Migrants workers are important participants in and contributors to economic and social construction, but they still face the reality of being marginalized. Based on data from the China Migrants Dynamic Survey in 2018, this paper systematically investigated the impact of public health services on the multidimensional poverty of migrant workers. The research found that, first, the current mean of the multidimensional poverty deprivation value of migrant workers is 0.1806, which is one dimension of poverty that exists on average. In addition, migrant workers do not have high access to public health services. The proportions of migrant workers who have not established residents’ health files and who have not received public health education are 74.22% and 29.92%, respectively. Second, public health services can significantly alleviate the multidimensional poverty of migrant workers. After mitigating the potential endogeneity problem by the IV-2SLS method and conducting robustness tests by the PSM method, the conclusion is still robust. Further research found that the impact of public health services on the multidimensional poverty alleviation of migrant workers is heterogeneous. The improvement of public health services has the greatest effect on the multidimensional poverty alleviation of the new generation of migrant female workers in the western region. The research in this paper helps to examine and clarify the policy significance of public health services for the multidimensional poverty alleviation of migrant workers and provides empirical evidence for the use of public health services to tackle the poverty problem.

The convergence of rural industries has brought about significant changes in the traditional small-scale farmer management model, as well as new requirements for the quality and skills of agricultural practitioners in China. Meanwhile, it has inevitably affected the agricultural environmental total factor productivity (AETFP). This paper endeavors to assess the impact of industrial convergence on AETFP, striving to clarify their inherent connection and furnish insightful guidance for policymaking. Utilizing inter-provincial panel data from China spanning 2008 to 2021, this paper applies the SBM-GML model for measurement purposes and employs the entropy method to evaluate the extent of industrial convergence in rural areas. It delves into the mechanism through which industrial convergence influences AETFP, utilizing the intermediary effect model and incorporating two mediating variables: rural human capital and agricultural scale operations. The findings of this research reveal that industrial convergence exerts a direct positive influence on AETFP, while rural human capital and agricultural scale operations serve as partial mediators in this process. Additionally, the stability of the transmission mechanism receives further validation via the application of interaction terms. Consequently, it is possible to enhance AETFP via the expedited convergent development of industries, coupled with the strategic utilization of rural human capital and agricultural scale operations as catalysts for further improvements in AETFP.