Commentary on ‘The economics of landmine clearance: case study of Cambodia’
Bibliographic record
Abstract
Abstract A recent cost‐benefit analysis of landmine clearance in Cambodia (Harris, JID 12 (2), 2000) reported a net present value (NPV) of minus $3,434 million, and concluded landmine clearance using existing technologies is not economically justified for Cambodia. Professor Harris suggested higher returns would accrue to investments in de‐mining technology, while aid funds for landmine clearance should be reallocated to meet other development objectives. However, the methodology used massively overstates the present value of de‐mining costs while the estimated benefits are far too low. More fundamentally, the specification of the model makes it suitable only for an ‘all‐or‐nothing’ decision whether to rid Cambodia entirely of landmine contamination, and does not allow the analysis of targeted clearance of priority land. With appropriate adjustments, the economics of landmine clearance in Cambodia are not bleak, and may well yield positive rates of return in NPV terms. Copyright © 2001 John Wiley & Sons, Ltd.
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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 | 0.006 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.038 | 0.018 |
| Insufficient payload (model declined to judge) | 0.010 | 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".