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Record W1989479287 · doi:10.5539/ass.v5n6p3

Internally Displaced Persons in Nepal: Neglected and Vulnerable

2009· article· en· W1989479287 on OpenAlexaffvenue
Ritendra Tamang

Bibliographic record

VenueAsian Social Science · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicHydropower, Displacement, Environmental Impact
Canadian institutionsMount Royal UniversityRoyal College of Physicians and Surgeons of Canada
Fundersnot available
KeywordsInternally displaced personGeopoliticsDisplaced personPolitical scienceGovernment (linguistics)International communityArmed conflictDevelopment economicsEconomic growthDisplacement (psychology)RefugeePoliticsLawPsychologyEconomics

Abstract

fetched live from OpenAlex

This article examines Nepal’s policies regarding internally displaced persons (IDPs), and aid efforts by international aid agencies and donors. Ten years of conflict (1996-2006) between the Nepal government and the Maoists was a main cause of the displacement of many people. Although the international community acknowledged that the armed conflict between Maoist forces and Nepal security forces contributed significantly to the displacement, the crisis did not receive enough international attention until recently. Ongoing violence in some districts of Nepal continues to pose major challenges to many returnees and to the peace process. The contradictions and tensions existing within Nepal’s IDP policies create further strains, especially on individuals and families displaced by Nepal security forces. Researchers, policy makers, and international agencies need to be aware of the geopolitical factors that could endanger the effectiveness of aid distribution to displaced Nepalese.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0120.006
Scholarly communication0.0050.006
Open science0.0010.011
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.012
GPT teacher head0.384
Teacher spread0.371 · 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 designQualitative
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

Citations12
Published2009
Admission routes2
Has abstractyes

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