Incorporating ‘the earth and skies, the winds and rocks’:<sup>1</sup>nature as an active participant in conflict transformation and peacebuilding
Bibliographic record
Abstract
Winning essay: the 2009 Routledge – GCP&S Essay Competition† †An international essay competition encouraging contributions on global issues from graduate students and early career researchers. Scholars often re-tell and analyze peacebuilding stories as independent of locale, as though place does not matter. Inspired by a Mayan priest's observation that academic peacebuilding frameworks are missing ‘the earth and skies, the winds and rocks’, this article examines the role of nature in conflict transformation and peacebuilding. It reviews the results of studies highlighting nature's function in human evolution and in improving mental health and well-being. It then presents three case studies of peacebuilding processes in which participants interacted with one another in natural settings. When these cases are taken at the convergence of the empirical research on nature's emotional and physiological benefits to human beings, a meaningful pattern emerges. Each case becomes understood as tied to the ecologies of the place where participants engaged with one another, thus suggesting that nature is an active yet overlooked participant in conflict transformation and peacebuilding.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".