生成式人工智能背景下科技期刊编辑就业质量提升的现实障碍及应对策略[J]. 中国科技期刊研究, 2025, 36(8): 1026-1034.
GAO Hong, MI Ran. Practical obstacles and coping strategies for enhancing the employment quality of scientific journal editors in the context of generative artificial intelligence[J]. Chinese Journal of Scientific and Technical Periodicals, 2025, 36(8): 1026-1034.