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Record W2014675672 · doi:10.1111/1540-6237.8403010

Do Human Rights Matter in Bilateral Aid Allocation? A Quantitative Analysis of 21 Donor Countries<sup>*</sup>

2003· article· en· W2014675672 on OpenAlexaboutno aff
Eric Neumayer

Bibliographic record

VenueSocial Science Quarterly · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
Fundersnot available
KeywordsHuman rightsPoliticsCivil rightsPolitical sciencePersonal IntegrityDeveloped countryEconometric analysisDevelopment economicsEconomicsLawPublic economicsSociologyPsychologySocial psychologyPopulationDemography

Abstract

fetched live from OpenAlex

Objective. To analyze the role of human rights in aid allocation of 21 donor countries. Methods. Econometric analysis is applied to a panel covering the period 1985 to 1997. Results. Respect for civil/political rights plays a statistically significant role for most donors at the aid eligibility stage. Personal integrity rights, on the other hand, have a positive impact on aid eligibility for few donors only. At the level stage, most donors fail to promote respect for human rights in a consistent manner and often give more aid to countries with a poor record on either civil/political or personal integrity rights. No systematic difference is apparent between the like‐minded countries commonly regarded as committed to human rights (Canada, Denmark, the Netherlands, Norway, and Sweden) and the other donors. Conclusions. Contrary to their verbal commitment, donor countries do not consistently reward respect for human rights in their foreign aid allocation.

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)0.012
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.331
Teacher spread0.315 · 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 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

Citations220
Published2003
Admission routes1
Has abstractyes

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Same venueSocial Science QuarterlySame topicInternational Development and AidFrench-language works237,207