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Record W2011584804 · doi:10.3138/cjh.49.3.423

Humanitarian Action: The Joint Church Aid and Health Care Intervention in the Nigeria-Biafra War, 1967–1970

2014· article· en· W2011584804 on OpenAlexvenueno aff
Arua Oko Omaka

Bibliographic record

VenueJournal of History · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitarian aidHealth careAgency (philosophy)Economic growthIntervention (counseling)Spanish Civil WarPolitical sciencePublic administrationMedicineLawSociologyNursingEconomicsSocial science

Abstract

fetched live from OpenAlex

International humanitarian aid played an important role in the Nigeria-Biafra War, 1967-70. Relief aid was organized under two major umbrella bodies — the International Committee of the Red Cross (ICRC) and the Joint Church Aid (JCA). The JCA received support from Catholic and Protestant churches while the ICRC, an established humanitarian agency, relied on donations from many governments as well as from the United Nations International Children’s Emergency Fund (UNICEF). This paper focuses on the formation of the JCA as a humanitarian organization and examines its efforts to provide health care for the war victims in Biafra. Though the JCA has not received adequate scholarly attention, its humanitarian aid in Biafra was the first of its kind in the developing world and involved the largest civilian airlift in history. As this paper argues, the JCA’s health care intervention in Biafra was restricted to minimal care because of a lack of essential medications, equipment, food, and epidemiological expertise. Despite these challenges, however, the JCA managed to provide basic health care to over ten million persons in Biafra during the war. Further, the organization succeeded in providing aid without creating long-term dependency.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

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 studies0.0100.008
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.068
GPT teacher head0.256
Teacher spread0.188 · 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

Citations20
Published2014
Admission routes1
Has abstractyes

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