Diverse understandings and values of nature at the peace–environment nexus: a critical analysis and policy implications towards decolonial peace
Bibliographic record
Abstract
Scholarship in peace and conflict studies is paying increasing attention to the role of the environment for conflict transformation and peacebuilding. However, a closer analysis on how different understandings of “nature” implicate policy proposals and approaches to peacebuilding is lacking. In this study, we provide a critical reflection on the diverse understandings and valuations of nature at the nexus of peace and environment. We do this from a decolonial approach and with a particular focus on the concept of sustainable peace. We first discuss our theoretical approach based on a critical and pluralistic understanding of “environment” as “nature” and a decolonial stand on peace. We then construct an analytical framework based on the values framework developed by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) that highlights different worldviews, approaches, notions, and conceptualizations of nature’s contribution to human well-being and implications incorporating Indigenous and local systems of knowledge. Drawing on academic publications that provide empirical and conceptual discussions on the role of nature and environment in peace transformation from diverse regions of the world, we interpret the diverse understandings and valuations of nature in relation to peace. We find that a limited understanding and valuation of nature (and peace) limits the transitions towards a more profound re-mending of the social-ecological relationships that are needed for sustainable peace. We argue that future research should focus on overcoming the ontological bias that persists in the literature at the nexus of peace and the environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.048 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.020 | 0.132 |
| Scholarly communication | 0.027 | 0.047 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.009 | 0.023 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".