In, Out or Beyond? Waste Pickers and Policy Networks: A Story from Jardim Gramacho (Rio de Janeiro)

Abstract

As circularity is momentous, waste-picker communities all around the world are getting noticed. Brazil is at the forefront of waste-picker community inclusion, recognizing, by law, waste-pickers as professionals who must be part of waste management. This level of institutionalization is the result of a political struggle within the national waste policy network over more than twenty years. Understanding these political relations is key to recognising the role of waste-pickers and making the case for justice in the circularity discourse and practices. This research presents the result of an extended case study of over seven years duration conducted by the author on the community of Jardim Gramacho, in the Rio de Janeiro Metropolitan Region. Building upon the policy network theory, this paper first maps the policy community and the issue network of waste governance. Second, through a thematic analysis of 20 semi-structured interviews, core themes are identified. These themes depict the waste-picker community beyond a paternalistic reading recognizing their agency and identifying a plurality of roles waste-pickers are playing in the waste policy community, among them the role of institutional stewards. In the conclusion, a research agenda is outlined, highlighting the need for transdisciplinarity in doing research with waste-pickers.

What Does It Mean to Have a Dirty and Informal Job? The Case of Waste Pickers in the Rio Grande do Sul, Brazil

“…Over the most recent years, occupations related to the collection and disposal of urban waste, such as street cleaners, refuse collectors or waste pickers, have assumed an increasingly important role within urban economies, not only as crucial operators for translating into practice the supply of an essential service, but also as workers who, through their daily activities, make it possible to develop forms of circular economy [17,19,29,56,57]. Despite their growing importance, they continue to be part of the so-called dirty workers, subject to various forms of stigma and forced to deal with difficult working conditions and low wages.…”

“…The collected data were transcribed, anonymized, systematized, and analysed by applying qualitative content analysis based on thematic coding [54]. This basically involved generating initial codes through the raw data, identifying specific themes, and interpreting the identified themes (as conceptual blocks) [48,55,56]. The following section discusses the interpretation of the main empirical results.…”