MétaCan
Menu
Back to cohort
Record W78750265 · doi:10.1017/cbo9781139021869

Nepal in Transition

2012· book· en· W78750265 on OpenAlexaff
Sebastian von Einsiedel, Deepak Thapa, Rhoderick Chalmers, Devendra Raj Panday, Mahendra Lawoti, Teresa Whitfield, Frederick Rawski, Ian Martin, Catinca Slavu, Aditya Adhikari, Rajeev Ranjan Chaturvedy, S. D. Muni, Prashant Jha

Bibliographic record

VenueCambridge University Press eBooks · 2012
Typebook
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsNepaliPolitical scienceAutocracyPeacemakingContext (archaeology)DemocracyInsurgencyPoliticsInternational securitySecurity sector reformPolitical economyPublic administrationLawSociologyGeography

Abstract

fetched live from OpenAlex

Since emerging in 2006 from a ten-year Maoist insurgency, the 'People's War', Nepal has struggled with the difficult transition from war to peace, from autocracy to democracy, and from an exclusionary and centralized state to a more inclusive and federal one. The present volume, drawing on both international and Nepali scholars and leading practitioners, analyzes the context, dynamics and key players shaping Nepal's ongoing peace process. While the peace process is largely domestically driven, it has been accompanied by wide-ranging international involvement, including initiatives in peacemaking by NGOs, the United Nations and India, which, throughout the process, wielded considerable political influence; significant investments by international donors; and the deployment of a Security Council-mandated UN field mission. This book shines a light on the limits, opportunities and challenges of international efforts to assist Nepal in its quest for peace and stability and offers valuable lessons for similar endeavors elsewhere.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.024
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0050.003
Open science0.0000.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0240.006

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 head0.026
GPT teacher head0.247
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), 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

Citations56
Published2012
Admission routes1
Has abstractyes

Explore more

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