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Record W7131873998 · doi:10.5281/zenodo.18801852

AN ASSESSMENT OF THE PROBLEM OF MANAGING FOREIGN AID IN NIGERIA

2024· article· W7131873998 on OpenAlexaff
Israel Obisesan

Bibliographic record

VenueOpen MIND · 2024
Typearticle
Language
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsInternational Political Science Association
Fundersnot available
KeywordsAccountabilityBureaucracyAid effectivenessPoliticsDevelopment aidCorporate governanceGood governanceForeign policyFace (sociological concept)

Abstract

fetched live from OpenAlex

This study, “An Assessment of the Problem of Managing Foreign Aid in Nigeria,” critically examines the structural, institutional, and political challenges associated with the management of foreign assistance in Nigeria. Despite being one of the largest recipients of development assistance in sub-Saharan Africa, Nigeria continues to face persistent development deficits, raising concerns about the efficiency, transparency, and accountability mechanisms governing foreign aid utilization. The research explores key issues such as weak institutional capacity, corruption, policy inconsistency, donor–recipient misalignment, bureaucratic bottlenecks, and inadequate monitoring and evaluation frameworks. It further analyzes how governance structures, political interference, and public financial management systems influence aid effectiveness. Drawing on secondary data, policy documents, scholarly literature, and reports from international development partners, the study situates Nigeria’s experience within broader global debates on aid effectiveness and sustainable development.

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)0.004
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.003
Scholarly communication0.0090.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.392
Teacher spread0.358 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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