Abstract: Public trust in occupational groups and their expertise is a fundamental pillar of social stability. As professions become increasingly integrated with the broader social environment, the system of trust once underpinned by the "closure" of classical professions has been eroded, catalyzing a relational turn in the sociology of professions. This study develops a tripartite framework of relational mechanisms shaping public trust in occupations:relationships among occupations within the professional system, relationships between occupations and the market, and relationships between occupations and the state. Employing the Chinese Occupational Classification System (2022 edition) and the Tencent AI Lab Embedding Corpus, this study quantitatively assesses public trust in occupational expertise of a comprehensive set of occupations. It investigates how occupational network structures, the public nature of occupations, and China's distinctive system of occupational governance shape such trust. The findings reveal three key insights. First, task jurisdictional similarity between occupations exhibits an inverted U-shaped relationship with technical trust. Second, in an era of increasingly permeable knowledge boundaries, occupational groups that are client-independent and possess more abstract expertise are more likely to garner public trust. Finally, the study advances a localized institutional explanation:in contrast to the "associational professionalism" characteristic of the Anglo-American model, China regulates professional entry barriers through state-led qualification systems, which positively influences public trust in its occupational groups.