Evaluating the Structural Quality of Agricultural S&T Commercialization Policies: An Integrated Approach Combining Latent Dirichlet Allocation and the PMC Index

Promoting the commercialization of agricultural science and technology (S&T) achievements is a critical pathway toward achieving agricultural sustainability and a key governance challenge in advancing global food security and the Sustainable Development Goals (SDGs). However, China faces a structural paradox: despite sustained expansion of policy supply, the performance gains in technology commercialization remain limited. To uncover the underlying causes, this study integrates Latent Dirichlet Allocation (LDA) topic modeling with the Policy Modeling Consistency (PMC) index to conduct a systematic analysis of 82 central-level policy documents issued between 2015 and 2025. The findings reveal that policy attention is heavily concentrated on upstream R&D support, while insufficient emphasis is placed on downstream “last-mile” enablers—such as diffusion services, risk-sharing mechanisms, and intermediary capacity building. Moreover, many policies exhibit structural deficiencies in temporal specificity and multi-actor coordination, which hinder the formation of closed-loop implementation chains. The results suggest that policy structural inconsistency may be a key mechanism constraining policy effectiveness. By adopting a dual analytical lens of “attention allocation–structural design,” this study provides empirical evidence for optimizing policy formulation and enhancing institutional efficacy in agricultural S&T commercialization.