A pluriversal environmental governance? Ontological differences and knowledge co-production in scientific panels
Roger Merino & Ady Chinchay
What the paper says
Most models for international environmental governance acknowledge that the participation of non-state actors is critical; however, this participation is limited to a pre-political level in which scientific communities have a predominant role and indigenous ontologies are often marginalized. This article contextualizes these discussions by examining how ontological differences are incorporated or excluded in the international environmental governance of the Amazon rainforest. By exploring the interactions between Indigenous peoples and scientific communities, it examines the prospects of institutionalizing these interactions within the Amazonian Cooperation Treaty Organization (ACTO). The article relies on research during the years 2021-2024 involving semi-structured interviews and the comparative analysis of the the Science Panel for the Amazon (SPA) procedures and reports with the main international scientific platforms dedicated to the environment: the Intergovernmental Panel on Climate Change (IPCC) and the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES). The article argues that the inclusion of Indigenous peoples in these panels is not about knowledge co-production. Scientists conceive these panels through their Western universalist ontology as apolitical sites to collect, systematize, and diffuse scientific knowledge. In contrast, for Indigenous peoples, these are spaces for political exchanges on which they seek to formulate their political ontology and the proper ways to protect their world. Based on these findings, the article proposes reimagining scientist platforms and international decision-making forums as spaces for ‘pluriversal governance’.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.