Bibliographic record
Abstract
At the global level, the year 1997 was undoubtably the pinnacle of interest in mine action. This was the year that saw the award of the Nobel Peace Prize to Jody Williams and the International Campaign to Ban Land Mines (ICBL), the tragic death of Diana, Princess of Wales, the opening of the Anti-Personnel Mine Ban Convention (APMBC) for signature in Ottawa, the establishment of the United Nations Mine Action Service (UNMAS) as the UN focal point for mine action, the formation of the Geneva International Centre for Humanitarian Demining (GICHD), the genesis of the Mine Action Support Group (MASG), and the first publication of this Journal. However, these events did not just happen overnight; there was a full decade of work and commitment leading up to these significant achievements. This article looks at the challenges and successes of the early days of humanitarian mine action (HMA), particularly in the areas of coordination, standardization, and information sharing.
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.
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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.033 |
| Scholarly communication | 0.019 | 0.018 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".