Enhancing Public Participation in Poverty Governance: A Policy Feedback Framework of China’s Counterpart Assistance
Abstract
Public participation is critical to the effective implementation of anti-poverty policies, but it faces challenges such as low participation from marginalised groups, which stems from low awareness of opportunities for participation, lack of motivation, lack of resources and barriers such as the high cost of participation. The Chinese government's counterpart assistance policy is believed to have played an important role in mobilising public participation in poverty alleviation, but its mechanisms and impacts on public participation, especially in terms of social and political effects, remain understudied. This study aims to construct a comprehensive analytical framework to elucidate how counterpart assistance affects public participation in anti-poverty efforts through policy feedback theory and involutional effects, covering both positive and negative feedback mechanisms. A systematic literature review constructs a conceptual framework that explains how counterpart assistance affects public participation by integrating participation resources, participation attitudes, and participation autonomy as mediating variables. The proposed framework argues that counterpart assistance positively affects public participation through participation resources (resource effect) and participation attitudes (interpretation effect), enhancing material support and shaping positive attitudes. However, counterpart assistance may negatively affect participation autonomy, leading to an involution effect that manifests itself in reduced autonomy and formalistic participation. These mediating variables highlight the dynamic interaction of policy feedback in public participation. The framework offers fresh ideas for designing effective anti-poverty policies in developing countries, guides future empirical research, and informs policy adjustments to enhance public participation by balancing resource provision, attitude shaping, and autonomy maintenance.
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