Indigenous Participation and the Incorporation of Indigenous Knowledge and Perspectives in Global Environmental Governance Forums: a Systematic Review
Why this work is in the frame
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Bibliographic record
Abstract
Global environmental governance (GEG) forums, such as those convened through the United Nations, result in the development of monumental guiding frameworks such as the Sustainable Development Goals (SDGs) and the Convention on Biological Diversity (CBD) Conference of Parties (COPs) Aichi and post-2020 targets. The ratification of policy frameworks by member and/or signatory states can result in major shifts in environmental policy and decision-making and has major implications for Indigenous communities. In this article, we present systematic review of the peer-reviewed literature on Indigenous participation in GEG forums, and focus on the specific questions: (1) what GEG forums include Indigenous participation and (2) how do Indigenous peoples participate in GEG forums, including how their perspectives and knowledges are framed and/or included/excluded within governance discussions, decisions, and negotiations. We provide a bibliometric analysis of the articles and derive seven inductively determined themes from our review: (1) Critical governance forums and decisions; (2) inclusion and exclusion of Indigenous voices and knowledge in GEG forums; (3) capacity barriers; (4) knowledge hierarchies: inclusion, integration, and bridging; (5) representation and grouping of Indigenous peoples in GEG; (6) need for networks among and between Indigenous peoples and other governance actors; and (7) Indigenous peoples influence on GEG decisions and processes. Our findings can be used to improve GEG forums by contributing to the development strategies that address the barriers and inequities to meaningful and beneficial Indigenous participation and can contribute to future research that is focused on understanding the experiences of Indigenous peoples within GEG forums.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it