MétaCan
Menu
Back to cohort

The United Nations and Support to Nepal's Peace Process: The Role of the UN Mission in Nepal

2012· book-chapter· en· W644534185 on OpenAlexaff
Ian Martin

Bibliographic record

VenueCambridge University Press eBooks · 2012
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsMandatePolitical scienceContext (archaeology)International peaceWork (physics)ConstitutionStrengths and weaknessesPublic administrationPolitical economyLawGeographyEngineeringPoliticsSociologyPsychology

Abstract

fetched live from OpenAlex

Nepal's peace process has been exceptional in the extent to which it was a truly national achievement and not one mediated by any international actor. The United Nations Mission in Nepal (UNMIN) too has been unusual among recent UN peace operations, which increasingly have had wide-ranging mandates, in the limited focus of its support, and among UN missions with a military function, in the lightness of its military component. This chapter explains how this mandate and mission configuration – negotiated between the expectations of the parties and the capacities of the UN – came about. It describes the work of UNMIN in monitoring the commitments of the peace agreements regarding the armies and their weapons and in assisting the country on its troubled path toward the election of a Constituent Assembly. It explains how the breakdown of cooperation among the parties after the election success of the Maoists delayed decisions about the future of the combatants and the nature of a federal constitution for the new republic. It concludes by considering the flaws in Nepal's peace process and the strengths and weaknesses of an unusual UN mission in this context, particularly the tensions UNMIN faced between a limited mandate and high expectations, as well as its inability to determine its exit strategy when it depended on decisions that it was largely excluded from assisting.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.992
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.249
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations14
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCambridge University Press eBooksSame topicPeacebuilding and International SecurityFrench-language works237,207