Spatiotemporal evolution and heterogeneous driving mechanisms of social work organizations in China: evidence from the Hu Huanyong Line

Introduction As a critical component of modern social governance systems, the scientific spatial allocation of social work organizations (SWOs) directly affects the equitable provision of public services. Methods Using panel data from prefecture-level and higher cities in China spanning 2000–2024, this study systematically investigates the spatiotemporal evolution and driving mechanisms of SWOs through kernel density estimation, center-of-gravity trajectory analysis, Geodetector method, and geographically weighted regression (GWR). Results (1) SWO development in China has progressed through three distinct phases, early development, rapid expansion, and subsequent contraction, with registrations peaking in 2021. Their spatial distribution exhibits pronounced clustering and geographic proximity effects, closely following the Hu Huanyong Line (Hu’s Line), and forming a polycentric pattern centered on the Pearl River Delta, the Yangtze River Delta, the Beijing–Tianjin–Hebei region, and the Chengdu–Chongqing region. (2) Geodetector analysis identifies city administrative level as the primary driver of spatial differentiation, whereas physical factors such as terrain impose minimal constraints. OLS and GWR results further reveal substantial spatial nonstationarity: at the global scale, per capita disposable income and migrant population size consistently exert positive effects, while at the local scale, social security expenditure demonstrates a dual influence, constraining SWO growth in eastern regions but promoting it in central and western regions. Discussion These findings reveal a fundamental shift in the development logic of SWOs, from “exogenous administrative empowerment” toward a demand-driven model. This study provides the first prefecture-level national evidence of spatial polarization in SWO development across China, uncovers region-specific driving mechanisms on both sides of Hu’s Line, and highlights the pivotal role of educational capacity in resource-constrained areas.