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Record W2126265159 · doi:10.1017/s0020818314000289

Multilateral Aid and Domestic Economic Interests

2014· article· en· W2126265159 on OpenAlexaboutno aff
Elena V. McLean

Bibliographic record

VenueInternational Organization · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
Fundersnot available
KeywordsArgument (complex analysis)IncentiveCommodityInternational economicsInternational tradeBusinessAid effectivenessPromotion (chess)EconomicsDeveloping countryPublic economicsEconomic growthPolitical scienceFinanceMarket economy

Abstract

fetched live from OpenAlex

Abstract Existing studies of foreign aid suggest that donor countries' economic groups, such as exporters, should be generally opposed to multilateral aid because multilateral flows do not allow donor countries to tie their aid implicitly or explicitly to the promotion of their domestic economic interests. However, economic groups can actually benefit from some types of multilateral aid, and this serves as an incentive for donor governments to support international organizations generating the benefits. I test my argument using data on aid allocated to the Multilateral Fund for the Implementation of the Montreal Protocol and the Global Environment Facility, and international trade by commodity. I find robust empirical support for the argument that when donors' domestic economic groups are likely to gain from opportunities created by international environmental organizations' programs, donor governments increase aid allocations to these organizations.

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)0.023
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0010.002
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.001

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 head0.006
GPT teacher head0.277
Teacher spread0.271 · 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

Citations51
Published2014
Admission routes1
Has abstractyes

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