MétaCan
Menu
Back to cohort
Record W2116067358 · doi:10.5565/rev/tdevorado.25

Treating tuberculosis in North Korea. The experience of Eugene Bell Foundation

2015· article· en· W2116067358 on OpenAlexaff
Avram Agov

Bibliographic record

VenueTiempo devorado · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicKorean Peninsula Historical and Political Studies
Canadian institutionsLangara College
Fundersnot available
KeywordsTuberculosisDemocracyFoundation (evidence)Political scienceEconomic growthHumanitarian aidPopulationDiseaseWork (physics)Development economicsMedicineLawEngineeringEconomicsEnvironmental healthPolitics

Abstract

fetched live from OpenAlex

Tuberculosis, often referred to as “the disease of the poor”, spread in North Korea as a result of the severe decline in the country's socio-economic conditions in the 1990s. This article examines tuberculosis treatment in North Korea through the prism of the humanitarian work of the Eugene Bell Foundation (EBF), which spearheaded an international effort to help the population of the Democratic People’s Republic (DPRK) cope with the humanitarian crisis. In recent years, the EBF has devoted its treatment program to drug-resistant tuberculosis, which is the deadliest strain of the disease. The Foundation’s experience in this field offers a unique perspective on North Korea’s relations with non-governmental organizations. The EBF’s work in North Korea and its relations with officials and tuberculosis patients highlight the difficulties and challenges in managing humanitarian projects in the country. This case study shows, however, how people-to-people exchanges are an effective way to engage North Korea toward positive outcomes in dealing with specific problems in the humanitarian field. In particular, the EBF acts as a connecting node in a complex institutional and human network involving the two Koreas, the United States, and other countries

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.053
GPT teacher head0.312
Teacher spread0.260 · 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 designObservational
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

Citations1
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueTiempo devoradoSame topicKorean Peninsula Historical and Political StudiesFrench-language works237,207