关键词: 复杂网络, 安全生产政策, 央地政策协同, 主题匹配度, 文本相似度

Abstract:

To enhance China's work safety governance level, policy texts on work safety issued by the central government and 30 provincial-level governments from 2014 to 2023, as well as safety accident data from the same period, were used as the research sample. By integrating the Levenshtein distance algorithm, the Jaccard similarity algorithm, and other similarity measures, a "theme-content" two-stage policy synergy analysis model was proposed. Central-local policy synergy degree was quantitatively measured through a weighted evaluation of policy theme matching degree and content similarity. A complex synergy network was then constructed. Using social network analysis and modularity algorithms, the structural characteristics of the central-local safety policy synergy network were analyzed in depth, and its spatiotemporal evolution was revealed. Based on panel data, the impact of central-local synergy outcomes of safety policies on accident incidence were further investigated. The results show that China's central-local safety policy synergy network is exhibiting an increasingly integrated development trend over time. The responsiveness of provincial governments to central policies is continuously improving, evolving from early regional differentiation toward comprehensive nationwide coordination, and an initial "central planning-local response" national work safety policy system has been initially established. Moreover, the central-local policy synergy degree is significantly negatively correlated with the frequency of safety accidents, and improving the level of coordination can effectively reduce the risk of work safety accidents.

Key words: complex network, work safety policy, central-local policy synergy, theme matching, text similarity