Bibliographic record
Abstract
Nepal's peace process was both led and driven by Nepalis, but it was also remarkably open to the involvement of a wide range of external actors. This chapter focuses on the most prominent and committed of the international peacemakers involved – among them the Swiss-based nongovernmental organization (NGO), the Centre for Humanitarian Dialogue, that worked in Nepal from 2000–6; the United Nations, whose secretary-general first offered his “good offices” in 2002 and whose presence later grew into a large Office of the UN High Commissioner for Human Rights (OHCHR, established in 2005) and a special political mission, the United Nations Mission in Nepal (UNMIN, formed in 2007); the Carter Center, whose conflict resolution program engaged with Nepal from 2004–6; and the government of Switzerland, which dispatched a special adviser for peacebuilding to Nepal in mid-2005. The chapter also analyzes the critical role played by India, which is explored more fully elsewhere in this volume.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".