Water for agriculture: challenges and opportunities in a war zone
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Wars, drought and social collapse have greatly impaired land management and agriculture production systems in the southeastern Afghanistan provinces of Khost, Paktika and Paktya. This region has long existed with limited central government influence and remains particularly unstable. A complex physical and social geography, on-going warfare, severely limited mobility and policies poorly adapted to regional realities hamper development and reconstruction. On-farm water efficiency improvement, watershed-scale work restricted to small, socially homogeneous watersheds and word-of-mouth Afghan-to-Afghan technology dissemination are particularly important development strategies in this environment. Keywords: community-based natural resource managementIndus watershedinsurgencymilitarystabilizationsustainable agriculture Acknowledgements The authors wish to recognize logistical support provided by military and civilian personnel with Task Forces Currahee, Rakkasans and Yukon. The support of the USAID-funded Afghanistan Water Agriculture and Technology Transfer project is also gratefully acknowledged. The manuscript has benefitted from the comments of J. Schoonover, K. Williard and an anonymous reviewer. The opinions stated in this paper are strictly those of the authors and are not intended to represent those of any government or organization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it