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The 2008 Constituent Assembly Election: Social Inclusion for Peace

2012· book-chapter· en· W195544911 on OpenAlexaff
Catinca Slavu

Bibliographic record

VenueCambridge University Press eBooks · 2012
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsPolitical scienceDemocracyPolitical economyInclusion (mineral)PoliticsState (computer science)Context (archaeology)Representation (politics)Perspective (graphical)Public administrationEconomic systemSociologySocial scienceLawGeographyEconomics

Abstract

fetched live from OpenAlex

A Balancing Act Electoral processes are not serving their main purpose, that of consolidating or deepening democracy, unless they are fostering a political system representative of the society and advancing human rights. The election for Nepal's long-pursued Constituent Assembly was meant to ensure such a democratic transformation and, with it, the deliverance from a decade-long conflict. In the context in which large-scale social exclusion had been the root cause of the conflict in Nepal, this chapter focuses on the opportunities and limitations for peace and state-building through electoral processes from the perspective of inclusive representation. Two circular paradigms framed the Constituent Assembly electoral process. Holding an early election would sustain the necessary momentum for the peace process by maintaining the trust between the main parties to it, the Seven Party Alliance and the Communist Party of Nepal (Maoist) (CPN-M). At the same time, holding the election before granting the traditionally marginalized communities the freedom to elect their own representatives was prone to opening a new dimension for the conflict.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0050.004
Open science0.0000.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.002

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.

Opus teacher head0.033
GPT teacher head0.270
Teacher spread0.237 · 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
GenreEmpirical

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

Citations3
Published2012
Admission routes1
Has abstractyes

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