Inclusion in body and mind: ensuring full participation of Indigenous peoples and local communities in decisions related to nature
Bibliographic record
Abstract
The inclusion of the knowledge and perspectives of Indigenous peoples and local communities (IPLC) in global sciencepolicy processes are increasingly being mandated. This is indicative of the recognition of their expertise and worldviews to inform social and ecological decisions. The IPBES Values Assessment (VA) explicitly highlighted the necessity for a nuanced engagement of different actors while undertaking valuation for decisions related to nature. In this paper we further reflect on the findings of Chapter 6 of the VA that focused on operationalizing diverse values approaches in policy. We examine how IPLC are consulted and their values included in sectoral and cross-sectoral policies interlinked with biodiversity. We specifically share IPLC experiences of the IPBES process based on personal reflections of a participating Indigenous scholar. Apart from emphasizing the pitfalls of excluding diverse IPLC values of nature from decision making, our review also discusses how IPLC perspectives are represented within global forums, and particularly in IPBES processes. Our analysis reveals that meaningful IPLC inclusion pertains to representation of knowledge (mind) and of active participation and agency to bring their networks into the discourse (body). While highlighting some major deficiencies of the current decision-making practices (e.g., lack of pluralistic and inclusive processes, human and financial resources, or culturally sensitive processes) that preclude the full and effective inclusion of IPLC, we offer promising approaches, specifically engaging reflexivity and learning, that can address these deficiencies and move toward ensuring higher representation of IPLC by and for themselves.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".