Management of spatially extensive natural resources in postwar contexts: working with the peace process
Bibliographic record
Abstract
While extensively occurring natural resources play a fundamental role in the survival and recovery of postwar populations, their management is not presently part of the operational priorities in a peace process. Dependence on naturally occurring food, fuel, water, secure locations, and products that can be obtained and sold quickly for dislocated, war-weary populations is a primary approach to postwar livelihoods. The peace process however focuses on the logistical and institutional aspects of security, demobilization, reintegration and humanitarian efforts. The result is profound degradation of the spatially extensive resources necessary for longer-term recovery. The primary reason for the inattention to resource degradation in a peace process is that conventional conservation approaches do not fit with the priorities of a peace process or attend to the immediate needs of a postwar population; designed as they are for stable, peaceful settings. This article focuses on the need to derive postwar natural resource management approaches which can work with the in-place priorities of a peace process. Four such approaches are suggested, with successful examples from specific countries.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".