The roles and values of the natural environment in Northern Uganda’s peace process: a conceptual document analysis
Bibliographic record
Abstract
Over the past years, the natural environment has increasingly become instrumental in peace policies and the focus of study in peace and conflict research. Concurrently, there is mounting global recognition that nature contributes to peoples wellbeing in manifold ways and that incorporating diverse values of nature in policymaking is paramount for sustainable development. At the nexus of current debates on environmental peacebuilding and nature values and contributions to people, the aim of this study is to understand how peace narratives in Northern Uganda have integrated environmental considerations and accommodated diverse understandings and values of nature to reflect on prospects for sustainable peace. Even though the armed conflict between the Lord Resistance Army and the Government of Uganda in Northern Uganda was not a conflict for access and control over natural resources per se, twenty years of conflict have affected the natural environment as well as social-ecological relations between local peoples and nature. Informed by our theoretical approach from political ecology, we carry out a descriptive and conceptual document analysis using an analytical framework based on three types of values of nature: (a) instrumental, when nature is valued as an instrument or means to an end, (b) intrinsic, when nature is valued in itself, and (c) relational, when nature is valued as the social-ecological relations that it nurtures among people and people and nature. Our central argument is that for peace to be sustainable, understandings and values stemming from peoples directly affected by armed conflicts and dependent on their natural environment should permeate peace narratives and strategies. In particular, relational values of nature become central for nurturing relations, regulating conflict, and eventually assisting the possibilities for long-lasting peace.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".