The multilevel governance of selective waste collection policy through its instrumentation and the circulation of public policy communities.

• Grant number: 24/23817-7
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: March 01, 2025
• End date: June 30, 2026
• Field of knowledge: Humanities - Political Science - Public Policies
• Principal Investigator: Renata Mirandola Bichir
• Grantee: Jessica Duquini dos Santos
• Host Institution: Faculdade de Filosofia, Letras e Ciências Humanas (FFLCH). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 13/07616-7 - CEM - Center for Metropolitan Studies, AP.CEPID

Abstract

The doctoral research aims to analyze the multilevel governance of the selective waste collection policy, focusing on the multilevel interaction processes between state and non-state actors and instruments in the implementation of this policy from 2002 to 2020. To this end, the research will examine the circulation of public policy communities between the national and municipal levels, as well as the public policy instruments involved in the governance of this policy and their effects on implementation. Selective waste collection is nationally regulated by the National Solid Waste Policy (PNRS), which establishes a series of instruments and mandates the inclusion of recyclable material collectors. However, it is implemented at the municipal level, raising questions about how the interaction between actors and instruments at the national and local levels affects the implementation of this policy. A multiple case study of a qualitative nature will be conducted to understand the vertical and horizontal aspects of governance. The cases of São Paulo and Belo Horizonte were selected based on the method of similarities, as both cities had local regulations, instruments, and the participation of private initiatives and recyclable material collectors in the policy even before the PNRS was enacted. The study will use methods such as literature review, document analysis, and semi-structured interviews. The data will be analyzed based on the proposed concepts and using Content Analysis, and coded using NVivo.